Med Eng Phys, 2014 · DOI: 10.1016/j.medengphy.2014.09.008 · Published: December 1, 2014
Voluntary surface electromyogram (EMG) signals from neurological injury patients are often corrupted by involuntary background interference or spikes, imposing difficulties for myoelectric control. This study presents a framework that applies a Wiener filter to restore voluntary surface EMG signals based on tracking a priori signal to noise ratio (SNR) by using the decision-directed method. The proposed framework is characterized by quick and simple implementation, making it more suitable for application in a myoelectric control system toward neurological injury rehabilitation.
The proposed Wiener filtering framework enhances the accuracy and reliability of myoelectric control systems by effectively suppressing involuntary background spikes in EMG signals, leading to better control for neurological injury patients.
The study demonstrates that the onset detection of voluntary muscle activity is significantly improved, which is crucial for triggering and controlling assistive devices or rehabilitation robots.
The quick and simple implementation of the framework makes it suitable for real-time applications, enabling timely and effective control in myoelectric systems.