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Related Concept Videos

Motor Unit Stimulation01:20

Motor Unit Stimulation

When the neuron of a motor unit fires an action potential, it triggers a series of events, leading to a twitch contraction in the muscle fibers. The process of excitation-contraction coupling is crucial in relaying the action potential to the muscle fibers.
The latent period of contraction marks the onset of excitation-contraction coupling, when the action potential propagates across the sarcolemma, preparing the muscle fibers for contraction. As the fibers enter the contraction phase, the...

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SpiKon-E: Hybrid Soft Artificial Muscle Control Using Hardware Spiking Neural Network.

Florian-Alexandru Brașoveanu1, Mircea Hulea2, Adrian Burlacu1

  • 1Department of Automatic Control and Applied Informatics, Faculty of Automatic Control and Computer Engineering, "Gheorghe Asachi" Technical University of Iasi, Str. Dimitrie Mangeron, 700050 Iași, Romania.

Biomimetics (Basel, Switzerland)
|October 28, 2025
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Summary
This summary is machine-generated.

This study introduces a novel artificial muscle system using shape memory alloys and a hardware Spiking Neural Network (HW-SNN) for enhanced displacement and control in soft robotics and humanoid applications.

Keywords:
soft roboticsspiking neural networksystem control

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Area of Science:

  • Robotics
  • Materials Science
  • Biomimicry

Background:

  • Artificial muscles are crucial for advanced robotics and medical devices, shifting from servo motors to smart materials.
  • Current control strategies for artificial muscles require optimization to precisely mimic natural muscle actuation.

Purpose of the Study:

  • To design and implement a novel artificial muscle system that replicates biological muscle's full range of motion and control.
  • To advance sustainable soft robotics through innovative actuation and control mechanisms.

Main Methods:

  • Developed a novel shape memory alloy (SMA)-based linear actuator with a guiding mechanism for increased displacement.
  • Integrated the SMA actuator into a hybrid soft actuation structure with a silicone PneuNet and force sensor.
  • Utilized a hardware Spiking Neural Network (HW-SNN) for real-time force control at the actuator's endpoint.

Main Results:

  • The novel SMA linear actuator demonstrated significantly higher displacements compared to traditional SMA wire-driven systems.
  • The integrated hybrid soft actuation system provided real-time pressure feedback and precise force control.
  • Experimental results confirmed superior displacement and performance compared to traditional control-based SMA systems.

Conclusions:

  • The developed artificial muscle system successfully mimics biological muscle actuation, offering enhanced displacement and control.
  • This research contributes significantly to sustainable soft robotics, particularly in actuation and control for humanoid robotics.