Feature recognition in multiple CNNs using sEMG images from a prototype comfort test.

Journal: Computer methods and programs in biomedicine
Published Date: Oct 26, 2023

Abstract

OBJECTIVE: Deep learning-based CNN networks have recently been investigated to solve the problem of body posture recognition based on surface electromyographic signals (sEMG). Influenced by these studies, to develop a combined approach of sEMG and CNNs in the study of human-product interactions and the impact of body comfort, and to compare the advantages and disadvantages of various CNNs networks.

Authors

  • You-Lei Fu
    Department of Design, National Taiwan Normal University, Taipei 106, Taiwan; Fine Art and Design College, Quanzhou Normal University, Quanzhou 362000, China. Electronic address: 80868006t@ntnu.edu.tw.
  • Wu Song
    College of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, China. Electronic address: songwu@hqu.edu.cn.
  • Wanni Xu
    Department of Pathology, Xijing Hospital, Fourth Military Medical University, Changle West Road 127#, Xi'an City, 710032, People's Republic of China; Deng Road 97#, Xi'an City, 710077, People's Republic of China.
  • Jie Lin
    Department of Reproductive Medicine, Zigong Hospital of Women and Children Health Care, Zigong, China.
  • Xuchao Nian
    Xiamen NanYang University, Xiamen 361000, China.

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