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Electromyography (EMG) employs widespread usage of rehabilitation robotics. EMG informs about the maximum capabilities of muscles and allows comparisons between different tasks performed. This presents a comparitive study % MVC (Maximum Voluntary Contraction) hand muscles among 30 to 60 years of age group. The movement considered are flexion and extension of elbow and wrist, pronation and supination...
Biomechanical investigation of human movement contributing to rehabilitation treatment has gained an increasing interest from researchers on regards to human impairments and assistive techniques. There are many methods of treatment previously investigated namely with the focus being towards the nervous system. Due to the advancement of technology over time, motion capture became possible where it...
This paper presents the use of a Wavelet Neural Network (WNN) as an efficient classifier of Electromyographic (EMG) signals. Generally, an EMG signal requires advanced methods for detection, decomposition, processing and classification. In this paper a WNN model will relate the firing frequency of motor unit action potentials (MUAPs) and three different muscle force levels, in order to improve the...
Surface electromyography (sEMG) has been widely used to estimate muscle activity. However, satisfying both low variability and rapid responsiveness of muscle activities using standard signal processing techniques such as the moving average (MAV), root mean square (RMS), and low-pass filter continues to present challenges. To address these issues, we propose a new method for EMG amplitude estimation...
A novel signal processing approach for surface electromyogram (EMG) is proposed to estimate the forces produced at multiple degree of freedom (DOF) simultaneously during dynamic voluntary contractions. The method is based on a generative model of surface EMG, and the estimation algorithm is a modified non-negative matrix factorization (NFM). The proposed method has potential to provide simultaneous...
This paper describes a real-time isometric pinch force prediction algorithm using surface electromyogram (sEMG). The activities of seven muscles related to the movements of the thumb and index finger joints, which are observable using surface electrodes, were recorded during pinch force experiments. For the successful implementation of the real-time prediction algorithm, an off-line analysis was performed...
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