research-article

WR-Hand: Wearable Armband Can Track User's Hand

Authors:

Zhenjiang LiAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 5, Issue 3

Article No.: 118, Pages 1 - 27

https://doi.org/10.1145/3478112

Published: 14 September 2021 Publication History

Abstract

This paper presents WR-Hand, a wearable-based system tracking 3D hand pose of 14 hand skeleton points over time using Electromyography (EMG) and gyroscope sensor data from commercial armband. This system provides a significant leap in wearable sensing and enables new application potentials in medical care, human-computer interaction, etc. A challenge is the armband EMG sensors inevitably collect mixed EMG signals from multiple forearm muscles because of the fixed sensor positions on the device, while prior bio-medical models for hand pose tracking are built on isolated EMG signal inputs from isolated forearm spots for different muscles. In this paper, we leverage the recent success of neural networks to enhance the existing bio-medical model using the armband's EMG data and visualize our design to understand why our solution is effective. Moreover, we propose solutions to place the constructed hand pose reliably in a global coordinate system, and address two practical issues by providing a general plug-and-play version for new users without training and compensating for the position difference in how users wear their armbands. We implement a prototype using different commercial armbands, which is lightweight to execute on user's phone in real-time. Extensive evaluation shows the efficacy of the WR-Hand design.

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Index Terms

WR-Hand: Wearable Armband Can Track User's Hand
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction techniques
  2. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 5, Issue 3

Sept 2021

1443 pages

EISSN:2474-9567

DOI:10.1145/3486621

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Copyright © 2021 ACM.

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Published: 14 September 2021

Published in IMWUT Volume 5, Issue 3

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Cited By

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https://dl.acm.org/doi/10.1145/3659614
Zhang QLiu KWang D(2024)Sensing to Hear through MemoryProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36595988:2(1-31)Online publication date: 15-May-2024
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Wang SZhong LFu YChen LRen JZhang Y(2024)UFaceProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435468:1(1-27)Online publication date: 6-Mar-2024
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