Research ArticleImplementation of Intelligent Electronic Acupuncture SystemUsing Sensor Module
You-Sik Hong1 Baek-Ki Kim2 and Bong-Hwa Hong3
1 Department of Computer Science Sangji University Wonju 220-702 Republic of Korea2Department of Information amp Telecommunication Engineering Gangneung-Wonju National UniversityWonju 220-711 Republic of Korea
3 Department of Digital Media Engineering Kyung Hee Cyber University Seoul 130-739 Republic of Korea
Correspondence should be addressed to Baek-Ki Kim bkkimgwnuackr and Bong-Hwa Hong bhhongkhcuackr
Received 30 August 2013 Accepted 2 February 2014 Published 9 March 2014
Academic Editor Young-Sik Jeong
Copyright copy 2014 You-Sik Hong et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited
Conventional electronic acupuncture can stimulate only one acupuncture point and patients have to decide the time and thestrength by themselves In order to solve these problems intelligent electronic acupuncture using biometric sensors and fuzzytechnology was developed in this paper And wireless electronic acupuncture system using sensor modules was developed in thispaper We used the sensor modules to obtain a patientrsquos diagnosis signals These sensor modules consist of 5 parts The signalswere analyzed to make instructions for the treatment and the sensing pad for electronic acupuncture was designed In additionadaptive wireless acupuncture system was developed to adjust strength and time of acupuncture and several acupuncture pointsof patients by using fuzzy technology We implemented efficient wireless electronic acupuncture system to get acupuncture easilyusing intelligent diagnosis system
1 Introduction
The electronic acupuncture is different from the traditionalacupuncture in their shape and treatment method But itsbasic principle of treatment is the sameMore than 60 percentof the electronic acupunctures developed in the countryuse low frequency and the rest is developed using instanta-neous electro stimulation Existing low-frequency therapeu-tic apparatuses are simple frequency generator (16sim32Hz)which attaches electrodes to patientrsquos diseased area Patientcannot be treated effectively because it does not providedetailed frequency Furthermore it cannot find acupuncturepoints since it has no consideration of the patientsrsquo sex ageweight illness and so forth And it causes a problem thatsome children and elderly people are bruised or woundedafter getting electronic acupuncture due to inappropriateacupuncture time and strength [1]
Intelligent electronic acupuncture means that theacupuncture system can treat a patient automatically withacupuncture adapted voltage current and frequency Toperform this electronic acupuncture the system has function
of sensing and treatment simultaneously And the systemrequires an accurate analysis and processing technique oflogical and statistical data using fuzzy [2 3]
The pulse is considered an important factor in orientalmedicine because a personrsquos pulse rate may reflect his or herhealth condition For example if a patientrsquos heart stops itis a very serious situation and this situation can be judgedby pulse Oriental doctors have considered pulse rates asimportant data in diagnosis But the existing blood pressurepulse analyzers have some problems It is uncertain whetherthe blood pressure pulse analyzing sensor is located preciselyon the radial artery and it is also difficult to diagnose pulseexactly depending on the thickness of forearm Furthermorethe analogue type of blood pressure pulse analyzers hasproblems with quantification of the blood pressure pulseAlthough some people may have the same forearm lengthbut the thickness of their blood vessel may differ Thereforethere is no set of data that is considered reliable enough tojudge the accuracy of blood pressure pulse rates Orientaldoctors should not only judge the basic biological signalssuch as the pulsersquos size strength and speed but should also
Hindawi Publishing CorporationInternational Journal of Distributed Sensor NetworksVolume 2014 Article ID 238502 7 pageshttpdxdoiorg1011552014238502
2 International Journal of Distributed Sensor Networks
Body signal parts
∙ Blood pressure sensing
∙ Skin conductivity sensing
∙ ECG signal sensing
∙ Oxygen saturation signal sensing
∙ Body temperature sensing
Signal analyzing and treatment system
∙ Electronic acupuncture part
Monitoring and DB generating
Figure 1 Whole system diagram of the intelligent electronic acupuncture system
consider the basic and quantitative analysis of the pulse inorder tomake an accurate diagnosis Also the doctors shouldconsider physical characteristics such as the thickness ofthe skin and blood vessels in order to reach an accurateconclusion Therefore measurement of the blood flow rate isa vital indicator in understanding the blood pressure rate andhow the substances in the blood are transported [4ndash6]
The method of exiting diagnosis has a problem whichcannot diagnose the old and the infirm exactly because thepatientrsquos condition including gender age skin is not takeninto consideration To solve this problem we analyzed thefine distinction considering thickness of skin and blood ves-sels and pulse whether they are big or small strong or weakand fast or slow We proposed the algorithm that diagnosesthe condition of a patient optimally using intelligent fuzzytechnique [7 8]
Adaptive wireless acupuncture system was developedin this paper by using pulse diagnosis system to adjuststrength and time of acupuncture and several acupuncturepoints of patients to whom intellectual fuzzy technology is
applied Conventional electronic acupuncture cannot findthe acupuncture points at once However SW which canstimulate multiple acupuncture points and calculate thetime of the electronic acupuncture was developed in thispaper Conventional electronic acupuncture only stimulatesthe acupuncture point but the electronic acupuncture withKIT (SW + HW) developed in this paper made remote orself-diagnosis possible using the conditions of the patientsand disease reasoning function Doctorsrsquo help is neededto find the acupuncture point with conventional electronicacupuncture Intelligent electronic acupuncture that easilycalculates optimal acupuncture time considering the patientsrsquohealth condition with smart phones was developed in thispaper
Figure 1 shows thewhole systemdiagramof the intelligentelectronic acupuncture system It consists of 4 parts The firstpart is a sensor module the second part is a main part whichanalyzes the transferred signals and generates the treatmentsignalsThe third part is an electronic acupuncture partwhichapplies electronic acupuncture according to treatment signals
International Journal of Distributed Sensor Networks 3
from the main partThe last part is a program for monitoringand generating DB
The composition of this paper is as follows Section 2is about a sensor module for electronic acupunctureand Section 3 is about intelligent pulse diagnosis algo-rithm Section 4 deals with implementation of the electronicacupuncture system Finally the conclusion is made inSection 5
2 Sensor Module for Electronic Acupuncture
We used several sensor modules to obtain a patientrsquos diagno-sis signals These sensor modules consist of 5 parts and theydetect and analyze the abnormal signals from human body
Figure 2 shows the sensor modules for electronicacupuncture system The measured signals from the eachsensor of modules are transferred to main the part
(1) Pulsimeter module It measures pulse rate It mea-sures the data from the finger connected to the fingersensor
(2) EGC module It measures electrocardiogram(3) SPO2 module It measures oxygen saturation of
blood(4) Skin conduction module It measures conductivity of
palmar skin(5) Body temperature module It measures temperature
of human body
3 Intelligent Pulse Diagnosis Algorithm
The intelligent pulse diagnosis system is composed of threeparts The first part is composed of the sensor to detect theconductance which is appropriate for injured part of humanbody and reference signal generator to adjust the signalgenerated from the patients The second part is composed ofDSP (Digital Signal Processor) board in which the signals aremeasured and classified using fuzzy algorithm The last partis composed of a computer system that displays the signalfrom DSP board to the monitor and analysis software todiagnose the patients Figure 3 shows the whole diagram ofphysical signal data network for electronic acupuncture Thealgorithm consists of 3 parts First step is sensing methodsthe second step is indexing methods and the third step isclassification methods
Pulse is beat-wave pattern of chest wall and great arteriesaccording to heartbeat The main purpose of pulse is toobserve cardiomotility and blood movement Recently studyusing physical characteristics shows that pulse wave patterncan change depending on condition of blood vessels andblood circulation The pulse wave pattern can be obtainedby second differentiation of digital plethysmogram usingphysical specific status such as uncertain inflection pointsIn this paper we classified a patientrsquos physical condition intothree categories as dangerous ordinary and normal condi-tion adapting pulse diagnosis algorithm using accelerationpulse wave pattern [9]
Fuzzy rules are generally presented with IF-THEN for-mat Fuzzy inference is procedures that infer new relationsor facts from the given rules and max-min reference is used
Input 119909 is 1198601015840 AND 119910 is 1198611015840
1198771 IF 119909 is 1198601 AND 119910 is 1198611 THEN 119911 is 1198621OR 1198772 IF 119909 is 1198602 AND 119910 is 1198612 THEN 119911 is 1198622
OR 119877119899 IF 119909 is 119860119899 AND 119910 is 119861119899 THEN 119911 is 119862119899Conclusion 119911 is 119862
Combination Function of Trust Value 1 and 2 type of fuzzycreation rule reduced from type of 5 and 6 can come to thesamenode and conclusion through different inference path toinfer fuzzy In this node the same conclusion reached two ofmore different trust value In this case combination functionof trust value is used to recalculate trust value of conclusion[2 8]
120573
119888= 120573comb (120573119888 120573
old119888) = max (120573
119888 120573
old119888) (1)
Here 120573old119888
is trust value of the conclusion reached throughinference path already 120573
119888is trust value of other conclusion
reached through another inference path If the 4 patientsrsquo (ab c d) illness condition is end-stage the value is displayed as08ndash10 shown in the left in case of the middle stage the valueis 04ndash07 and in case of the first stage the value is displayedas 01ndash03 The value in the middle shows patientrsquos physicalcondition For example if the patientrsquos height is 150 cm andweight is lower than 45 kg the value is displayed as 01ndash03
