Collaborative Human Activity Recognition with Passive Inter-Body Electrostatic Field

TL;DR

This paper explores the use of passive inter-body electrostatic fields for wearable human activity recognition, evaluating its effectiveness alone and in combination with traditional sensors for collaborative activities.

Contribution

It introduces the first quantitative evaluation of inter-body electrostatic fields and demonstrates their potential as a complementary sensing modality for activity recognition.

Findings

Electrostatic field sensing alone shows less competitive recognition performance than accelerometers.

Fusion of electrostatic and accelerometer data improves collaborative activity recognition by 16%.

A new dataset with 16 hours of annotated collaborative activities was collected.

Abstract

The passive body-area electrostatic field has recently been aspiringly explored for wearable motion sensing, harnessing its two thrilling characteristics: full-body motion sensitivity and environmental sensitivity, which potentially empowers human activity recognition both independently and jointly from a single sensing front-end and theoretically brings significant competition against traditional inertial sensor that is incapable in environmental variations sensing. While most works focus on exploring the electrostatic field of a single body as the target, this work, for the first time, quantitatively evaluates the mutual effect of inter-body electrostatic fields and its contribution to collaborative activity recognition. A wearable electrostatic field sensing front-end and wrist-worn prototypes are built, and a sixteen-hour, manually annotated dataset is collected, involving an experiment of manipulating objects both independently and collaboratively. A regression model is finally used to recognize the collaborative activities among users. Despite the theoretical advantages of the body electrostatic field, the recognition of both single and collaborative activities shows unanticipated less-competitive recognition performance compared with the accelerometer. However, It is worth mentioning that this novel sensing modality improves the recognition F-score of user collaboration by 16\% in the fusion result of the two wearable motion sensing modalities, demonstrating the potential of bringing body electrostatic field as a complementary power-efficient signal for collaborative activity tracking using wearables.