andreas schrempf, thomas minarik upper austria university of applied sciences medical engineering
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Andreas Schrempf, Thomas Minarik Upper Austria University of Applied Sciences Medical Engineering Linz, Austria [email protected]. An interactive activity- monitoring device for use in home- rehabilitation . Upper Austria University of Applied Sciences. - PowerPoint PPT PresentationTRANSCRIPT
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Andreas Schrempf, Thomas MinarikUpper Austria University of Applied SciencesMedical Engineering
Linz, Austria
An interactive activity- monitoring device for use in home- rehabilitation
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Upper Austria University of Applied Sciences
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Upper Austria University of Applied Sciences
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Faculty of Applied Health and Social Sciences
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Education: Applied Health and Social SciencesResearch: - Medical Engineering
- Assisting Technologies and Processes for the Elderly
Campus Linz ...
Emergency HospitalLinz
Rehab. Amb.Linz
General HospitalLinz
Pediadric and Gynecological Clinic Linz
GKK-OOEHealth Ins. Comp.
HospitalDiakonissen
Neurological Clinic Wagner Jauregg Linz
Most of the medical partners are within a square km.
University of Applied SciencesCampus Linz
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Activity Measurement Application AreasApplication and Benefits :– preventive care
– measures taken to prevent diseases– motivation factor
– therapy evaluation – objective measures of the therapy
progress– Documentation– assessment
– therapy control – compare exercise measurement data
against golden reference– adjust intensity according progress, – provide feedback
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Device DevelopmentActilab – Features• developed in cooperation with g.tec medical engineering
– Device development – g.tec medical engineering– Algorithm development – FH-OOE
• Mobile system– duration, intensity, frequency of activity
• Intended to become a medical device• Triaxial accelerometer
– measuring range: ±18g– Resolution: ~ 6.25mg
• Barometric pressure sensor– Measurement range 30-120kPa– Resolution: ~10cm
• GSM module
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Device DevelopmentNEON – Features• developed in cooperation with spantec GmbH
• Triaxial accelerometer– measuring range: ±8g– Resolution: ~ 3.9mg
• Barometric pressure sensor – 30 kPa - 120 kPa measuring range– Resolution: 1.5 Pa ( ∼ 10cm at s.l.)
• GPS module– accuracy position: 5m CEP (Circular error probable)– accuracy velocity: 0.1m/s– update rate: 1Hz
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Device DevelopmentNEON – Features
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mini USB connector
LEDs
ANT module
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Device DevelopmentNEON – Features• Compatible with all ANT(+) devices
– e.g. Garmin HRM1G
• micro SD-card– 2 GB data memory
• UART connection to local PC
• ANT module– 2.4GHz wireless networking protocol designed
for wireless sensor networks– network (internet) connection possible (bridging)
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Device DevelopmentCommunication Concepts
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Actilab
NEON
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AccelerometryCOM moves during Walking
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Center Of Mass (COM) moves during walking according to the different phases of the walking cycle
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AccelerometryCOM moves during Walking
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Frequency and amplitudes change dependingon walking speed
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AccelerometryCOM moves during Walking
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Putting an activity measurement device near to the COM allows to measure these movements in terms of the accelerations.
vertical acceleration:
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AccelerometryPA - Energy Expenditure
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Total Energy Expenditure (TEE)
TEE = BMR + DIT + PA• BMR: basal metabolic rate BMR• DIT: diet induced thermogenesis• PA: physical activity
Physical activity level (according to WHO) (1.2 sitting, 1.8-1.9 walking)
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AccelerometryPA - Energy Expenditure
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Estimation ( modified Goldman equation)
• T: terrain factor• : overall efficiency• m: body mass• v: walking speed• a(v): total average acceleration,
depends on walking speed• dh/dt: change of elevation per time unit• g: gravity constant
condition Tasphalt 1.0gravel 1.4soft underground 1.8loose sand 2.1deep snow (25cm) 3.3
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AccelerometryPA - Energy Expenditure
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• estimation based on mean acceleration (indoor/outdoor)
• measured by GPS (outdoor)• measured by acceleration
sensors
• measured by barometric pressure sensor (indoor/outdoor)
• measured by GPS (outdoor)
• overall efficiency, depends on age, fitness level, gender, …
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AccelerometryPA - Energy Expenditure
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mean total body acceleration• High-pass filtering (offset,
artefacts)• rectifying (power)• Low-pass filtering (mean
acceleration)
• distinguishing between no activity, walking and running
• estimation of walking speed
a(t) LP | . | HP
walking
running
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AccelerometryPA - Energy Expenditure
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Estimation of walking speed (based only on accelerations)
walking
running
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AccelerometryPA - Energy Expenditure
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heart-rate measurementsallows to estimate the EE:• depends on age,• depends on fitness level,• depends on gender,• different for walking and
running,• hysteresis,• direct measurement of the
energy expenditure (allows to quantify the efficiency)
HR [bpm]
dE/d
t [kc
al/m
in/k
g]
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AccelerometryAccuracy Assessment
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altitude: GPS vs. pressure sensor• pressure sensor requires stable weather
conditions,• GPS accuracy limited, when low signal
quality• GPS may loose signal, does not work
indoor
forest (low GPS signal quality)
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AccelerometryAccuracy Assessment
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walking speed: GPS vs. barometric press. sensor• pressure sensor requires
stable weather conditions,• GPS may loose signal,
does not work indoor• --> sensor fusion
stairs down
altitude GPS (low signal quality)
round trip
stairs up, then down
altitude barometer
walking speedGPS
walking speed prediction byaccelerometer(problem: up and down)
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AccelerometrySensorfusion/Autom. Calibration
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Problems:• GPS signal only available
outdoor• GPS: altitude low accuracy,
especially for small altitude differences
• barometric height measurement only valid for short time or during stable weather conditions
• Speed prediction by accelerometer not accurate enough when going up or down
• Efficiency not constant varies between different subjects (depending on age, fitness level or pathology)V
Solutions:• Sensor fusion combining GPS
and barometric pressure sensor. Weighting of signal depends on signal quality and/or availability
• Individual calibration of speed prediction algorithm, during good GPS-signal quality
• Individual calibration of efficiency using heart-rate monitor