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Related Concept Videos

Somatosensation01:33

Somatosensation

The somatosensory system relays sensory information from the skin, mucous membranes, limbs, and joints. Somatosensation is more familiarly known as the sense of touch. A typical somatosensory pathway includes three types of long neurons: primary, secondary, and tertiary. Primary neurons have cell bodies located near the spinal cord in groups of neurons called dorsal root ganglia. The sensory neurons of ganglia innervate designated areas of skin called dermatomes.
Hierarchy of Motor Control01:18

Hierarchy of Motor Control

The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.

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Related Experiment Video

Updated: May 25, 2026

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
06:58

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

Control of hand prostheses using peripheral information.

Silvestro Micera1, Jacopo Carpaneto, Stanisa Raspopovic

  • 1ARTS Lab, Scuola Superiore Sant'Anna, 56127 Pisa, Italy. micera@sssup.it

IEEE Reviews in Biomedical Engineering
|January 26, 2012
PubMed
Summary
This summary is machine-generated.

This review compares electromyographic (EMG) and electroneurographic (ENG) signals for controlling prosthetic hands. It details methods and outcomes for improved prosthesis control in individuals with impairments.

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Area of Science:

  • Biomedical Engineering
  • Rehabilitation Technology
  • Neuroprosthetics

Background:

  • Dexterous hand prosthesis control is crucial for individuals with impairments.
  • Signal selection significantly impacts prosthesis functionality and user experience.

Purpose of the Study:

  • To review and discuss recent advancements in prosthetic hand control using biological signals.
  • To compare the efficacy of electromyographic (EMG) and electroneurographic (ENG) signals.

Main Methods:

  • Review of studies utilizing surface electromyography (sEMG) and intramuscular electromyography (iEMG).
  • Analysis of electroneurographic (ENG) signal applications in prosthesis control.
  • Evaluation of signal processing and control strategies.

Main Results:

  • Both sEMG and iEMG offer viable pathways for prosthesis control, each with distinct advantages and limitations.
  • ENG signals present unique opportunities for high-fidelity control.
  • Effective control requires careful consideration of signal acquisition, processing, and integration.

Conclusions:

  • The choice of signal (sEMG, iEMG, or ENG) is critical for optimizing hand prosthesis control.
  • Further research is needed to refine signal processing and develop comprehensive control frameworks.
  • A clear roadmap is presented to guide future developments in dexterous hand prosthesis control.