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Electromyography

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PCA and deep learning based myoelectric grasping control of a prosthetic hand.

Biomedical engineering online
BACKGROUND: For the functional control of prosthetic hand, it is insufficient to obtain only the motion pattern information. As far as practicality is concerned, the control of the prosthetic hand force is indispensable. The application value of pros...

Multiday EMG-Based Classification of Hand Motions with Deep Learning Techniques.

Sensors (Basel, Switzerland)
Pattern recognition of electromyography (EMG) signals can potentially improve the performance of myoelectric control for upper limb prostheses with respect to current clinical approaches based on direct control. However, the choice of features for cl...

Improving internal model strength and performance of prosthetic hands using augmented feedback.

Journal of neuroengineering and rehabilitation
BACKGROUND: The loss of an arm presents a substantial challenge for upper limb amputees when performing activities of daily living. Myoelectric prosthetic devices partially replace lost hand functions; however, lack of sensory feedback and strong und...

A Vision-Driven Collaborative Robotic Grasping System Tele-Operated by Surface Electromyography.

Sensors (Basel, Switzerland)
This paper presents a system that combines computer vision and surface electromyography techniques to perform grasping tasks with a robotic hand. In order to achieve a reliable grasping action, the vision-driven system is used to compute pre-grasping...

Sensor Fusion for Myoelectric Control Based on Deep Learning With Recurrent Convolutional Neural Networks.

Artificial organs
Electromyogram (EMG) signal decoding is the essential part of myoelectric control. However, traditional machine learning methods lack the capability of learning and expressing the information contained in EMG signals, and the robustness of the myoele...

Acute pain intensity monitoring with the classification of multiple physiological parameters.

Journal of clinical monitoring and computing
Current acute pain intensity assessment tools are mainly based on self-reporting by patients, which is impractical for non-communicative, sedated or critically ill patients. In previous studies, various physiological signals have been observed qualit...

Translation of robot-assisted rehabilitation to clinical service: a comparison of the rehabilitation effectiveness of EMG-driven robot hand assisted upper limb training in practical clinical service and in clinical trial with laboratory configuration for chronic stroke.

Biomedical engineering online
BACKGROUND: Rehabilitation robots can provide intensive physical training after stroke. However, variations of the rehabilitation effects in translation from well-controlled research studies to clinical services have not been well evaluated yet. This...

A Portable Passive Rehabilitation Robot for Upper-Extremity Functional Resistance Training.

IEEE transactions on bio-medical engineering
OBJECTIVE: Loss of arm function is common in individuals with neurological damage, such as stroke or cerebral palsy. Robotic devices that address muscle strength deficits in a task-specific manner can assist in the recovery of arm function; however, ...

Design and Evaluation of a Motorized Robotic Bed Mover With Omnidirectional Mobility for Patient Transportation.

IEEE journal of biomedical and health informatics
Patient transportation in hospitals faces many challenges, including the limited manpower, work-related injuries, and low efficiency of current bed pushing methods. This paper presents a new motorized robotic bed mover with omnidirectional mobility t...

Characterizing the SEMG patterns with myofascial pain using a multi-scale wavelet model through machine learning approaches.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
In this paper, we introduce a newly developed multi-scale wavelet model for the interpretation of surface electromyography (SEMG) signals and validate the model's capability to characterize changes in neuromuscular activation in cases with myofascial...