AIMC Topic: Electromyography

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Aggregate features in multisample classification problems.

IEEE journal of biomedical and health informatics
This paper evaluates the classification of multisample problems, such as electromyographic (EMG) data, by making aggregate features available to a per-sample classifier. It is found that the accuracy of this approach is superior to that of traditiona...

Robot-assisted gait training improves motor performances and modifies Motor Unit firing in poststroke patients.

European journal of physical and rehabilitation medicine
BACKGROUND: Robotics and related technologies are realizing their promise to improve the delivery of rehabilitation therapy but the mechanism by which they enhance recovery is still unknown. The electromechanical-driven gait orthosis Lokomat has demo...

The Hypno-PC: uncovering sleep dynamics through principal component analysis and hidden Markov modeling of electrophysiological signals.

Sleep
Manual sleep scoring segments sleep into discrete 30-s epochs (wake, non-rapid-eye-movement [NREM] 1-3, rapid-eye-movement [REM]), yet substantial evidence suggests that sleep unfolds as a continuous, microstate-rich process. Using a data-driven appr...

Integrating Motor Unit Activity With Deep Learning for Real-Time, Simultaneous and Proportional Wrist Angle and Grasp Force Estimation.

IEEE transactions on bio-medical engineering
OBJECTIVE: Myoelectric prostheses offer great promise in enabling amputees to perform daily activities independently. However, existing neural interfaces generally cannot simultaneously and proportionally decode kinematics and kinetics in real time, ...

Hierarchical Transformer Fusion of Gaze Attention and Muscle Activity for Forearm Movement Estimation.

IEEE transactions on bio-medical engineering
Tracking forearm movement via measured physiological signals is crucial for understanding human motor control mechanism. Current methods mainly use muscle-derived signals to predict arm movements while often overlooking the potential role of gaze att...

A Pilot Study on Fabric-Based Pneumatic Soft Gloves for Assisting Patients With Severe Brachial Plexus Injury.

IEEE transactions on bio-medical engineering
OBJECTIVE: Robotic gloves show promise in hand assistance due to their wearability and home-based potential, yet empirical research remains limited. This pilot study presents a fabric-based pneumatic soft glove, aiming to identify its potential and c...

PhyTransformer: A unified framework for learning spatial-temporal representation from physiological signals.

Neural networks : the official journal of the International Neural Network Society
As a modal of physiological information, electroencephalogram (EEG), surface electromyography (sEMG), and eye tracking (ET) signals are widely used to decode human intention, promoting the development of human-computer interaction systems. Extensive ...

Geometry of orofacial neuromuscular signals: speech articulation decoding using surface electromyography.

Journal of neural engineering
In this article, we present data and methods for decoding speech articulations using surface electromyogram (EMG) signals. EMG-based speech neuroprostheses offer a promising approach for restoring audible speech in individuals who have lost the abili...

Ultra-low-power System-on-Chip for automated screening of central apnea and hypopnea via chin electromyography.

Computers in biology and medicine
Central Apnea (CA) and Central Hypopnea (CH) are sleep disorders arising from the brain's inability to signal respiratory muscles, potentially leading to severe complications such as heart failure. This study presents a novel system for automating CA...