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Andreas Schrempf, Thomas Minarik
Upper Austria University of Applied Sciences
Medical Engineering
Linz, Austria
An interactive activity- monitoring device for use in home- rehabilitation
Upper Austria University of Applied Sciences
4th International Conference MRH | Pilsen June 30th 2011 Page 2
Upper Austria University of Applied Sciences
4th International Conference MRH | Pilsen June 30th 2011 Page 3
Faculty of Applied Health and Social Sciences
4th International Conference MRH | Pilsen June 30th 2011 Page 4
Education: Applied Health and Social Sciences
Research: - 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
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
4th International Conference MRH | Pilsen June 30th 2011 Page 5
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
4th International Conference MRH | Pilsen June 30th 2011 Page 6
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
4th International Conference MRH | Pilsen June 30th 2011 Page 7
Device DevelopmentNEON – Features
4th International Conference MRH | Pilsen June 30th 2011 Page 8
mini USB connector
LEDs
ANT module
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)
4th International Conference MRH | Pilsen June 30th 2011 Page 9
Device DevelopmentCommunication Concepts
4th International Conference MRH | Pilsen June 30th 2011 Page 10
Actilab
NEON
AccelerometryCOM moves during Walking
4th International Conference MRH | Pilsen June 30th 2011 Page 11
Center Of Mass (COM) moves during walking according to the different phases of the walking cycle
AccelerometryCOM moves during Walking
4th International Conference MRH | Pilsen June 30th 2011 Page 12
Frequency and amplitudes change depending
on walking speed
AccelerometryCOM moves during Walking
4th International Conference MRH | Pilsen June 30th 2011 Page 13
Putting an activity measurement device near to the COM allows to measure these movements in terms of the accelerations.
vertical acceleration:
AccelerometryPA - Energy Expenditure
4th International Conference MRH | Pilsen June 30th 2011 Page 14
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)
AccelerometryPA - Energy Expenditure
4th International Conference MRH | Pilsen June 30th 2011 Page 15
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 T
asphalt 1.0
gravel 1.4
soft underground 1.8
loose sand 2.1
deep snow (25cm) 3.3
AccelerometryPA - Energy Expenditure
4th International Conference MRH | Pilsen June 30th 2011 Page 16
• 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, …
AccelerometryPA - Energy Expenditure
4th International Conference MRH | Pilsen June 30th 2011 Page 17
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
AccelerometryPA - Energy Expenditure
4th International Conference MRH | Pilsen June 30th 2011 Page 18
Estimation of walking speed (based only on accelerations)
walking
running
AccelerometryPA - Energy Expenditure
4th International Conference MRH | Pilsen June 30th 2011 Page 19
heart-rate measurements
allows 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 [k
cal/m
in/k
g]
AccelerometryAccuracy Assessment
4th International Conference MRH | Pilsen June 30th 2011 Page 20
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)
AccelerometryAccuracy Assessment
4th International Conference MRH | Pilsen June 30th 2011 Page 21
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)
AccelerometrySensorfusion/Autom. Calibration
4th International Conference MRH | Pilsen June 30th 2011 Page 22
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