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Related Experiment Video

Updated: Dec 13, 2025

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Development of Soft sEMG Sensing Structures Using 3D-Printing Technologies.

Gerjan Wolterink1,2, Pedro Dias1, Remco G P Sanders1

  • 1Robotics And Mechatronics group (RAM), University of Twente, 7500 AE Enschede, The Netherlands.

Sensors (Basel, Switzerland)
|August 6, 2020
PubMed
Summary
This summary is machine-generated.

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3D-printed soft EMG sensors offer a personalized and cost-effective solution for muscle activity monitoring. These flexible sensors show performance comparable to traditional electrodes, enabling applications in prosthetics and gesture recognition.

Area of Science:

  • Biomedical Engineering
  • Materials Science
  • Wearable Technology

Background:

  • Surface electromyography (sEMG) is crucial for monitoring muscle activity.
  • Traditional sEMG electrodes often lack personalization and can be uncomfortable.
  • Advancements in 3D printing offer potential for customized and integrated biosensor solutions.

Purpose of the Study:

  • To develop and characterize flexible, 3D-printed surface electromyography (sEMG) sensing structures.
  • To evaluate the performance of these 3D-printed sensors against conventional electrodes.
  • To demonstrate the potential of 3D-printed sEMG sensors in practical applications like gesture recognition.

Main Methods:

  • Fabrication of flexible, carbon-black doped TPU-based sEMG sensors using a multi-material FDM 3D printer.
Keywords:
3D-printingEMGconductiveelectrodesflexiblesoftthermoplactic polyurethane (TPU)

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  • Direct 3D printing without post-processing.
  • Comparative analysis of 3D-printed sensors against Ag/AgCl gel electrodes.
  • Testing sensor capabilities in detecting varying levels of biceps brachii muscle activity.
  • Application of pattern recognition algorithms to analyze sEMG data from a 3D-printed electrode band for hand gesture recognition.

    • Main Results:

    • Successfully developed and characterized flexible, 3D-printed sEMG sensing structures.
    • No significant difference in EMG signal amplitude was observed between 3D-printed sensors and gold standard Ag/AgCl electrodes.
    • The 3D-printed sensors effectively distinguished varying levels of muscle activity.
    • Demonstrated proof-of-principle for hand gesture recognition using a 3D-printed 8-electrode band.

    Conclusions:

    • 3D-printed sEMG electrodes are a viable, personalized, and potentially low-cost alternative to traditional sensors.
    • These sensors exhibit comparable performance to conventional electrodes.
    • The technology holds significant promise for integration into prosthetic, assistive devices, and human-computer interfaces.