When the patientrsquos height is between 151 and 170 cm andthe weight is between 46 kg and 70 kg the value is displayedas 04ndash07 and when the height is 171 cmndash200 cm and weightis 71 kgndash130 kg the value is displayed as 08ndash10 In Figure 3the process to calculate fuzzy correction factor according topatientrsquos physical condition is shown
4 Implementation of the ElectronicAcupuncture System
Electronic acupuncture system with built in multi pad whichcan find out the condition of the patients automatically andtreat the patients simultaneously The system includes thefunction that can treat the patients with acupuncture andadjust voltage current frequency oscillation automaticallyaccording to their physical conditions To perform the func-tion the system senses and treats acupuncture simultane-ously and requires logical and statistical data processingtechnique using fuzzy and exact analysis Installing the 5round pads underneath the palm we can change the signaland then adaptive acupuncture treatment can be given
At this point measurement of the signal uses the wirelesstype instead of cable type Because the wireless type hasadvantage of convenience to get acupuncture reduction ofnoise by using cable connected to a computer system andprevention of electric shock depending on abrupt high-tension electricity [10 11]
4 International Journal of Distributed Sensor Networks
Pulse sensor
Blood pressure and sugar sensor
ECG sensor
Hmote 2420
Infrared temperature
(a) Sensor module parts considering patientrsquos physical conditions
Bloodpressure
Bloodpressure
sensor
REF
PGAAMP AD
CC2430
USB to serial
BAT and DCDC
15
PGAAMP CC2430
USB to serial
BAT and DCDC
13
EGC3
Notchfilter AD
CC2430
USB to serial
BAT and DCDC
EGC2
EGC1
11
Photodiode
AMPLED
AD
DA
PGAAMP PIC18F85
USB to serial
BAT and DCDC
1
2
30
AD
MOSFET
TRarray
TFTLCD
UART
SD slop
DCDC
SSPV210(cortex-A8)
SDRAM
Nand flash
CPLDdecoder
AudioALC5622USB host
20
ZigBee
Ethernet
WiFi
Bluetooth 20
20
16bit
24bit24bit
10M
512MB
256MB
2G
(b) Block diagram of Sensor modules
Figure 2 Sensor modules for electronic acupuncture system
In order to treat acupuncture it is important not only toget information from the human body but also to learn agessexes height and weight of the patients To do this controlvariables using fuzzy algorithm are made before treatment ofacupuncture
Figure 4 shows Circuit of the acupuncture signal Thepart of sensing pad and contact point of the fingertipmade of stripe array type to distribute contact point areaevenly after being plated with gold to reduce electric resis-tance
International Journal of Distributed Sensor Networks 5
RF channel 11Group ID
Hmoto2420 sender
Hmoto2420 sender
Hmoto2420 sender
Hmoto2420 senderHmoto2420 sender
Hmoto2420 receiver
Hmoto2420 receiver
Hmoto2420 receiver
Hmoto2420 receiverHmoto2420 receiver
0 times 05
RF channel 11Group ID 0 times 01 RF channel 11
Group ID 0 times 03
RF channel 12Group ID 0 times 01
RF channel 13Group ID 0 times 01
2405Mhz2410Mhz
2415Mhz
Figure 3 Whole diagram of physical signal data network for electronic acupuncture
PWM-2
TX
B_DIR-2
A_DIR-2B_DIR-1
A_DIR-1
D_DIR-2D_DIR-1C_DIR-2C_DIR-1
RX
A_DIR-1A_DIR-2PWM-1
LOAD
PWM-1
Load
C11104
C15104
C16 C17104
U3MAX232
1381110
134526
129147
1615
R1INR2INT1INT2IN
C+
C2+
V+
R1OUTR2OUTT1OUTT2OUT
VCC
GN
D
+
C4
+
C8
+
C5
+C10
R1220
Q1C1011
23
R8
R5 R7
R3
R6
+
U52
36
81
C13104
C18104
C12104
C14104
LS1Buzzer
+
+C3
U1AT89C2051
1
10
1213141516171819
20
23678911
54
RSTVPP
GN
D
P10AIN0P11AIN1
P12P13P14P15P16P17
P30RXDP31TXDP32INTOP33INT1P34T0P35T1P37
XTAL1XTAL2
R4
D1 1N4007
C718P(CH) +
C9
R2
C618P(CH)
C2104
X-TAL1
U232
1
VINVOUT
AD
J
C1 104
U4
L6203
4
5
3
8
1
6
2
9
711
10
+VIN
+BOOST
+CURLIM
+SENSE
REF
LIM
DIM
D2
1N4148
GND
Output module-CH1
C1minus
C2minus
Vminus
Data A
Data B
10uf25V
10uf25V
10uf25V
10uf25V
10uf25V
+5V
+5V
+5V
+5V
+5V
110592m
82K
minus
minus
1 uF16 V
22uF16V
minusVINminusBOOST
minusCURLIM
minusVOUT
1K
1K
2K
10K 20K
20K
Output CH1
Output CH1
VCC
VCC
VCC
Figure 4 Circuit of the acupuncture signal
In this paper we designed the optimal algorithm whichcould judge the remote medical diagnosis using fuzzy logicand fuzzy inference rules and we simulated the process tocalculate the optimal acupuncture time of the body conditionof patients We produced the wireless communication partto transmit condition of patientsrsquo pulse skin conductanceand oxygen saturation data to userrsquos terminal or remotemedical terminal and to receive the control signal fromuserrsquosterminal or remote medical terminal
To do this we made the sensing pad the circuit of AMPand acupuncture signal wireless communicationmodule and
charging circuit for storage battery And also we proposed thesoftware including algorithm of analysis and control usingfuzzy technique Existing acupuncture system using DSPhas a complex structure uses up a lot of electricity and itrsquosbig and expensive But the adaptive wireless acupuncturesystem proposed in this paper is simple inexpensive andsafe Figure 5 shows simulation of the glove type electronicacupuncture
To implement wireless system we used the way of RFdata modem for wireless communication using NarrowbandFSK The feature of this way is robust to noise and it can
6 International Journal of Distributed Sensor Networks
Figure 5 Simulation of the glove type electronic acupuncture
Figure 6 Data transmitter and receiver using RF communication
transmit data easily by simple communication protocol Andthis system is adapt to designmulti type data communicationsystem and can be designed by low power one 3V batteryin case of short distance We considered not only resistancemeasurement but capacitive component to reduce errordepending on several conditions of human body To do thiswe applied the pulse wave DC 50Vsim200V 500 uAsim1500 uAintermittent stimulation of 5Hzsim5KHz to the main pad andfingertip andmeasured the voltage peak and phase frequency[12 13]
We used 470MHz band frequency and designed thesystem to change 21 physical frequency And logical addressof a channel corresponding to each adaptive acupuncture wasassigned using polling technique and then calledThe systemsupports half duplex communicationThis way is suitable forthe system because the system requires low data and uses rel-atively low speed communicationThe output power of wire-less signal using button type battery is 1mW and it is adequateto transmit data without noise The speed of transmissionis 1200sim9600 bps and wireless encoding uses a way of Bi-phase Manchester code Communication between notebookcomputer and wireless modem uses RS232C Figure 6 showsthe data transmitter and receiver using RF communicationFor remote medical treatment the transmitter acquires data
Figure 7 Transmitreceive system for ubiquitous network
Figure 8 Analysis of electro stimulation to fingertips
Figure 9 Output of electronic acupuncture needle time simulationusing FIS matlab
from 4 sensors and then transmit the data to receiver usingRF communication
In Figure 7 the system consists of transmit andreceive system parts for ubiquitous network It is madeof MSP240CPU and CC2420 RF chip Figure 8 showsanalysis of electro stimulation to fingertips using padsTo obtain signal we send a reference signal to palm andthen decide body condition of patients on the basis of dataobtained from pre-investigation using sensing pads andMCU attached to fingertips As soon as signal processingis completed electric stimulation signal generated by fuzzyalgorithm is transmitted to sensing pads
Table 1 explains fuzzy inference of a variety of patientswith the same disease according to varying blood pressurecondition Heart rate condition and vascular aging condi-tion In other words Table 1 clearly shows that the systemcalculate varying time of acupuncture for different patientsphysical conditions
Figure 9 shows the Output of electronic acupunctureneedle time simulation using Fuzzy Inference SystemMatlabIt explains how the system calculates the output condition
International Journal of Distributed Sensor Networks 7
Table 1 Electronic acupuncture needle time simulation
Patient biometric information Optimal acupuncture needle timeInput data (minutes)
Blood pressure condition Heart rate condition Vascular aging condition Conventional IntelligenceMedium Medium Small 10 12Big Big Big 10 06Big Big Medium 10 08Medium Medium Medium 10 11Medium Big Big 10 07Medium Medium Small 10 10Small Big Big 10 07Small Medium Big 10 06Small Small Small 10 05
of the time for acupuncture from the input data of the 3conditions of patient physical conditions
5 Conclusion
In this paper we implemented intelligent electronic acupunc-ture system using sensor modules We used the sensormodules to obtain a patientrsquos diagnosis signals These sensormodules consist of 5 parts These sensor modules detect andanalyze the abnormal signals from human bodyWe analyzedthe signals to make instructions for the treatment And thenwedesigned the sensing pads for electronic acupuncture Andwe also developed adaptive wireless acupuncture system toadjust strength and time of acupuncture and several acupunc-ture points of patients by using fuzzy technology We madethe sensing pads the circuit of AMP and acupuncture signalWe implemented efficient electronic acupuncture system toget acupuncture easily using intelligent diagnosis systemThe intelligent acupuncture system proposed in this paperis simple inexpensive and safe compared with conventionalacupuncture systems
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITSWCreative research program supervised by the NIPA (NationalIT Industry Promotion Agency)rdquo (NIPA-2013-H0502-13-1112)
References
[1] Y S Hong H K Kim and B K Kim ldquoImplementation of adap-tive electronic acupuncture system using intelligent diagnosissystemrdquo International Journal of Control and Automation vol5 no 3 pp 141ndashl52 2012
[2] H K Baruah ldquoThe theory of fuzzy sets beliefs and realitiesrdquoInternational Journal of Energy Information and Communica-tions vol 2 no 2 pp 1ndash22 2011
[3] J Jeong ldquoThe development of web-based decision tree programfor the analysis of clinical information ideas constitutionrdquoKorea Institute of Oriental Medicine vol 12 pp 81ndash87 2008
[4] Y J Lee J Lee H J Lee H H Yoo E J Choi and J Y KimldquoStudy on the characteristics of blood vessel pulse area usingultrasonicrdquo Korea Institute of Oriental Medicine Researches vol13 no 3 pp 111ndash119 2007
[5] P A Shaltis A T Reisner and H H Asada ldquoCuffless bloodpressure monitoring using hydrostatic pressure changesrdquo IEEETransactions on Biomedical Engineering vol 55 pp 1775ndash17772008
[6] National College of Oriental MedicineDiagnostics Saint Func-tionality of Medicine St Functional Medicine 2008 GunjaPublisher 2007
[7] Department of Medical Sciences College of Oriental MedicineKyung Hee University ldquoMedical practice materialsrdquo 2007
