TouchWave: Exploring mmWave-based Non-contact Fingertip-force Sensing in Activities of Daily Living

Yuliang Fu, Zhi Zhang, Rakshita Ranganath, Zhizhen Li, Yuchen Liu, Ning Sui, Huining Li, Chenhan Xu

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Keywords: fingertip force, non-contact sensing, digital biomarker, mmWave

TL;DR: This paper presents TouchWave, a non-contact sensing system designed to monitor fingertip forces, an important digital biomarker, from activities of daily living.

Abstract: Fingertip forces are important biomarkers for the detection and management of various conditions, including stroke and Parkinson’s disease. This paper presents TouchWave, a non-contact sensing system designed to monitor fingertip forces during activities of daily living (ADL). TouchWave leverages under-cabinet millimeter-wave (mmWave) sensors to capture both macroscopic hand movements and subtle biomechanical cues associated with fingertip force production. A novel signal processing scheme is developed to suppress noise while preserving force-related information in the mmWave signals. Additionally, a hybrid deep neural network model is proposed to estimate high-fidelity fingertip forces. A comprehensive evaluation involving 21 participants demonstrates the effectiveness of TouchWave in both controlled settings and ADL scenarios.

Track: 7. Contact-less solutions for human sensing

NominateReviewer: Yuliang Fu ([e-mail])

Submission Number: 77