AIMC Topic: Electromyography

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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...

HapPro: A Wearable Haptic Device for Proprioceptive Feedback.

IEEE transactions on bio-medical engineering
OBJECTIVE: Myoelectric hand prostheses have reached a considerable technological level and gained an increasing attention in assistive robotics. However, their abandonment rate remains high, with unintuitive control and lack of sensory feedback being...

Deep learning for healthcare applications based on physiological signals: A review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: We have cast the net into the ocean of knowledge to retrieve the latest scientific research on deep learning methods for physiological signals. We found 53 research papers on this topic, published from 01.01.2008 to 31.12.20...

Motor-commands decoding using peripheral nerve signals: a review.

Journal of neural engineering
During the last few decades, substantial scientific and technological efforts have been focused on the development of neuroprostheses. The major emphasis has been on techniques for connecting the human nervous system with a robotic prosthesis via nat...