[8] O P Verma and S Singh ldquoA fuzzy impulse noise filter based onboundary discriminative noise detectionrdquo Journal of Informa-tion Processing System vol 9 no 1 2013
[9] S-S Lee M-C An and S-H Ahn ldquoA new measurementmethod of a radial pulse wave usingmultiple hall array devicesrdquoJournal of Magnetics vol 14 no 3 pp 132ndash136 2009
[10] S Haykin Modem Wireless Communication Prentice-Hall2003
[11] A Swami andH YaWireless Sensor Networks Signal Processingand Communications John Wiley amp Sons 2007
[12] J K-Y Ng ldquoUbiquitous healthcare healthcare systems andapplications enabled by mobile and wirelessrdquo Journal of Con-vergence vol 3 no 2 2012
[13] A Sinha and D K Lobiyal ldquoPerformance evaluation of dataaggregation for cluster-based wireless sensor networkrdquoHuman-Centric Computing and Information Sciences vol 3 article 132013
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DistributedSensor Networks
International Journal of
2 International Journal of Distributed Sensor Networks
Body signal parts
∙ Blood pressure sensing
∙ Skin conductivity sensing
∙ ECG signal sensing
∙ Oxygen saturation signal sensing
∙ Body temperature sensing
Signal analyzing and treatment system
∙ Electronic acupuncture part
Monitoring and DB generating
Figure 1 Whole system diagram of the intelligent electronic acupuncture system
consider the basic and quantitative analysis of the pulse inorder tomake an accurate diagnosis Also the doctors shouldconsider physical characteristics such as the thickness ofthe skin and blood vessels in order to reach an accurateconclusion Therefore measurement of the blood flow rate isa vital indicator in understanding the blood pressure rate andhow the substances in the blood are transported [4ndash6]
The method of exiting diagnosis has a problem whichcannot diagnose the old and the infirm exactly because thepatientrsquos condition including gender age skin is not takeninto consideration To solve this problem we analyzed thefine distinction considering thickness of skin and blood ves-sels and pulse whether they are big or small strong or weakand fast or slow We proposed the algorithm that diagnosesthe condition of a patient optimally using intelligent fuzzytechnique [7 8]
Adaptive wireless acupuncture system was developedin this paper by using pulse diagnosis system to adjuststrength and time of acupuncture and several acupuncturepoints of patients to whom intellectual fuzzy technology is
applied Conventional electronic acupuncture cannot findthe acupuncture points at once However SW which canstimulate multiple acupuncture points and calculate thetime of the electronic acupuncture was developed in thispaper Conventional electronic acupuncture only stimulatesthe acupuncture point but the electronic acupuncture withKIT (SW + HW) developed in this paper made remote orself-diagnosis possible using the conditions of the patientsand disease reasoning function Doctorsrsquo help is neededto find the acupuncture point with conventional electronicacupuncture Intelligent electronic acupuncture that easilycalculates optimal acupuncture time considering the patientsrsquohealth condition with smart phones was developed in thispaper
Figure 1 shows thewhole systemdiagramof the intelligentelectronic acupuncture system It consists of 4 parts The firstpart is a sensor module the second part is a main part whichanalyzes the transferred signals and generates the treatmentsignalsThe third part is an electronic acupuncture partwhichapplies electronic acupuncture according to treatment signals
International Journal of Distributed Sensor Networks 3
from the main partThe last part is a program for monitoringand generating DB
The composition of this paper is as follows Section 2is about a sensor module for electronic acupunctureand Section 3 is about intelligent pulse diagnosis algo-rithm Section 4 deals with implementation of the electronicacupuncture system Finally the conclusion is made inSection 5
2 Sensor Module for Electronic Acupuncture
We used several sensor modules to obtain a patientrsquos diagno-sis signals These sensor modules consist of 5 parts and theydetect and analyze the abnormal signals from human body
Figure 2 shows the sensor modules for electronicacupuncture system The measured signals from the eachsensor of modules are transferred to main the part
(1) Pulsimeter module It measures pulse rate It mea-sures the data from the finger connected to the fingersensor
(2) EGC module It measures electrocardiogram(3) SPO2 module It measures oxygen saturation of
blood(4) Skin conduction module It measures conductivity of
palmar skin(5) Body temperature module It measures temperature
of human body
3 Intelligent Pulse Diagnosis Algorithm
The intelligent pulse diagnosis system is composed of threeparts The first part is composed of the sensor to detect theconductance which is appropriate for injured part of humanbody and reference signal generator to adjust the signalgenerated from the patients The second part is composed ofDSP (Digital Signal Processor) board in which the signals aremeasured and classified using fuzzy algorithm The last partis composed of a computer system that displays the signalfrom DSP board to the monitor and analysis software todiagnose the patients Figure 3 shows the whole diagram ofphysical signal data network for electronic acupuncture Thealgorithm consists of 3 parts First step is sensing methodsthe second step is indexing methods and the third step isclassification methods
Pulse is beat-wave pattern of chest wall and great arteriesaccording to heartbeat The main purpose of pulse is toobserve cardiomotility and blood movement Recently studyusing physical characteristics shows that pulse wave patterncan change depending on condition of blood vessels andblood circulation The pulse wave pattern can be obtainedby second differentiation of digital plethysmogram usingphysical specific status such as uncertain inflection pointsIn this paper we classified a patientrsquos physical condition intothree categories as dangerous ordinary and normal condi-tion adapting pulse diagnosis algorithm using accelerationpulse wave pattern [9]
Fuzzy rules are generally presented with IF-THEN for-mat Fuzzy inference is procedures that infer new relationsor facts from the given rules and max-min reference is used
Input 119909 is 1198601015840 AND 119910 is 1198611015840
1198771 IF 119909 is 1198601 AND 119910 is 1198611 THEN 119911 is 1198621OR 1198772 IF 119909 is 1198602 AND 119910 is 1198612 THEN 119911 is 1198622
OR 119877119899 IF 119909 is 119860119899 AND 119910 is 119861119899 THEN 119911 is 119862119899Conclusion 119911 is 119862
Combination Function of Trust Value 1 and 2 type of fuzzycreation rule reduced from type of 5 and 6 can come to thesamenode and conclusion through different inference path toinfer fuzzy In this node the same conclusion reached two ofmore different trust value In this case combination functionof trust value is used to recalculate trust value of conclusion[2 8]
120573
119888= 120573comb (120573119888 120573
old119888) = max (120573
119888 120573
old119888) (1)
Here 120573old119888
is trust value of the conclusion reached throughinference path already 120573
119888is trust value of other conclusion
reached through another inference path If the 4 patientsrsquo (ab c d) illness condition is end-stage the value is displayed as08ndash10 shown in the left in case of the middle stage the valueis 04ndash07 and in case of the first stage the value is displayedas 01ndash03 The value in the middle shows patientrsquos physicalcondition For example if the patientrsquos height is 150 cm andweight is lower than 45 kg the value is displayed as 01ndash03
When the patientrsquos height is between 151 and 170 cm andthe weight is between 46 kg and 70 kg the value is displayedas 04ndash07 and when the height is 171 cmndash200 cm and weightis 71 kgndash130 kg the value is displayed as 08ndash10 In Figure 3the process to calculate fuzzy correction factor according topatientrsquos physical condition is shown
4 Implementation of the ElectronicAcupuncture System
Electronic acupuncture system with built in multi pad whichcan find out the condition of the patients automatically andtreat the patients simultaneously The system includes thefunction that can treat the patients with acupuncture andadjust voltage current frequency oscillation automaticallyaccording to their physical conditions To perform the func-tion the system senses and treats acupuncture simultane-ously and requires logical and statistical data processingtechnique using fuzzy and exact analysis Installing the 5round pads underneath the palm we can change the signaland then adaptive acupuncture treatment can be given
At this point measurement of the signal uses the wirelesstype instead of cable type Because the wireless type hasadvantage of convenience to get acupuncture reduction ofnoise by using cable connected to a computer system andprevention of electric shock depending on abrupt high-tension electricity [10 11]
4 International Journal of Distributed Sensor Networks
Pulse sensor
Blood pressure and sugar sensor
ECG sensor
Hmote 2420
Infrared temperature
(a) Sensor module parts considering patientrsquos physical conditions
Bloodpressure
Bloodpressure
sensor
REF
PGAAMP AD
CC2430
USB to serial
BAT and DCDC
15
PGAAMP CC2430
USB to serial
BAT and DCDC
13
EGC3
Notchfilter AD
CC2430
USB to serial
BAT and DCDC
EGC2
EGC1
11
Photodiode
AMPLED
AD
DA
PGAAMP PIC18F85
USB to serial
BAT and DCDC
1
2
30
AD
MOSFET
TRarray
TFTLCD
UART
SD slop
DCDC
SSPV210(cortex-A8)
SDRAM
Nand flash
CPLDdecoder
AudioALC5622USB host
20
ZigBee
Ethernet
WiFi
Bluetooth 20
20
16bit
24bit24bit
10M
512MB
256MB
2G
(b) Block diagram of Sensor modules
Figure 2 Sensor modules for electronic acupuncture system
In order to treat acupuncture it is important not only toget information from the human body but also to learn agessexes height and weight of the patients To do this controlvariables using fuzzy algorithm are made before treatment ofacupuncture
Figure 4 shows Circuit of the acupuncture signal Thepart of sensing pad and contact point of the fingertipmade of stripe array type to distribute contact point areaevenly after being plated with gold to reduce electric resis-tance
International Journal of Distributed Sensor Networks 5
RF channel 11Group ID
Hmoto2420 sender
Hmoto2420 sender
Hmoto2420 sender
Hmoto2420 senderHmoto2420 sender
Hmoto2420 receiver
Hmoto2420 receiver
Hmoto2420 receiver
Hmoto2420 receiverHmoto2420 receiver
0 times 05
RF channel 11Group ID 0 times 01 RF channel 11
Group ID 0 times 03
RF channel 12Group ID 0 times 01
RF channel 13Group ID 0 times 01
2405Mhz2410Mhz
2415Mhz
Figure 3 Whole diagram of physical signal data network for electronic acupuncture
PWM-2
TX
B_DIR-2
A_DIR-2B_DIR-1
A_DIR-1
D_DIR-2D_DIR-1C_DIR-2C_DIR-1
RX
A_DIR-1A_DIR-2PWM-1
LOAD
PWM-1
Load
C11104
C15104
C16 C17104
U3MAX232
1381110
134526
129147
1615
R1INR2INT1INT2IN
