april 3 rd, 2008. wireless autonomous transducer systems sywert h. brongersma
TRANSCRIPT
April 3rd, 2008
April 3rd, 2008
WIRELESS AUTONOMOUS TRANSDUCER SYSTEMS
Sywert H. Brongersma
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
3© Holst Centre
Holst Centre open innovation
Wireless Autonomous Transducer Solutions
IMEC
System-in-Foil Products and Production
TNO
Technology Integration
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4© Holst Centre
Medical & Lifestyle as an application driver
Wearability
Connectivity
Intelligence
Functionality
Autonomy
Implantability
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5© Holst Centre
Optimizing energy scavenging
Camel Fridge: medicine transportation
2mW 0.03mW/cm2
S10W
A10W
FrontEnd
20WDSP
20W
Radio20W
Micropower System - 100W
P20W
Thermal, Vibrational, RF, Light
NonElectrical
World
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6© Holst Centre
Physical sensing or actuating mechanismTransducer design & physics
Device physics inside nanowire,MEMS,…
Signal preconditioning: Amplification, buffering, actuator driving, …
Typically analog electronics
Interface between sensor and signal processing unitTypically ADC, DAC, or counter, pulse generator
Low-level signal processingSensor data calibration, data correction, compression
Transducer feedback and control loop
Algorithms for data interpretationPattern matching, sensor data fusion, classification
Data interpretationApplication software, diagnosis, …
Underlying technology to fabricate transducersMEMS, nanowire deposition, micro-optics, …
Application layer
Algorithmic layer
Processing layer
Interfacing layer
Signal conditioninglayer
Physical layer
Technology layer
Picture: P. Nair (Purdue Univ.)
An Integrated Approach is Key…
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7© Holst Centre
www.continuaalliance.org
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2002: Portable they say…
Progress in ambulatory EEG…
2008
ULP biopotential read-out ASIC
3D-SiP layer integration
Formfactor 300 1 cm3
Low power <10mW
Unither Nanomedical & Telemedical Technology
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[ MIT Technology Review ]
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Patient Number
Se
con
ds
Aft
er E
lect
rog
rap
hic
O
ns
et
Automatic Detections" "Patient/Caregiver Pushbutton"Feature
Extractor
FeatureExtractor
EEG Channel 1
EEG Channel 21
Support-Vector
Machine
EEG Channel 2 ClassificationTemporalConstraint
FeatureExtractor
X1,1
X1,2
X1,3
X1,4
X2,1
X2,2
X2,3
X2,4
X21,1
X21,2
X21,3
X21,4
… to enable automated epileptic seizure detection
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10© Holst Centre
Power Consumption of 8-Channel EEG
Micro0.81mW
Radio2.40mW
EEG0.30mW
Total power consumption: 3.51mW
256 Hz
8 channels
Further reduction towards 100 W
Radio technology
Local processing to reduce transmission
DSP w. > 500 MOPs/mW required
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In parallel: wireless ECG patch
Hybrid integrationElectronics integration on flex substrateTextile integration for stretchability
Flexible core partULP bio-potential read-out front endLow-power digital signal processing: TI MSP430 f1611Low-power radio link: Built on Nordic nRF24L01175mAh Li-ion battery
Band-aid integrationWire-free and easy to set-upFits any body shapes and electrode placement
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Towards automated arrhythmia detection
99.5499.5410010099.9099.9099.90Se(% )
7.903.98-1.18-1.416.4510.8312.06Me (samples)
22.9719.4813.214.4413.9622.6132.33Sd (samples)
3542354236233623319431943194# annotations
TendTpeakQRSendQRSonPendPpeakPonParameters
99.5499.5410010099.9099.9099.90Se(% )
7.903.98-1.18-1.416.4510.8312.06Me (samples)
22.9719.4813.214.4413.9622.6132.33Sd (samples)
3542354236233623319431943194# annotations
TendTpeakQRSendQRSonPendPpeakPonParameters
For 90 nm technology:
DSP Active power consumption 6mW + Duty cycle 1%
Average power consumption 60W
Unither Nanomedical & Telemedical Technology
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13© Holst Centre
And also: body temperature… on flex & SpO2 autonomously
Commercial SpO2 sensor integrated
with WATS sensor node
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Multi sensor node approach very powerful
ECG, respiration
EMG
EEG, EOG
SpO2
Temperature
Activity monitoring
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Multi-sensor body area network for complex health issues
Star network with 3 slaves2 channels EEG (F2/A1 and C2/A1)2 channels EOG1 channel EMG
TDMA MAC protocol
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Wireless Sleep Monitoring
Sleep apnea prevalence
Europe: 4% male population, 2% female population
USA: 10% population
Narcolepsy prevalence 1 in 1359
Dramatic socio-economic consequences
Current sleep monitoring systems
Expensive, non-natural environment
Wired systems: cumbersome, noisy, hinder mobility
Wireless sleep staging system
Pre-screening in home environment
Ambulatory and comfort
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Preliminary clinical evaluation
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18© Holst Centre
Monitoring emotions
psycho-physiological response to external stimuli
Emotional response
ANS
Homeostasis…
CNS
Control behaviorInfo processing
…
Vocal system
Speech…
Emotional response is one of many reasons for
changes in ANS, CNS and vocal system
Need for integration of multi-modalities
Need to isolate emotion response
Ultra-low-power wireless sensor network
as enabling technology
Test environment
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Application 1: Biofeedback and emotion control
ECG, Respiration
Temperature, GSR
Back muscle stiffness
Emotionclassification
FeedbackVisualAuditivePharmaceutical
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Application 2: monitoring acceptance of drug treatment
Hospital analysis
WB
AN
: U
LP U
WB
for
15.
14a
stan
dard
Net
wor
k (s
ecur
ity,
priv
acy,
rel
iabi
lity)
Continuous monitoring from home
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Feature 1
Fea
ture
2
First prototype of emotion monitor
Emotion
Cla
ssifi
er
ECG
GSR
Temp
Respiration
MeanMean 1st diff
MeanMean 1st diff
Mean
MeanMean 1st diff
Emotion
HR + filter
analysis
Filter
Filter
RR + filter
FFT
Cla
ssifi
er
ECG
GSR
Temp
Respiration
MeanMean 1st diff
MeanMean 1st diff
Mean
MeanMean 1st diff
Emotion
HR + filter
analysis
Filter
Filter
RR + filter
FFT
Fisher mapping:
Clustering of emosion
Error rate: ~40%
Interpretation• Error rate estimated using leave-one-out
cross-validation on a very reduced data
set• Risk of over-fitting
Check on new data set !
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Trend towards the future:
Truly Unobtrusive Monitoring Solutions
with ever increasing sensor functionality
On-board power scavengingLow power sensors & actuators
* Sweat, Saliva, Breath Lactate, Urea, Glucose, Oxygen, Acetone
* Polerized dipole moleculesNO2, CO, Ethanol, Amines
* Redox moleculesAmmonia, NO2, H2S, COx)
* Volatile organic compounds Benzene, Alkanes, Ethanol
read-out circuitry radio dsp