TY - GEN
T1 - Adapting magnetic resonant coupling based relative positioning technology for wearable activitiy recogniton
AU - Pirkl, Gerald
AU - Stockinger, Karl
AU - Kunze, Kai
AU - Lukowicz, Paul
PY - 2008/12/1
Y1 - 2008/12/1
N2 - We demonstrate how modulated magnetic field technology that is well established in high precision, stationary motion tracking systems can be adapted to wearable activity recognition. To this end we describe the design and implementation of a cheap (components cost about 20 Euro for the transmitter and 15 Euro for the receiver), low power (17mA for the transmitter and 40mA for the receiver), and easily wearable (the main size constraint are the coils which are about 25mm3) system for tracking the relative position and orientation of body parts. We evaluate our system on two recognition tasks. On a set of 6 subtle nutrition related gestures it achieves 99.25% recognition rate compared to 94.1% for a XSense inertial device ( operated calibrated, euler angle mode). On the recognition of 8 Tai Chi moves it reaches 94 % compared to 86% of an accelerometer. Combining our sensor with the accelerometer leads to 100% correct recognition (as compared to 90% when combining the accelerometer with a gyro)
AB - We demonstrate how modulated magnetic field technology that is well established in high precision, stationary motion tracking systems can be adapted to wearable activity recognition. To this end we describe the design and implementation of a cheap (components cost about 20 Euro for the transmitter and 15 Euro for the receiver), low power (17mA for the transmitter and 40mA for the receiver), and easily wearable (the main size constraint are the coils which are about 25mm3) system for tracking the relative position and orientation of body parts. We evaluate our system on two recognition tasks. On a set of 6 subtle nutrition related gestures it achieves 99.25% recognition rate compared to 94.1% for a XSense inertial device ( operated calibrated, euler angle mode). On the recognition of 8 Tai Chi moves it reaches 94 % compared to 86% of an accelerometer. Combining our sensor with the accelerometer leads to 100% correct recognition (as compared to 90% when combining the accelerometer with a gyro)
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U2 - 10.1109/ISWC.2008.4911584
DO - 10.1109/ISWC.2008.4911584
M3 - Conference contribution
AN - SCOPUS:70349144534
SN - 9781424426379
T3 - Proceedings - International Symposium on Wearable Computers, ISWC
SP - 47
EP - 54
BT - Proceedings - 12th IEEE International Symposium on Wearable Computers, ISWC 2008
T2 - 12th IEEE International Symposium on Wearable Computers, ISWC 2008
Y2 - 28 September 2008 through 1 October 2008
ER -