C+
C2+
V+
R1OUTR2OUTT1OUTT2OUT
VCC
GN
D
+
C4
+
C8
+
C5
+C10
R1220
Q1C1011
23
R8
R5 R7
R3
R6
+
U52
36
81
C13104
C18104
C12104
C14104
LS1Buzzer
+
+C3
U1AT89C2051
1
10
1213141516171819
20
23678911
54
RSTVPP
GN
D
P10AIN0P11AIN1
P12P13P14P15P16P17
P30RXDP31TXDP32INTOP33INT1P34T0P35T1P37
XTAL1XTAL2
R4
D1 1N4007
C718P(CH) +
C9
R2
C618P(CH)
C2104
X-TAL1
U232
1
VINVOUT
AD
J
C1 104
U4
L6203
4
5
3
8
1
6
2
9
711
10
+VIN
+BOOST
+CURLIM
+SENSE
REF
LIM
DIM
D2
1N4148
GND
Output module-CH1
C1minus
C2minus
Vminus
Data A
Data B
10uf25V
10uf25V
10uf25V
10uf25V
10uf25V
+5V
+5V
+5V
+5V
+5V
110592m
82K
minus
minus
1 uF16 V
22uF16V
minusVINminusBOOST
minusCURLIM
minusVOUT
1K
1K
2K
10K 20K
20K
Output CH1
Output CH1
VCC
VCC
VCC
Figure 4 Circuit of the acupuncture signal
In this paper we designed the optimal algorithm whichcould judge the remote medical diagnosis using fuzzy logicand fuzzy inference rules and we simulated the process tocalculate the optimal acupuncture time of the body conditionof patients We produced the wireless communication partto transmit condition of patientsrsquo pulse skin conductanceand oxygen saturation data to userrsquos terminal or remotemedical terminal and to receive the control signal fromuserrsquosterminal or remote medical terminal
To do this we made the sensing pad the circuit of AMPand acupuncture signal wireless communicationmodule and
charging circuit for storage battery And also we proposed thesoftware including algorithm of analysis and control usingfuzzy technique Existing acupuncture system using DSPhas a complex structure uses up a lot of electricity and itrsquosbig and expensive But the adaptive wireless acupuncturesystem proposed in this paper is simple inexpensive andsafe Figure 5 shows simulation of the glove type electronicacupuncture
To implement wireless system we used the way of RFdata modem for wireless communication using NarrowbandFSK The feature of this way is robust to noise and it can
6 International Journal of Distributed Sensor Networks
Figure 5 Simulation of the glove type electronic acupuncture
Figure 6 Data transmitter and receiver using RF communication
transmit data easily by simple communication protocol Andthis system is adapt to designmulti type data communicationsystem and can be designed by low power one 3V batteryin case of short distance We considered not only resistancemeasurement but capacitive component to reduce errordepending on several conditions of human body To do thiswe applied the pulse wave DC 50Vsim200V 500 uAsim1500 uAintermittent stimulation of 5Hzsim5KHz to the main pad andfingertip andmeasured the voltage peak and phase frequency[12 13]
We used 470MHz band frequency and designed thesystem to change 21 physical frequency And logical addressof a channel corresponding to each adaptive acupuncture wasassigned using polling technique and then calledThe systemsupports half duplex communicationThis way is suitable forthe system because the system requires low data and uses rel-atively low speed communicationThe output power of wire-less signal using button type battery is 1mW and it is adequateto transmit data without noise The speed of transmissionis 1200sim9600 bps and wireless encoding uses a way of Bi-phase Manchester code Communication between notebookcomputer and wireless modem uses RS232C Figure 6 showsthe data transmitter and receiver using RF communicationFor remote medical treatment the transmitter acquires data
Figure 7 Transmitreceive system for ubiquitous network
Figure 8 Analysis of electro stimulation to fingertips
Figure 9 Output of electronic acupuncture needle time simulationusing FIS matlab
from 4 sensors and then transmit the data to receiver usingRF communication
In Figure 7 the system consists of transmit andreceive system parts for ubiquitous network It is madeof MSP240CPU and CC2420 RF chip Figure 8 showsanalysis of electro stimulation to fingertips using padsTo obtain signal we send a reference signal to palm andthen decide body condition of patients on the basis of dataobtained from pre-investigation using sensing pads andMCU attached to fingertips As soon as signal processingis completed electric stimulation signal generated by fuzzyalgorithm is transmitted to sensing pads
Table 1 explains fuzzy inference of a variety of patientswith the same disease according to varying blood pressurecondition Heart rate condition and vascular aging condi-tion In other words Table 1 clearly shows that the systemcalculate varying time of acupuncture for different patientsphysical conditions
Figure 9 shows the Output of electronic acupunctureneedle time simulation using Fuzzy Inference SystemMatlabIt explains how the system calculates the output condition
International Journal of Distributed Sensor Networks 7
Table 1 Electronic acupuncture needle time simulation
Patient biometric information Optimal acupuncture needle timeInput data (minutes)
Blood pressure condition Heart rate condition Vascular aging condition Conventional IntelligenceMedium Medium Small 10 12Big Big Big 10 06Big Big Medium 10 08Medium Medium Medium 10 11Medium Big Big 10 07Medium Medium Small 10 10Small Big Big 10 07Small Medium Big 10 06Small Small Small 10 05
of the time for acupuncture from the input data of the 3conditions of patient physical conditions
5 Conclusion
In this paper we implemented intelligent electronic acupunc-ture system using sensor modules We used the sensormodules to obtain a patientrsquos diagnosis signals These sensormodules consist of 5 parts These sensor modules detect andanalyze the abnormal signals from human bodyWe analyzedthe signals to make instructions for the treatment And thenwedesigned the sensing pads for electronic acupuncture Andwe also developed adaptive wireless acupuncture system toadjust strength and time of acupuncture and several acupunc-ture points of patients by using fuzzy technology We madethe sensing pads the circuit of AMP and acupuncture signalWe implemented efficient electronic acupuncture system toget acupuncture easily using intelligent diagnosis systemThe intelligent acupuncture system proposed in this paperis simple inexpensive and safe compared with conventionalacupuncture systems
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITSWCreative research program supervised by the NIPA (NationalIT Industry Promotion Agency)rdquo (NIPA-2013-H0502-13-1112)
References
[1] Y S Hong H K Kim and B K Kim ldquoImplementation of adap-tive electronic acupuncture system using intelligent diagnosissystemrdquo International Journal of Control and Automation vol5 no 3 pp 141ndashl52 2012
[2] H K Baruah ldquoThe theory of fuzzy sets beliefs and realitiesrdquoInternational Journal of Energy Information and Communica-tions vol 2 no 2 pp 1ndash22 2011
[3] J Jeong ldquoThe development of web-based decision tree programfor the analysis of clinical information ideas constitutionrdquoKorea Institute of Oriental Medicine vol 12 pp 81ndash87 2008
[4] Y J Lee J Lee H J Lee H H Yoo E J Choi and J Y KimldquoStudy on the characteristics of blood vessel pulse area usingultrasonicrdquo Korea Institute of Oriental Medicine Researches vol13 no 3 pp 111ndash119 2007
[5] P A Shaltis A T Reisner and H H Asada ldquoCuffless bloodpressure monitoring using hydrostatic pressure changesrdquo IEEETransactions on Biomedical Engineering vol 55 pp 1775ndash17772008
[6] National College of Oriental MedicineDiagnostics Saint Func-tionality of Medicine St Functional Medicine 2008 GunjaPublisher 2007
[7] Department of Medical Sciences College of Oriental MedicineKyung Hee University ldquoMedical practice materialsrdquo 2007
[8] O P Verma and S Singh ldquoA fuzzy impulse noise filter based onboundary discriminative noise detectionrdquo Journal of Informa-tion Processing System vol 9 no 1 2013
[9] S-S Lee M-C An and S-H Ahn ldquoA new measurementmethod of a radial pulse wave usingmultiple hall array devicesrdquoJournal of Magnetics vol 14 no 3 pp 132ndash136 2009
[10] S Haykin Modem Wireless Communication Prentice-Hall2003
[11] A Swami andH YaWireless Sensor Networks Signal Processingand Communications John Wiley amp Sons 2007
[12] J K-Y Ng ldquoUbiquitous healthcare healthcare systems andapplications enabled by mobile and wirelessrdquo Journal of Con-vergence vol 3 no 2 2012
[13] A Sinha and D K Lobiyal ldquoPerformance evaluation of dataaggregation for cluster-based wireless sensor networkrdquoHuman-Centric Computing and Information Sciences vol 3 article 132013
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
International Journal of Distributed Sensor Networks 3
from the main partThe last part is a program for monitoringand generating DB
The composition of this paper is as follows Section 2is about a sensor module for electronic acupunctureand Section 3 is about intelligent pulse diagnosis algo-rithm Section 4 deals with implementation of the electronicacupuncture system Finally the conclusion is made inSection 5
2 Sensor Module for Electronic Acupuncture
We used several sensor modules to obtain a patientrsquos diagno-sis signals These sensor modules consist of 5 parts and theydetect and analyze the abnormal signals from human body
Figure 2 shows the sensor modules for electronicacupuncture system The measured signals from the eachsensor of modules are transferred to main the part
(1) Pulsimeter module It measures pulse rate It mea-sures the data from the finger connected to the fingersensor
(2) EGC module It measures electrocardiogram(3) SPO2 module It measures oxygen saturation of
blood(4) Skin conduction module It measures conductivity of
palmar skin(5) Body temperature module It measures temperature
of human body
3 Intelligent Pulse Diagnosis Algorithm
The intelligent pulse diagnosis system is composed of threeparts The first part is composed of the sensor to detect theconductance which is appropriate for injured part of humanbody and reference signal generator to adjust the signalgenerated from the patients The second part is composed ofDSP (Digital Signal Processor) board in which the signals aremeasured and classified using fuzzy algorithm The last partis composed of a computer system that displays the signalfrom DSP board to the monitor and analysis software todiagnose the patients Figure 3 shows the whole diagram ofphysical signal data network for electronic acupuncture Thealgorithm consists of 3 parts First step is sensing methodsthe second step is indexing methods and the third step isclassification methods
Pulse is beat-wave pattern of chest wall and great arteriesaccording to heartbeat The main purpose of pulse is toobserve cardiomotility and blood movement Recently studyusing physical characteristics shows that pulse wave patterncan change depending on condition of blood vessels andblood circulation The pulse wave pattern can be obtainedby second differentiation of digital plethysmogram usingphysical specific status such as uncertain inflection pointsIn this paper we classified a patientrsquos physical condition intothree categories as dangerous ordinary and normal condi-tion adapting pulse diagnosis algorithm using accelerationpulse wave pattern [9]
