. This paper aims to investigate the feasibility and the validity of applying deep convolutional neural networks (CNN) to identify motor unit (MU) spike trains and estimate the neural drive to muscles from high-density electromyography (HD-EMG) signa...
Grasp force estimation based on surface electromyography (sEMG) is essential for the dexterous control of a prosthetic hand. Nowadays, although increasing the number of sEMG measurement positions and extracting more features are common methods to inc...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 30, 2021
This paper aims to improve the performance of an electromyography (EMG) decoder based on a switching mechanism in controlling a rehabilitation robot for assisting human-robot cooperation arm movements. For a complex arm movement, the major difficulty...
We present an approach for real-time model-free optimization of the orientation of the elliptical trajectory. The performance is evaluated in simulation and experimental stages. Our model-free approach is based on the use of Extremum Seeking Control ...
Medical & biological engineering & computing
Mar 21, 2021
Jump locomotion is the basic movement of human. However, no thorough research on the recognition of jump sub-phases has been carried so far. This paper aims to use multi-sensor information fusion and machine learning to recognize the human jump phase...
Recent advances in the field of neural rehabilitation, facilitated through technological innovation and improved neurophysiological knowledge of impaired motor control, have opened up new research directions. Such advances increase the relevance of e...
Journal of neuroengineering and rehabilitation
Feb 25, 2021
BACKGROUND: Advanced prostheses can restore function and improve quality of life for individuals with amputations. Unfortunately, most commercial control strategies do not fully utilize the rich control information from residual nerves and musculatur...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Feb 25, 2021
In myoelectric machine learning (ML) based control, it has been demonstrated that control performance usually increases with training, but it remains largely unknown which underlying factors govern these improvements. It has been suggested that the i...
ForceMyography (FMG) is an emerging competitor to surface ElectroMyography (sEMG) for hand gesture recognition. Most of the state-of-the-art research in this area explores different machine learning algorithms or feature engineering to improve hand g...
Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
Feb 16, 2021
BACKGROUND: Recovery of hand function after stroke represents the hardest target for clinicians. Robot-assisted therapy has been proved to be effective for hand recovery. Nevertheless, studies aimed to refer patients to the best therapy are missing.