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Related Experiment Video

Updated: May 14, 2026

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

Enhanced multi-site EMG-force estimation using contact pressure.

Javad Hashemi1, Evelyn Morin, Parvin Mousavi

  • 1Department of Electrical and Computer Engineering, School of Computing, Queen’s University, Kingston, ON K7L 3N6, Canada. javad.hashemi@queensu.ca

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|February 1, 2013
PubMed
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This study introduces a novel method combining surface electromyogram (SEMG) and contact pressure for improved muscle force estimation. Integrating these signals enhances SEMG-force models, leading to more accurate predictions of wrist force during isometric contractions.

Area of Science:

  • Biomedical Engineering
  • Neuroscience
  • Biomechanics

Background:

  • Surface electromyogram (SEMG) is widely used for muscle activity assessment.
  • Accurate SEMG-based force estimation remains challenging due to signal variability.
  • Integrating contact pressure offers a potential method to improve SEMG signal reliability.

Purpose of the Study:

  • To develop and validate a novel modification method for SEMG signals using integrated contact pressure.
  • To enhance the performance of SEMG-force models for more accurate muscle force estimation.
  • To investigate the correlation between modified SEMG signals and induced wrist force.

Main Methods:

  • A sensor patch integrating six SEMG and six contact pressure sensors was designed and fabricated.

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Last Updated: May 14, 2026

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

Force and Position Control in Humans - The Role of Augmented Feedback
06:31

Force and Position Control in Humans - The Role of Augmented Feedback

Published on: June 19, 2016

  • Multi-site SEMG signals from the biceps brachii were modified by simultaneously recorded pressure signals.
  • Isometric contractions were performed, and induced wrist force (FW) was measured.
  • Polynomial fitting was employed to establish mapping between SEMG and FW.

    • Main Results:

    • The modified SEMG signals, specifically the product of pressure and SEMG, showed significantly higher correlation with induced wrist force.
    • SEMG-force models trained with the modified signals demonstrated statistically superior performance in force estimation compared to models using non-modified SEMG.
    • Data collected from five subjects confirmed the effectiveness of the integrated sensing approach.

    Conclusions:

    • Integrating contact pressure with SEMG recordings provides a robust method for enhancing muscle force estimation.
    • The developed modification technique significantly improves the accuracy and reliability of SEMG-based biomechanical models.
    • This approach holds promise for advanced applications in prosthetics, rehabilitation, and human-computer interfaces.