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Related Experiment Video

Updated: Jul 10, 2026

Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis

Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis

Published on: July 22, 2014

A control system for a powered prosthesis using positional and myoelectric inputs from the shoulder complex.

Y Losier¹, K Englehart, B Hudgins

¹Institute of Biomedical Engineering, University of New Brunswick, Fredericton, NB Canada. yves.losier@unb.ca

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|November 16, 2007

Summary

Integrating shoulder myoelectric signals and position data enhances prosthetic limb control. This hybrid approach enables smoother, intuitive multi-joint movements for users, advancing prosthetic technology.

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Area of Science:

Biomedical Engineering
Rehabilitation Robotics
Neuroprosthetics

Background:

Powered upper limb prostheses aim to restore natural movement.
Current control systems often lack intuitive multi-joint control.
Integrating diverse sensor data can improve prosthetic functionality.

Purpose of the Study:

To investigate the efficacy of combining myoelectric signals (MES) and shoulder position for prosthetic limb control.
To develop a hybrid control strategy for intuitive multi-joint reaching movements.
To advance the development of prosthetic systems capable of controlling three degrees of freedom (DOF).

Main Methods:

Utilized myoelectric signals (MES) from the shoulder area as an input source.
Incorporated shoulder position data as a complementary input source.
Employed multiple linear discriminant analysis (LDA) classifiers to process combined input signals.

Main Results:

The hybrid approach demonstrated potential for generating control signals for three DOF.
Combined MES and shoulder position data facilitated more intuitive user control.
The system showed promise for smoother, more natural multi-joint reaching movements.

Conclusions:

Combining myoelectric signals and shoulder position is a viable strategy for advanced prosthetic control.
This hybrid system represents a significant step towards simultaneous multi-DOF control in prosthetic limbs.
Further development of such hybrid systems can enhance user experience and functional recovery in prosthetic users.