Abstract
Inertial measurement unit (IMU) is currently the dominant sensing modality in sensor-based wearable human activity recognition. In this work, we explored an alternative wearable motion-sensing approach: inferring motion information of various body parts from the human body capacitance (HBC). While being less robust in tracking the body motions, HBC has a property that makes it complementary to IMU: It does not require the sensor to be placed directly on the moving part of the body of which the motion needs to be tracked. To demonstrate the value of HBC, we performed exercise recognition and counting of seven machine-free leg-alone exercises. The HBC sensing shows significant advantages over the IMU signals in both classification(0.89 vs 0.78 in F-score) and counting.
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Bian, S., Yuan, S., Rey, V.F., Lukowicz, P. (2022). Using Human Body Capacitance Sensing to Monitor Leg Motion Dominated Activities with a Wrist Worn Device. In: Ahad, M.A.R., Inoue, S., Roggen, D., Fujinami, K. (eds) Sensor- and Video-Based Activity and Behavior Computing. Smart Innovation, Systems and Technologies, vol 291. Springer, Singapore. https://doi.org/10.1007/978-981-19-0361-8_5
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DOI: https://doi.org/10.1007/978-981-19-0361-8_5
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