TY - GEN
T1 - Dealing with sensor displacement in motion-based onbody activity recognition systems
AU - Kunze, Kai
AU - Lukowicz, Paul
PY - 2008
Y1 - 2008
N2 - We present a set of heuristics that significantly increase the robustness of motion sensor-based activity recognition with respect to sensor displacement. In this paper placement refers to the position within a single body part (e.g, lower arm). We show how, within certain limits and with modest quality degradation, motion sensorbased activity recognition can be implemented in a displacement tolerant way. We first describe the physical principles that lead to our heuristic. We then evaluate them first on a set of synthetic lower arm motions which are well suited to illustrate the strengths and limits of our approach, then on an extended modes of locomotion problem (sensors on the upper leg) and finally on a set of exercises performed on various gym machines (sensors placed on the lower arm). In this example our heuristic raises the displaced recognition rate from 24% for a displaced accelerometer, which had 96% recognition when not displaced, to 82%.
AB - We present a set of heuristics that significantly increase the robustness of motion sensor-based activity recognition with respect to sensor displacement. In this paper placement refers to the position within a single body part (e.g, lower arm). We show how, within certain limits and with modest quality degradation, motion sensorbased activity recognition can be implemented in a displacement tolerant way. We first describe the physical principles that lead to our heuristic. We then evaluate them first on a set of synthetic lower arm motions which are well suited to illustrate the strengths and limits of our approach, then on an extended modes of locomotion problem (sensors on the upper leg) and finally on a set of exercises performed on various gym machines (sensors placed on the lower arm). In this example our heuristic raises the displaced recognition rate from 24% for a displaced accelerometer, which had 96% recognition when not displaced, to 82%.
KW - Fitness exercises
KW - Motion sensors
KW - Opportunistic activity recognition
KW - Sensor displacement
UR - http://www.scopus.com/inward/record.url?scp=59249086539&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=59249086539&partnerID=8YFLogxK
U2 - 10.1145/1409635.1409639
DO - 10.1145/1409635.1409639
M3 - Conference contribution
AN - SCOPUS:59249086539
SN - 9781605581361
T3 - UbiComp 2008 - Proceedings of the 10th International Conference on Ubiquitous Computing
SP - 20
EP - 29
BT - UbiComp 2008 - Proceedings of the 10th International Conference on Ubiquitous Computing
T2 - 10th International Conference on Ubiquitous Computing, UbiComp 2008
Y2 - 21 September 2008 through 24 September 2008
ER -