Fuzzy rules are generally presented with IF-THEN for-mat Fuzzy inference is procedures that infer new relationsor facts from the given rules and max-min reference is used
Input 119909 is 1198601015840 AND 119910 is 1198611015840
1198771 IF 119909 is 1198601 AND 119910 is 1198611 THEN 119911 is 1198621OR 1198772 IF 119909 is 1198602 AND 119910 is 1198612 THEN 119911 is 1198622
OR 119877119899 IF 119909 is 119860119899 AND 119910 is 119861119899 THEN 119911 is 119862119899Conclusion 119911 is 119862
Combination Function of Trust Value 1 and 2 type of fuzzycreation rule reduced from type of 5 and 6 can come to thesamenode and conclusion through different inference path toinfer fuzzy In this node the same conclusion reached two ofmore different trust value In this case combination functionof trust value is used to recalculate trust value of conclusion[2 8]
120573
119888= 120573comb (120573119888 120573
old119888) = max (120573
119888 120573
old119888) (1)
Here 120573old119888
is trust value of the conclusion reached throughinference path already 120573
119888is trust value of other conclusion
reached through another inference path If the 4 patientsrsquo (ab c d) illness condition is end-stage the value is displayed as08ndash10 shown in the left in case of the middle stage the valueis 04ndash07 and in case of the first stage the value is displayedas 01ndash03 The value in the middle shows patientrsquos physicalcondition For example if the patientrsquos height is 150 cm andweight is lower than 45 kg the value is displayed as 01ndash03
When the patientrsquos height is between 151 and 170 cm andthe weight is between 46 kg and 70 kg the value is displayedas 04ndash07 and when the height is 171 cmndash200 cm and weightis 71 kgndash130 kg the value is displayed as 08ndash10 In Figure 3the process to calculate fuzzy correction factor according topatientrsquos physical condition is shown
4 Implementation of the ElectronicAcupuncture System
Electronic acupuncture system with built in multi pad whichcan find out the condition of the patients automatically andtreat the patients simultaneously The system includes thefunction that can treat the patients with acupuncture andadjust voltage current frequency oscillation automaticallyaccording to their physical conditions To perform the func-tion the system senses and treats acupuncture simultane-ously and requires logical and statistical data processingtechnique using fuzzy and exact analysis Installing the 5round pads underneath the palm we can change the signaland then adaptive acupuncture treatment can be given
At this point measurement of the signal uses the wirelesstype instead of cable type Because the wireless type hasadvantage of convenience to get acupuncture reduction ofnoise by using cable connected to a computer system andprevention of electric shock depending on abrupt high-tension electricity [10 11]
4 International Journal of Distributed Sensor Networks
Pulse sensor
Blood pressure and sugar sensor
ECG sensor
Hmote 2420
Infrared temperature
(a) Sensor module parts considering patientrsquos physical conditions
Bloodpressure
Bloodpressure
sensor
REF
PGAAMP AD
CC2430
USB to serial
BAT and DCDC
15
PGAAMP CC2430
USB to serial
BAT and DCDC
13
EGC3
Notchfilter AD
CC2430
USB to serial
BAT and DCDC
EGC2
EGC1
11
Photodiode
AMPLED
AD
DA
PGAAMP PIC18F85
USB to serial
BAT and DCDC
1
2
30
AD
MOSFET
TRarray
TFTLCD
UART
SD slop
DCDC
SSPV210(cortex-A8)
SDRAM
Nand flash
CPLDdecoder
AudioALC5622USB host
20
ZigBee
Ethernet
WiFi
Bluetooth 20
20
16bit
24bit24bit
10M
512MB
256MB
2G
(b) Block diagram of Sensor modules
Figure 2 Sensor modules for electronic acupuncture system
In order to treat acupuncture it is important not only toget information from the human body but also to learn agessexes height and weight of the patients To do this controlvariables using fuzzy algorithm are made before treatment ofacupuncture
Figure 4 shows Circuit of the acupuncture signal Thepart of sensing pad and contact point of the fingertipmade of stripe array type to distribute contact point areaevenly after being plated with gold to reduce electric resis-tance
International Journal of Distributed Sensor Networks 5
RF channel 11Group ID
Hmoto2420 sender
Hmoto2420 sender
Hmoto2420 sender
Hmoto2420 senderHmoto2420 sender
Hmoto2420 receiver
Hmoto2420 receiver
Hmoto2420 receiver
Hmoto2420 receiverHmoto2420 receiver
0 times 05
RF channel 11Group ID 0 times 01 RF channel 11
Group ID 0 times 03
RF channel 12Group ID 0 times 01
RF channel 13Group ID 0 times 01
2405Mhz2410Mhz
2415Mhz
Figure 3 Whole diagram of physical signal data network for electronic acupuncture
PWM-2
TX
B_DIR-2
A_DIR-2B_DIR-1
A_DIR-1
D_DIR-2D_DIR-1C_DIR-2C_DIR-1
RX
A_DIR-1A_DIR-2PWM-1
LOAD
PWM-1
Load
C11104
C15104
C16 C17104
U3MAX232
1381110
134526
129147
1615
R1INR2INT1INT2IN
C+
C2+
V+
R1OUTR2OUTT1OUTT2OUT
VCC
GN
D
+
C4
+
C8
+
C5
+C10
R1220
Q1C1011
23
R8
R5 R7
R3
R6
+
U52
36
81
C13104
C18104
C12104
C14104
LS1Buzzer
+
+C3
U1AT89C2051
1
10
1213141516171819
20
23678911
54
RSTVPP
GN
D
P10AIN0P11AIN1
P12P13P14P15P16P17
P30RXDP31TXDP32INTOP33INT1P34T0P35T1P37
XTAL1XTAL2
R4
D1 1N4007
C718P(CH) +
C9
R2
C618P(CH)
C2104
X-TAL1
U232
1
VINVOUT
AD
J
C1 104
U4
L6203
4
5
3
8
1
6
2
9
711
10
+VIN
+BOOST
+CURLIM
+SENSE
REF
LIM
DIM
D2
1N4148
GND
Output module-CH1
C1minus
C2minus
Vminus
Data A
Data B
10uf25V
10uf25V
10uf25V
10uf25V
10uf25V
+5V
+5V
+5V
+5V
+5V
110592m
82K
minus
minus
1 uF16 V
22uF16V
minusVINminusBOOST
minusCURLIM
minusVOUT
1K
1K
2K
10K 20K
20K
Output CH1
Output CH1
VCC
VCC
VCC
Figure 4 Circuit of the acupuncture signal
In this paper we designed the optimal algorithm whichcould judge the remote medical diagnosis using fuzzy logicand fuzzy inference rules and we simulated the process tocalculate the optimal acupuncture time of the body conditionof patients We produced the wireless communication partto transmit condition of patientsrsquo pulse skin conductanceand oxygen saturation data to userrsquos terminal or remotemedical terminal and to receive the control signal fromuserrsquosterminal or remote medical terminal
To do this we made the sensing pad the circuit of AMPand acupuncture signal wireless communicationmodule and
charging circuit for storage battery And also we proposed thesoftware including algorithm of analysis and control usingfuzzy technique Existing acupuncture system using DSPhas a complex structure uses up a lot of electricity and itrsquosbig and expensive But the adaptive wireless acupuncturesystem proposed in this paper is simple inexpensive andsafe Figure 5 shows simulation of the glove type electronicacupuncture
To implement wireless system we used the way of RFdata modem for wireless communication using NarrowbandFSK The feature of this way is robust to noise and it can
6 International Journal of Distributed Sensor Networks
Figure 5 Simulation of the glove type electronic acupuncture
Figure 6 Data transmitter and receiver using RF communication
transmit data easily by simple communication protocol Andthis system is adapt to designmulti type data communicationsystem and can be designed by low power one 3V batteryin case of short distance We considered not only resistancemeasurement but capacitive component to reduce errordepending on several conditions of human body To do thiswe applied the pulse wave DC 50Vsim200V 500 uAsim1500 uAintermittent stimulation of 5Hzsim5KHz to the main pad andfingertip andmeasured the voltage peak and phase frequency[12 13]
We used 470MHz band frequency and designed thesystem to change 21 physical frequency And logical addressof a channel corresponding to each adaptive acupuncture wasassigned using polling technique and then calledThe systemsupports half duplex communicationThis way is suitable forthe system because the system requires low data and uses rel-atively low speed communicationThe output power of wire-less signal using button type battery is 1mW and it is adequateto transmit data without noise The speed of transmissionis 1200sim9600 bps and wireless encoding uses a way of Bi-phase Manchester code Communication between notebookcomputer and wireless modem uses RS232C Figure 6 showsthe data transmitter and receiver using RF communicationFor remote medical treatment the transmitter acquires data
Figure 7 Transmitreceive system for ubiquitous network
Figure 8 Analysis of electro stimulation to fingertips
Figure 9 Output of electronic acupuncture needle time simulationusing FIS matlab
from 4 sensors and then transmit the data to receiver usingRF communication
In Figure 7 the system consists of transmit andreceive system parts for ubiquitous network It is madeof MSP240CPU and CC2420 RF chip Figure 8 showsanalysis of electro stimulation to fingertips using padsTo obtain signal we send a reference signal to palm andthen decide body condition of patients on the basis of dataobtained from pre-investigation using sensing pads andMCU attached to fingertips As soon as signal processingis completed electric stimulation signal generated by fuzzyalgorithm is transmitted to sensing pads
Table 1 explains fuzzy inference of a variety of patientswith the same disease according to varying blood pressurecondition Heart rate condition and vascular aging condi-tion In other words Table 1 clearly shows that the systemcalculate varying time of acupuncture for different patientsphysical conditions
Figure 9 shows the Output of electronic acupunctureneedle time simulation using Fuzzy Inference SystemMatlabIt explains how the system calculates the output condition
International Journal of Distributed Sensor Networks 7
Table 1 Electronic acupuncture needle time simulation
Patient biometric information Optimal acupuncture needle timeInput data (minutes)
Blood pressure condition Heart rate condition Vascular aging condition Conventional IntelligenceMedium Medium Small 10 12Big Big Big 10 06Big Big Medium 10 08Medium Medium Medium 10 11Medium Big Big 10 07Medium Medium Small 10 10Small Big Big 10 07Small Medium Big 10 06Small Small Small 10 05
of the time for acupuncture from the input data of the 3conditions of patient physical conditions
5 Conclusion
In this paper we implemented intelligent electronic acupunc-ture system using sensor modules We used the sensormodules to obtain a patientrsquos diagnosis signals These sensormodules consist of 5 parts These sensor modules detect andanalyze the abnormal signals from human bodyWe analyzedthe signals to make instructions for the treatment And thenwedesigned the sensing pads for electronic acupuncture Andwe also developed adaptive wireless acupuncture system toadjust strength and time of acupuncture and several acupunc-ture points of patients by using fuzzy technology We madethe sensing pads the circuit of AMP and acupuncture signalWe implemented efficient electronic acupuncture system toget acupuncture easily using intelligent diagnosis systemThe intelligent acupuncture system proposed in this paperis simple inexpensive and safe compared with conventionalacupuncture systems
