跳到主要导航 跳到搜索 跳到主要内容

WMS: Wearables-Based Multisensor System for In-Home Fitness Guidance

  • Liwen Liang
  • , Yuxuan Duan
  • , Jincheng Che
  • , Chenyu Tang
  • , Wensi Dai
  • , Shuo Gao*
  • *此作品的通讯作者
  • Beihang University
  • University of Cambridge

科研成果: 期刊稿件文章同行评审

摘要

Human activity recognition (HAR) is now a powerful in-home fitness assistive technology. This article presents a wearables-based multisensor system (WMS), which not only supports conventional functionalities, such as motion evaluation based on multidimensional information about the user's body (movement speed, angle, muscle states, etc.), but also provides advanced services, including assessing training fatigue and providing real time, elastic, and professional training advice. The proposed WMS is experimentally validated by yielding 90.11% accuracy of motion evaluation with 36% and 23% improvement of fitness effect on bicep girth and muscular endurance, indicating its feasibility to prompt the development of HAR in the in-home fitness training domain.

源语言英语
页(从-至)17424-17435
页数12
期刊IEEE Internet of Things Journal
10
19
DOI
出版状态已出版 - 1 10月 2023

指纹

探究 'WMS: Wearables-Based Multisensor System for In-Home Fitness Guidance' 的科研主题。它们共同构成独一无二的指纹。

引用此