Related Experiment Video
Updated: Aug 14, 2026
09:42
Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography
Published on: January 24, 2025
Intelligent analysis of EMG data for improving lifestyle
Mark Donnelly1, Richard Davies, Chris Nugent
1School of Computing and Mathematics, Faculty of Engineering, University of Ulster at Jordanstown, Northern Ireland.
Studies in Health Technology and Informatics
|November 12, 2005
Summary
Brain maps enable amputees to control artificial hands using phantom sensations. Electromyography (EMG) signals are processed by AI models for intuitive prosthetic control, restoring mobility.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Artificial Intelligence
Background:
- Limb loss necessitates prosthetic use for mobility.
- Intact neural "body maps" in the brain can generate phantom sensations after amputation.
- Phantom sensations, though sometimes uncomfortable, offer a pathway for controlling prosthetic devices.
Purpose of the Study:
- To investigate the use of phantom sensations for controlling artificial hands.
- To develop and classify Electromyography (EMG) signals for prosthetic control.
- To create AI-based models for intuitive artificial hand operation.
Main Methods:
- Acquisition and analysis of Electromyography (EMG) signals.
- Development of a custom EMG signal recording device.
- Implementation of heuristic approaches and Artificial Intelligence (AI) classifiers, including Neural Networks, for signal classification.
Main Results:
- Successful acquisition and analysis of EMG signals.
- Development of classification models capable of interpreting EMG data.
- Demonstrated potential for controlling artificial hands through processed EMG signals.
Conclusions:
- Phantom sensations linked to intact "body maps" can be harnessed for prosthetic control.
- EMG signal processing, enhanced by AI, offers a viable method for intuitive artificial hand operation.
- This research paves the way for improved prosthetic functionality and patient mobility after limb loss.