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITSWCreative research program supervised by the NIPA (NationalIT Industry Promotion Agency)rdquo (NIPA-2013-H0502-13-1112)
References
[1] Y S Hong H K Kim and B K Kim ldquoImplementation of adap-tive electronic acupuncture system using intelligent diagnosissystemrdquo International Journal of Control and Automation vol5 no 3 pp 141ndashl52 2012
[2] H K Baruah ldquoThe theory of fuzzy sets beliefs and realitiesrdquoInternational Journal of Energy Information and Communica-tions vol 2 no 2 pp 1ndash22 2011
[3] J Jeong ldquoThe development of web-based decision tree programfor the analysis of clinical information ideas constitutionrdquoKorea Institute of Oriental Medicine vol 12 pp 81ndash87 2008
[4] Y J Lee J Lee H J Lee H H Yoo E J Choi and J Y KimldquoStudy on the characteristics of blood vessel pulse area usingultrasonicrdquo Korea Institute of Oriental Medicine Researches vol13 no 3 pp 111ndash119 2007
[5] P A Shaltis A T Reisner and H H Asada ldquoCuffless bloodpressure monitoring using hydrostatic pressure changesrdquo IEEETransactions on Biomedical Engineering vol 55 pp 1775ndash17772008
[6] National College of Oriental MedicineDiagnostics Saint Func-tionality of Medicine St Functional Medicine 2008 GunjaPublisher 2007
[7] Department of Medical Sciences College of Oriental MedicineKyung Hee University ldquoMedical practice materialsrdquo 2007
[8] O P Verma and S Singh ldquoA fuzzy impulse noise filter based onboundary discriminative noise detectionrdquo Journal of Informa-tion Processing System vol 9 no 1 2013
[9] S-S Lee M-C An and S-H Ahn ldquoA new measurementmethod of a radial pulse wave usingmultiple hall array devicesrdquoJournal of Magnetics vol 14 no 3 pp 132ndash136 2009
[10] S Haykin Modem Wireless Communication Prentice-Hall2003
[11] A Swami andH YaWireless Sensor Networks Signal Processingand Communications John Wiley amp Sons 2007
[12] J K-Y Ng ldquoUbiquitous healthcare healthcare systems andapplications enabled by mobile and wirelessrdquo Journal of Con-vergence vol 3 no 2 2012
[13] A Sinha and D K Lobiyal ldquoPerformance evaluation of dataaggregation for cluster-based wireless sensor networkrdquoHuman-Centric Computing and Information Sciences vol 3 article 132013
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
4 International Journal of Distributed Sensor Networks
Pulse sensor
Blood pressure and sugar sensor
ECG sensor
Hmote 2420
Infrared temperature
(a) Sensor module parts considering patientrsquos physical conditions
Bloodpressure
Bloodpressure
sensor
REF
PGAAMP AD
CC2430
USB to serial
BAT and DCDC
15
PGAAMP CC2430
USB to serial
BAT and DCDC
13
EGC3
Notchfilter AD
CC2430
USB to serial
BAT and DCDC
EGC2
EGC1
11
Photodiode
AMPLED
AD
DA
PGAAMP PIC18F85
USB to serial
BAT and DCDC
1
2
30
AD
MOSFET
TRarray
TFTLCD
UART
SD slop
DCDC
SSPV210(cortex-A8)
SDRAM
Nand flash
CPLDdecoder
AudioALC5622USB host
20
ZigBee
Ethernet
WiFi
Bluetooth 20
20
16bit
24bit24bit
10M
512MB
256MB
2G
(b) Block diagram of Sensor modules
Figure 2 Sensor modules for electronic acupuncture system
In order to treat acupuncture it is important not only toget information from the human body but also to learn agessexes height and weight of the patients To do this controlvariables using fuzzy algorithm are made before treatment ofacupuncture
Figure 4 shows Circuit of the acupuncture signal Thepart of sensing pad and contact point of the fingertipmade of stripe array type to distribute contact point areaevenly after being plated with gold to reduce electric resis-tance
International Journal of Distributed Sensor Networks 5
RF channel 11Group ID
Hmoto2420 sender
Hmoto2420 sender
Hmoto2420 sender
Hmoto2420 senderHmoto2420 sender
Hmoto2420 receiver
Hmoto2420 receiver
Hmoto2420 receiver
Hmoto2420 receiverHmoto2420 receiver
0 times 05
RF channel 11Group ID 0 times 01 RF channel 11
Group ID 0 times 03
RF channel 12Group ID 0 times 01
RF channel 13Group ID 0 times 01
2405Mhz2410Mhz
2415Mhz
Figure 3 Whole diagram of physical signal data network for electronic acupuncture
PWM-2
TX
B_DIR-2
A_DIR-2B_DIR-1
A_DIR-1
D_DIR-2D_DIR-1C_DIR-2C_DIR-1
RX
A_DIR-1A_DIR-2PWM-1
LOAD
PWM-1
Load
C11104
C15104
C16 C17104
U3MAX232
1381110
134526
129147
1615
R1INR2INT1INT2IN
C+
C2+
V+
R1OUTR2OUTT1OUTT2OUT
VCC
GN
D
+
C4
+
C8
+
C5
+C10
R1220
Q1C1011
23
R8
R5 R7
R3
R6
+
U52
36
81
C13104
C18104
C12104
C14104
LS1Buzzer
+
+C3
U1AT89C2051
1
10
1213141516171819
20
23678911
54
RSTVPP
GN
D
P10AIN0P11AIN1
P12P13P14P15P16P17
P30RXDP31TXDP32INTOP33INT1P34T0P35T1P37
XTAL1XTAL2
R4
D1 1N4007
C718P(CH) +
C9
R2
C618P(CH)
C2104
X-TAL1
U232
1
VINVOUT
AD
J
C1 104
U4
L6203
4
5
3
8
1
6
2
9
711
10
+VIN
+BOOST
+CURLIM
+SENSE
REF
LIM
DIM
D2
1N4148
GND
Output module-CH1
C1minus
C2minus
Vminus
Data A
Data B
10uf25V
10uf25V
10uf25V
10uf25V
10uf25V
+5V
+5V
+5V
+5V
+5V
110592m
82K
minus
minus
1 uF16 V
22uF16V
minusVINminusBOOST
minusCURLIM
minusVOUT
1K
1K
2K
10K 20K
20K
Output CH1
Output CH1
VCC
VCC
VCC
Figure 4 Circuit of the acupuncture signal
In this paper we designed the optimal algorithm whichcould judge the remote medical diagnosis using fuzzy logicand fuzzy inference rules and we simulated the process tocalculate the optimal acupuncture time of the body conditionof patients We produced the wireless communication partto transmit condition of patientsrsquo pulse skin conductanceand oxygen saturation data to userrsquos terminal or remotemedical terminal and to receive the control signal fromuserrsquosterminal or remote medical terminal
To do this we made the sensing pad the circuit of AMPand acupuncture signal wireless communicationmodule and
charging circuit for storage battery And also we proposed thesoftware including algorithm of analysis and control usingfuzzy technique Existing acupuncture system using DSPhas a complex structure uses up a lot of electricity and itrsquosbig and expensive But the adaptive wireless acupuncturesystem proposed in this paper is simple inexpensive andsafe Figure 5 shows simulation of the glove type electronicacupuncture
To implement wireless system we used the way of RFdata modem for wireless communication using NarrowbandFSK The feature of this way is robust to noise and it can
6 International Journal of Distributed Sensor Networks
Figure 5 Simulation of the glove type electronic acupuncture
Figure 6 Data transmitter and receiver using RF communication
transmit data easily by simple communication protocol Andthis system is adapt to designmulti type data communicationsystem and can be designed by low power one 3V batteryin case of short distance We considered not only resistancemeasurement but capacitive component to reduce errordepending on several conditions of human body To do thiswe applied the pulse wave DC 50Vsim200V 500 uAsim1500 uAintermittent stimulation of 5Hzsim5KHz to the main pad andfingertip andmeasured the voltage peak and phase frequency[12 13]
We used 470MHz band frequency and designed thesystem to change 21 physical frequency And logical addressof a channel corresponding to each adaptive acupuncture wasassigned using polling technique and then calledThe systemsupports half duplex communicationThis way is suitable forthe system because the system requires low data and uses rel-atively low speed communicationThe output power of wire-less signal using button type battery is 1mW and it is adequateto transmit data without noise The speed of transmissionis 1200sim9600 bps and wireless encoding uses a way of Bi-phase Manchester code Communication between notebookcomputer and wireless modem uses RS232C Figure 6 showsthe data transmitter and receiver using RF communicationFor remote medical treatment the transmitter acquires data
Figure 7 Transmitreceive system for ubiquitous network
Figure 8 Analysis of electro stimulation to fingertips
Figure 9 Output of electronic acupuncture needle time simulationusing FIS matlab
from 4 sensors and then transmit the data to receiver usingRF communication
In Figure 7 the system consists of transmit andreceive system parts for ubiquitous network It is madeof MSP240CPU and CC2420 RF chip Figure 8 showsanalysis of electro stimulation to fingertips using padsTo obtain signal we send a reference signal to palm andthen decide body condition of patients on the basis of dataobtained from pre-investigation using sensing pads andMCU attached to fingertips As soon as signal processingis completed electric stimulation signal generated by fuzzyalgorithm is transmitted to sensing pads
Table 1 explains fuzzy inference of a variety of patientswith the same disease according to varying blood pressurecondition Heart rate condition and vascular aging condi-tion In other words Table 1 clearly shows that the systemcalculate varying time of acupuncture for different patientsphysical conditions
Figure 9 shows the Output of electronic acupunctureneedle time simulation using Fuzzy Inference SystemMatlabIt explains how the system calculates the output condition
International Journal of Distributed Sensor Networks 7
Table 1 Electronic acupuncture needle time simulation
Patient biometric information Optimal acupuncture needle timeInput data (minutes)
Blood pressure condition Heart rate condition Vascular aging condition Conventional IntelligenceMedium Medium Small 10 12Big Big Big 10 06Big Big Medium 10 08Medium Medium Medium 10 11Medium Big Big 10 07Medium Medium Small 10 10Small Big Big 10 07Small Medium Big 10 06Small Small Small 10 05
of the time for acupuncture from the input data of the 3conditions of patient physical conditions
5 Conclusion
In this paper we implemented intelligent electronic acupunc-ture system using sensor modules We used the sensormodules to obtain a patientrsquos diagnosis signals These sensormodules consist of 5 parts These sensor modules detect andanalyze the abnormal signals from human bodyWe analyzedthe signals to make instructions for the treatment And thenwedesigned the sensing pads for electronic acupuncture Andwe also developed adaptive wireless acupuncture system toadjust strength and time of acupuncture and several acupunc-ture points of patients by using fuzzy technology We madethe sensing pads the circuit of AMP and acupuncture signalWe implemented efficient electronic acupuncture system toget acupuncture easily using intelligent diagnosis systemThe intelligent acupuncture system proposed in this paperis simple inexpensive and safe compared with conventionalacupuncture systems
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITSWCreative research program supervised by the NIPA (NationalIT Industry Promotion Agency)rdquo (NIPA-2013-H0502-13-1112)
