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Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
Published on: July 26, 2013
Intention detection of gait initiation using EMG and kinematic data
E C Wentink1, S I Beijen, H J Hermens
1MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands. e.c.wentink@utwente.nl
Gait & Posture
|August 25, 2012
Summary
Detecting gait initiation in transfemoral amputees (TFA) is crucial for prosthetic control. This study shows that key gait events can be predicted in advance using EMG and motion data, enabling better prosthetic function.
Area of Science:
- Biomechanics
- Prosthetics
- Neurorehabilitation
Background:
- Gait initiation in transfemoral amputees (TFA) is impaired due to prosthetic limitations.
- Lack of stability and push-off in prosthetic legs affects TFA mobility.
- Enhanced prosthetic control could improve gait initiation for TFA.
Purpose of the Study:
- To assess the feasibility of real-time intention detection for gait initiation in TFA.
- To determine if gait initiation can be predicted early enough for prosthetic control.
- To evaluate the potential for artificial push-off and stability in prosthetic legs.
Main Methods:
- Mimicking TFA gait initiation challenges in non-amputee subjects.
- Measuring electromyography (EMG) and inertial sensor data.
- Analyzing kinematic data to detect key gait events like toe-off and heel-strike.
Main Results:
- Toe-off and heel-strike of the leading limb were detected 130-260 ms in advance.
- Detection was achieved using only EMG and kinematic data available in TFA.
- Sufficient time was identified for prosthetic control during gait initiation.
Conclusions:
- Real-time gait initiation intention detection is feasible for prosthetic control.
- Early detection of gait events allows for timely prosthetic adjustments.
- Hypothesizes similar predictive capabilities in TFA, enabling improved prosthetic function.
