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The current dominated wearable body motion sensor is IMU. This work presentedan alternative wearable motion-sensing approach: human body capacitance (HBC,also commonly defined as body-area electric field). While being less robust intracking the posture and trajectory, HBC has two properties that make it anattractive. First, the deployment of the sensing node on the being tracked bodypart is not a requirement for HBC sensing approach. Second, HBC is sensitive tothe body's interaction with its surroundings, including both touching and beingin the immediate proximity of people and objects. We first described thesensing principle for HBC, sensor architecture and implementation, and methodsfor evaluation. We then presented two case studies demonstrating the usefulnessof HBC as a complement/alternative to IMUs. First, we explored the exerciserecognition and repetition counting of seven machine-free leg-only exercisesand eleven general gym workouts with the signal source of HBC and IMU. The HBCsensing shows significant advantages over the IMU signals inclassification(0.89 vs 0.78 in F-score) and counting(0.982 vs 0.938 inaccuracy) of the leg-only exercises. For the general gym workouts, HBC onlyshows recognition improvement for certain workouts like adductor where legsalone complete the movement. And it also supplies better results over the IMUfor workouts counting(0.800 vs. 0.756 when wearing the sensors on the wrist).In the second case, we tried to recognize actions related to manipulatingobjects and physical collaboration between users by using a wrist-worn HBCsensing unit. We detected collaboration between the users with 0.69 F-scorewhen receiving data from a single user and 0.78 when receiving data from bothusers. The capacitive sensor can improve the recognition of collaborativeactivities with an F-score over a single wrist accelerometer approach by 16\%.

The Contribution of Human Body Capacitance/Body-Area Electric Field To Individual and Collaborative Activity Recognition