References
[1] Y S Hong H K Kim and B K Kim ldquoImplementation of adap-tive electronic acupuncture system using intelligent diagnosissystemrdquo International Journal of Control and Automation vol5 no 3 pp 141ndashl52 2012
[2] H K Baruah ldquoThe theory of fuzzy sets beliefs and realitiesrdquoInternational Journal of Energy Information and Communica-tions vol 2 no 2 pp 1ndash22 2011
[3] J Jeong ldquoThe development of web-based decision tree programfor the analysis of clinical information ideas constitutionrdquoKorea Institute of Oriental Medicine vol 12 pp 81ndash87 2008
[4] Y J Lee J Lee H J Lee H H Yoo E J Choi and J Y KimldquoStudy on the characteristics of blood vessel pulse area usingultrasonicrdquo Korea Institute of Oriental Medicine Researches vol13 no 3 pp 111ndash119 2007
[5] P A Shaltis A T Reisner and H H Asada ldquoCuffless bloodpressure monitoring using hydrostatic pressure changesrdquo IEEETransactions on Biomedical Engineering vol 55 pp 1775ndash17772008
[6] National College of Oriental MedicineDiagnostics Saint Func-tionality of Medicine St Functional Medicine 2008 GunjaPublisher 2007
[7] Department of Medical Sciences College of Oriental MedicineKyung Hee University ldquoMedical practice materialsrdquo 2007
[8] O P Verma and S Singh ldquoA fuzzy impulse noise filter based onboundary discriminative noise detectionrdquo Journal of Informa-tion Processing System vol 9 no 1 2013
[9] S-S Lee M-C An and S-H Ahn ldquoA new measurementmethod of a radial pulse wave usingmultiple hall array devicesrdquoJournal of Magnetics vol 14 no 3 pp 132ndash136 2009
[10] S Haykin Modem Wireless Communication Prentice-Hall2003
[11] A Swami andH YaWireless Sensor Networks Signal Processingand Communications John Wiley amp Sons 2007
[12] J K-Y Ng ldquoUbiquitous healthcare healthcare systems andapplications enabled by mobile and wirelessrdquo Journal of Con-vergence vol 3 no 2 2012
[13] A Sinha and D K Lobiyal ldquoPerformance evaluation of dataaggregation for cluster-based wireless sensor networkrdquoHuman-Centric Computing and Information Sciences vol 3 article 132013
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
International Journal of Distributed Sensor Networks 5
RF channel 11Group ID
Hmoto2420 sender
Hmoto2420 sender
Hmoto2420 sender
Hmoto2420 senderHmoto2420 sender
Hmoto2420 receiver
Hmoto2420 receiver
Hmoto2420 receiver
Hmoto2420 receiverHmoto2420 receiver
0 times 05
RF channel 11Group ID 0 times 01 RF channel 11
Group ID 0 times 03
RF channel 12Group ID 0 times 01
RF channel 13Group ID 0 times 01
2405Mhz2410Mhz
2415Mhz
Figure 3 Whole diagram of physical signal data network for electronic acupuncture
PWM-2
TX
B_DIR-2
A_DIR-2B_DIR-1
A_DIR-1
D_DIR-2D_DIR-1C_DIR-2C_DIR-1
RX
A_DIR-1A_DIR-2PWM-1
LOAD
PWM-1
Load
C11104
C15104
C16 C17104
U3MAX232
1381110
134526
129147
1615
R1INR2INT1INT2IN
C+
C2+
V+
R1OUTR2OUTT1OUTT2OUT
VCC
GN
D
+
C4
+
C8
+
C5
+C10
R1220
Q1C1011
23
R8
R5 R7
R3
R6
+
U52
36
81
C13104
C18104
C12104
C14104
LS1Buzzer
+
+C3
U1AT89C2051
1
10
1213141516171819
20
23678911
54
RSTVPP
GN
D
P10AIN0P11AIN1
P12P13P14P15P16P17
P30RXDP31TXDP32INTOP33INT1P34T0P35T1P37
XTAL1XTAL2
R4
D1 1N4007
C718P(CH) +
C9
R2
C618P(CH)
C2104
X-TAL1
U232
1
VINVOUT
AD
J
C1 104
U4
L6203
4
5
3
8
1
6
2
9
711
10
+VIN
+BOOST
+CURLIM
+SENSE
REF
LIM
DIM
D2
1N4148
GND
Output module-CH1
C1minus
C2minus
Vminus
Data A
Data B
10uf25V
10uf25V
10uf25V
10uf25V
10uf25V
+5V
+5V
+5V
+5V
+5V
110592m
82K
minus
minus
1 uF16 V
22uF16V
minusVINminusBOOST
minusCURLIM
minusVOUT
1K
1K
2K
10K 20K
20K
Output CH1
Output CH1
VCC
VCC
VCC
Figure 4 Circuit of the acupuncture signal
In this paper we designed the optimal algorithm whichcould judge the remote medical diagnosis using fuzzy logicand fuzzy inference rules and we simulated the process tocalculate the optimal acupuncture time of the body conditionof patients We produced the wireless communication partto transmit condition of patientsrsquo pulse skin conductanceand oxygen saturation data to userrsquos terminal or remotemedical terminal and to receive the control signal fromuserrsquosterminal or remote medical terminal
To do this we made the sensing pad the circuit of AMPand acupuncture signal wireless communicationmodule and
charging circuit for storage battery And also we proposed thesoftware including algorithm of analysis and control usingfuzzy technique Existing acupuncture system using DSPhas a complex structure uses up a lot of electricity and itrsquosbig and expensive But the adaptive wireless acupuncturesystem proposed in this paper is simple inexpensive andsafe Figure 5 shows simulation of the glove type electronicacupuncture
To implement wireless system we used the way of RFdata modem for wireless communication using NarrowbandFSK The feature of this way is robust to noise and it can
6 International Journal of Distributed Sensor Networks
Figure 5 Simulation of the glove type electronic acupuncture
Figure 6 Data transmitter and receiver using RF communication
transmit data easily by simple communication protocol Andthis system is adapt to designmulti type data communicationsystem and can be designed by low power one 3V batteryin case of short distance We considered not only resistancemeasurement but capacitive component to reduce errordepending on several conditions of human body To do thiswe applied the pulse wave DC 50Vsim200V 500 uAsim1500 uAintermittent stimulation of 5Hzsim5KHz to the main pad andfingertip andmeasured the voltage peak and phase frequency[12 13]
We used 470MHz band frequency and designed thesystem to change 21 physical frequency And logical addressof a channel corresponding to each adaptive acupuncture wasassigned using polling technique and then calledThe systemsupports half duplex communicationThis way is suitable forthe system because the system requires low data and uses rel-atively low speed communicationThe output power of wire-less signal using button type battery is 1mW and it is adequateto transmit data without noise The speed of transmissionis 1200sim9600 bps and wireless encoding uses a way of Bi-phase Manchester code Communication between notebookcomputer and wireless modem uses RS232C Figure 6 showsthe data transmitter and receiver using RF communicationFor remote medical treatment the transmitter acquires data
Figure 7 Transmitreceive system for ubiquitous network
Figure 8 Analysis of electro stimulation to fingertips
Figure 9 Output of electronic acupuncture needle time simulationusing FIS matlab
from 4 sensors and then transmit the data to receiver usingRF communication
In Figure 7 the system consists of transmit andreceive system parts for ubiquitous network It is madeof MSP240CPU and CC2420 RF chip Figure 8 showsanalysis of electro stimulation to fingertips using padsTo obtain signal we send a reference signal to palm andthen decide body condition of patients on the basis of dataobtained from pre-investigation using sensing pads andMCU attached to fingertips As soon as signal processingis completed electric stimulation signal generated by fuzzyalgorithm is transmitted to sensing pads
Table 1 explains fuzzy inference of a variety of patientswith the same disease according to varying blood pressurecondition Heart rate condition and vascular aging condi-tion In other words Table 1 clearly shows that the systemcalculate varying time of acupuncture for different patientsphysical conditions
Figure 9 shows the Output of electronic acupunctureneedle time simulation using Fuzzy Inference SystemMatlabIt explains how the system calculates the output condition
International Journal of Distributed Sensor Networks 7
Table 1 Electronic acupuncture needle time simulation
Patient biometric information Optimal acupuncture needle timeInput data (minutes)
Blood pressure condition Heart rate condition Vascular aging condition Conventional IntelligenceMedium Medium Small 10 12Big Big Big 10 06Big Big Medium 10 08Medium Medium Medium 10 11Medium Big Big 10 07Medium Medium Small 10 10Small Big Big 10 07Small Medium Big 10 06Small Small Small 10 05
of the time for acupuncture from the input data of the 3conditions of patient physical conditions
5 Conclusion
In this paper we implemented intelligent electronic acupunc-ture system using sensor modules We used the sensormodules to obtain a patientrsquos diagnosis signals These sensormodules consist of 5 parts These sensor modules detect andanalyze the abnormal signals from human bodyWe analyzedthe signals to make instructions for the treatment And thenwedesigned the sensing pads for electronic acupuncture Andwe also developed adaptive wireless acupuncture system toadjust strength and time of acupuncture and several acupunc-ture points of patients by using fuzzy technology We madethe sensing pads the circuit of AMP and acupuncture signalWe implemented efficient electronic acupuncture system toget acupuncture easily using intelligent diagnosis systemThe intelligent acupuncture system proposed in this paperis simple inexpensive and safe compared with conventionalacupuncture systems
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITSWCreative research program supervised by the NIPA (NationalIT Industry Promotion Agency)rdquo (NIPA-2013-H0502-13-1112)
References
[1] Y S Hong H K Kim and B K Kim ldquoImplementation of adap-tive electronic acupuncture system using intelligent diagnosissystemrdquo International Journal of Control and Automation vol5 no 3 pp 141ndashl52 2012
[2] H K Baruah ldquoThe theory of fuzzy sets beliefs and realitiesrdquoInternational Journal of Energy Information and Communica-tions vol 2 no 2 pp 1ndash22 2011
[3] J Jeong ldquoThe development of web-based decision tree programfor the analysis of clinical information ideas constitutionrdquoKorea Institute of Oriental Medicine vol 12 pp 81ndash87 2008
[4] Y J Lee J Lee H J Lee H H Yoo E J Choi and J Y KimldquoStudy on the characteristics of blood vessel pulse area usingultrasonicrdquo Korea Institute of Oriental Medicine Researches vol13 no 3 pp 111ndash119 2007
[5] P A Shaltis A T Reisner and H H Asada ldquoCuffless bloodpressure monitoring using hydrostatic pressure changesrdquo IEEETransactions on Biomedical Engineering vol 55 pp 1775ndash17772008
[6] National College of Oriental MedicineDiagnostics Saint Func-tionality of Medicine St Functional Medicine 2008 GunjaPublisher 2007
[7] Department of Medical Sciences College of Oriental MedicineKyung Hee University ldquoMedical practice materialsrdquo 2007
[8] O P Verma and S Singh ldquoA fuzzy impulse noise filter based onboundary discriminative noise detectionrdquo Journal of Informa-tion Processing System vol 9 no 1 2013
[9] S-S Lee M-C An and S-H Ahn ldquoA new measurementmethod of a radial pulse wave usingmultiple hall array devicesrdquoJournal of Magnetics vol 14 no 3 pp 132ndash136 2009
[10] S Haykin Modem Wireless Communication Prentice-Hall2003
