Using Human Body Capacitance Sensing to Monitor Leg Motion Dominated Activities with a Wrist Worn Device

Sizhen Bian, Siyu Yuan, Vitor Fortes Rey, Paul Lukowicz

In: Proceedings of the 3rd International Conference on Activity and Behavior Computing. International Conference on Activity and Behavior Computing (ABC-2021) October 22-23 Smart Innovation, Systems and Technologies Springer 2021.


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.

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence