Muscle Condition Measurement System using Non-Invasive Electromyography Signal

Shih Hsiung Lee, Hsuan Chih Ku, Chia Hao Tsai, Chu Sing Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

When muscles contract or relax, they are usually clinically examined using an electromyography (EMG) machine. Currently, diagnosis requires professional medical personnel to use invasive needle electrodes to examine the muscles. During the examination, the physician will request the patient to perform relaxation and exertion movements, and the EMG machine is used to diagnose the patient's muscle condition in real-time. In addition, the inability of EMG machines to store real-time data makes it di cult to conduct subsequent tracking and analysis. Therefore, this paper designs a muscle condition measurement system that replaces electrode needles with adhesive patches, which is a non-invasive way to perform measurements. The advantages of this system allow patients to be more relaxed during the measurement of muscle signals and avoid misjudgments due to nervousness during measurement. Moreover, non-invasive devices can reduce the risk of infectious diseases. Additionally, this system provides signal recording and storage functions to facilitate subsequent data analysis. In the experimental part of this paper, the K-Means algorithm was adopted to initially find the baseline of muscles among the subjects for further research.

Original languageEnglish
Title of host publication2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages669-670
Number of pages2
ISBN (Electronic)9798350324174
DOIs
Publication statusPublished - 2023
Event2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Pingtung, Taiwan
Duration: 2023 Jul 172023 Jul 19

Publication series

Name2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings

Conference

Conference2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023
Country/TerritoryTaiwan
CityPingtung
Period23-07-1723-07-19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Human-Computer Interaction
  • Information Systems
  • Information Systems and Management
  • Electrical and Electronic Engineering
  • Media Technology
  • Instrumentation

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