[11] A Swami andH YaWireless Sensor Networks Signal Processingand Communications John Wiley amp Sons 2007
[12] J K-Y Ng ldquoUbiquitous healthcare healthcare systems andapplications enabled by mobile and wirelessrdquo Journal of Con-vergence vol 3 no 2 2012
[13] A Sinha and D K Lobiyal ldquoPerformance evaluation of dataaggregation for cluster-based wireless sensor networkrdquoHuman-Centric Computing and Information Sciences vol 3 article 132013
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
6 International Journal of Distributed Sensor Networks
Figure 5 Simulation of the glove type electronic acupuncture
Figure 6 Data transmitter and receiver using RF communication
transmit data easily by simple communication protocol Andthis system is adapt to designmulti type data communicationsystem and can be designed by low power one 3V batteryin case of short distance We considered not only resistancemeasurement but capacitive component to reduce errordepending on several conditions of human body To do thiswe applied the pulse wave DC 50Vsim200V 500 uAsim1500 uAintermittent stimulation of 5Hzsim5KHz to the main pad andfingertip andmeasured the voltage peak and phase frequency[12 13]
We used 470MHz band frequency and designed thesystem to change 21 physical frequency And logical addressof a channel corresponding to each adaptive acupuncture wasassigned using polling technique and then calledThe systemsupports half duplex communicationThis way is suitable forthe system because the system requires low data and uses rel-atively low speed communicationThe output power of wire-less signal using button type battery is 1mW and it is adequateto transmit data without noise The speed of transmissionis 1200sim9600 bps and wireless encoding uses a way of Bi-phase Manchester code Communication between notebookcomputer and wireless modem uses RS232C Figure 6 showsthe data transmitter and receiver using RF communicationFor remote medical treatment the transmitter acquires data
Figure 7 Transmitreceive system for ubiquitous network
Figure 8 Analysis of electro stimulation to fingertips
Figure 9 Output of electronic acupuncture needle time simulationusing FIS matlab
from 4 sensors and then transmit the data to receiver usingRF communication
In Figure 7 the system consists of transmit andreceive system parts for ubiquitous network It is madeof MSP240CPU and CC2420 RF chip Figure 8 showsanalysis of electro stimulation to fingertips using padsTo obtain signal we send a reference signal to palm andthen decide body condition of patients on the basis of dataobtained from pre-investigation using sensing pads andMCU attached to fingertips As soon as signal processingis completed electric stimulation signal generated by fuzzyalgorithm is transmitted to sensing pads
Table 1 explains fuzzy inference of a variety of patientswith the same disease according to varying blood pressurecondition Heart rate condition and vascular aging condi-tion In other words Table 1 clearly shows that the systemcalculate varying time of acupuncture for different patientsphysical conditions
Figure 9 shows the Output of electronic acupunctureneedle time simulation using Fuzzy Inference SystemMatlabIt explains how the system calculates the output condition
International Journal of Distributed Sensor Networks 7
Table 1 Electronic acupuncture needle time simulation
Patient biometric information Optimal acupuncture needle timeInput data (minutes)
Blood pressure condition Heart rate condition Vascular aging condition Conventional IntelligenceMedium Medium Small 10 12Big Big Big 10 06Big Big Medium 10 08Medium Medium Medium 10 11Medium Big Big 10 07Medium Medium Small 10 10Small Big Big 10 07Small Medium Big 10 06Small Small Small 10 05
of the time for acupuncture from the input data of the 3conditions of patient physical conditions
5 Conclusion
In this paper we implemented intelligent electronic acupunc-ture system using sensor modules We used the sensormodules to obtain a patientrsquos diagnosis signals These sensormodules consist of 5 parts These sensor modules detect andanalyze the abnormal signals from human bodyWe analyzedthe signals to make instructions for the treatment And thenwedesigned the sensing pads for electronic acupuncture Andwe also developed adaptive wireless acupuncture system toadjust strength and time of acupuncture and several acupunc-ture points of patients by using fuzzy technology We madethe sensing pads the circuit of AMP and acupuncture signalWe implemented efficient electronic acupuncture system toget acupuncture easily using intelligent diagnosis systemThe intelligent acupuncture system proposed in this paperis simple inexpensive and safe compared with conventionalacupuncture systems
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITSWCreative research program supervised by the NIPA (NationalIT Industry Promotion Agency)rdquo (NIPA-2013-H0502-13-1112)
References
[1] Y S Hong H K Kim and B K Kim ldquoImplementation of adap-tive electronic acupuncture system using intelligent diagnosissystemrdquo International Journal of Control and Automation vol5 no 3 pp 141ndashl52 2012
[2] H K Baruah ldquoThe theory of fuzzy sets beliefs and realitiesrdquoInternational Journal of Energy Information and Communica-tions vol 2 no 2 pp 1ndash22 2011
[3] J Jeong ldquoThe development of web-based decision tree programfor the analysis of clinical information ideas constitutionrdquoKorea Institute of Oriental Medicine vol 12 pp 81ndash87 2008
[4] Y J Lee J Lee H J Lee H H Yoo E J Choi and J Y KimldquoStudy on the characteristics of blood vessel pulse area usingultrasonicrdquo Korea Institute of Oriental Medicine Researches vol13 no 3 pp 111ndash119 2007
[5] P A Shaltis A T Reisner and H H Asada ldquoCuffless bloodpressure monitoring using hydrostatic pressure changesrdquo IEEETransactions on Biomedical Engineering vol 55 pp 1775ndash17772008
[6] National College of Oriental MedicineDiagnostics Saint Func-tionality of Medicine St Functional Medicine 2008 GunjaPublisher 2007
[7] Department of Medical Sciences College of Oriental MedicineKyung Hee University ldquoMedical practice materialsrdquo 2007
[8] O P Verma and S Singh ldquoA fuzzy impulse noise filter based onboundary discriminative noise detectionrdquo Journal of Informa-tion Processing System vol 9 no 1 2013
[9] S-S Lee M-C An and S-H Ahn ldquoA new measurementmethod of a radial pulse wave usingmultiple hall array devicesrdquoJournal of Magnetics vol 14 no 3 pp 132ndash136 2009
[10] S Haykin Modem Wireless Communication Prentice-Hall2003
[11] A Swami andH YaWireless Sensor Networks Signal Processingand Communications John Wiley amp Sons 2007
[12] J K-Y Ng ldquoUbiquitous healthcare healthcare systems andapplications enabled by mobile and wirelessrdquo Journal of Con-vergence vol 3 no 2 2012
[13] A Sinha and D K Lobiyal ldquoPerformance evaluation of dataaggregation for cluster-based wireless sensor networkrdquoHuman-Centric Computing and Information Sciences vol 3 article 132013
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
International Journal of Distributed Sensor Networks 7
Table 1 Electronic acupuncture needle time simulation
Patient biometric information Optimal acupuncture needle timeInput data (minutes)
Blood pressure condition Heart rate condition Vascular aging condition Conventional IntelligenceMedium Medium Small 10 12Big Big Big 10 06Big Big Medium 10 08Medium Medium Medium 10 11Medium Big Big 10 07Medium Medium Small 10 10Small Big Big 10 07Small Medium Big 10 06Small Small Small 10 05
of the time for acupuncture from the input data of the 3conditions of patient physical conditions
5 Conclusion
In this paper we implemented intelligent electronic acupunc-ture system using sensor modules We used the sensormodules to obtain a patientrsquos diagnosis signals These sensormodules consist of 5 parts These sensor modules detect andanalyze the abnormal signals from human bodyWe analyzedthe signals to make instructions for the treatment And thenwedesigned the sensing pads for electronic acupuncture Andwe also developed adaptive wireless acupuncture system toadjust strength and time of acupuncture and several acupunc-ture points of patients by using fuzzy technology We madethe sensing pads the circuit of AMP and acupuncture signalWe implemented efficient electronic acupuncture system toget acupuncture easily using intelligent diagnosis systemThe intelligent acupuncture system proposed in this paperis simple inexpensive and safe compared with conventionalacupuncture systems
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITSWCreative research program supervised by the NIPA (NationalIT Industry Promotion Agency)rdquo (NIPA-2013-H0502-13-1112)
References
[1] Y S Hong H K Kim and B K Kim ldquoImplementation of adap-tive electronic acupuncture system using intelligent diagnosissystemrdquo International Journal of Control and Automation vol5 no 3 pp 141ndashl52 2012
[2] H K Baruah ldquoThe theory of fuzzy sets beliefs and realitiesrdquoInternational Journal of Energy Information and Communica-tions vol 2 no 2 pp 1ndash22 2011
[3] J Jeong ldquoThe development of web-based decision tree programfor the analysis of clinical information ideas constitutionrdquoKorea Institute of Oriental Medicine vol 12 pp 81ndash87 2008
[4] Y J Lee J Lee H J Lee H H Yoo E J Choi and J Y KimldquoStudy on the characteristics of blood vessel pulse area usingultrasonicrdquo Korea Institute of Oriental Medicine Researches vol13 no 3 pp 111ndash119 2007
[5] P A Shaltis A T Reisner and H H Asada ldquoCuffless bloodpressure monitoring using hydrostatic pressure changesrdquo IEEETransactions on Biomedical Engineering vol 55 pp 1775ndash17772008
[6] National College of Oriental MedicineDiagnostics Saint Func-tionality of Medicine St Functional Medicine 2008 GunjaPublisher 2007
[7] Department of Medical Sciences College of Oriental MedicineKyung Hee University ldquoMedical practice materialsrdquo 2007
[8] O P Verma and S Singh ldquoA fuzzy impulse noise filter based onboundary discriminative noise detectionrdquo Journal of Informa-tion Processing System vol 9 no 1 2013
[9] S-S Lee M-C An and S-H Ahn ldquoA new measurementmethod of a radial pulse wave usingmultiple hall array devicesrdquoJournal of Magnetics vol 14 no 3 pp 132ndash136 2009
[10] S Haykin Modem Wireless Communication Prentice-Hall2003
[11] A Swami andH YaWireless Sensor Networks Signal Processingand Communications John Wiley amp Sons 2007
[12] J K-Y Ng ldquoUbiquitous healthcare healthcare systems andapplications enabled by mobile and wirelessrdquo Journal of Con-vergence vol 3 no 2 2012
[13] A Sinha and D K Lobiyal ldquoPerformance evaluation of dataaggregation for cluster-based wireless sensor networkrdquoHuman-Centric Computing and Information Sciences vol 3 article 132013
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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of