- Adaptive real-time decomposition algorithm for detecting muscle activation.
- New motor units are identified and improved the accuracy of decomposition is achieved with the algorithm.
Motor units (MU) are a basis of muscle activation and transmit firing activities into contractions of muscle fibers. MU can provide insight into the conditions around neuromuscular control. MU activity can be captured using HD-EMG and extracted using source separation algorithms. These algorithms are computationally intensive, and the signals, therefore, need to be processed offline. Real-time approaches have been developed but have limitations in the number of MU that can be detected and the quality of the signal. An improved real-time decomposition algorithm is needed for use in research and clinical settings.
Researchers in the Department of Biomedical Engineering has developed an adaptive real-time decomposition algorithm for detecting muscle activation. This is a parallel-double-thread computation algorithm, with the backend performing separation matrix updates, while the frontend performs the real-time decomposition. The separation matrix updates alleviate the performance degradation of the decomposition. Studies with simulated signals were used to evaluate the performance of the real-time algorithm. This demonstrated that the real-time algorithm identified new motor units (3-4 fold over 30 minutes) and improved the accuracy of decomposition up to 10% in real-time, compared to approaches without real-time decomposition.
- Adaptive real-time MU decomposition
- Enhanced identification of new MU
- Improved accuracy of decomposition compared to non-real-time approaches
Research and clinical EMG studies. Myoelectric control of rehabilitation or assistive devices.
Name: Matthew Howe