Finger Tracking Using Wrist-Worn EMG Sensors

Jiani Cao, Yang Liu, Lixiang Han, Zhenjiang Li*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

2 Citations (Scopus)

Abstract

This paper introduces WETrak, a finger tracking system using wrist-worn electromyography (EMG) sensors. Recent finger tracking methods mainly employ EMGs on armbands. Compared to a range of contactless methods using cameras or wireless, they are not limited by high computational costs, privacy concerns, and mobility, while unlike other wearable-based approaches, they do not require the deployment of sensors on the user's hands. However, users need to wear an additional armband on their forearm each time solely for tracking purpose, which hinders the widespread adoption of finger tracking in practice. This paper investigates the feasibility of moving EMG sensors from the forearm to the wrist for finger tracking. WETrak inherits the advantages of existing EMG-based armband tracking while avoiding the limitation of requiring additional armbands, which brings a strong incentive for integrating EMG sensors into wrist-worn wearables in the future. As sensor placement varies, we find new challenges in determing good locations to place sensors to gather useful information to capture all finger movements and using low-quality signals to still ensure accurate tracking. In this paper, we introduce new, efficient solutions to these problems. We develop a prototype, and the results show that WETrak outperforms the state-of-the-art method and performs consistently well under various settings. © 2024 IEEE
Original languageEnglish
Pages (from-to)14099 - 14110
Number of pages13
JournalIEEE Transactions on Mobile Computing
Volume23
Issue number12
Online published6 Aug 2024
DOIs
Publication statusPublished - Dec 2024

Funding

This work is supported by the General Research Fund (GRF) grants from Research Grants Council of Hong Kong (Project No. CityU 11217420 and CityU 11213622), and the CityU Strategic Research Grant 7005658.

Research Keywords

  • EMG sensors
  • finger tracking
  • mobile sensing
  • muscle distribution

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