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Electromyography

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Biomechanical effects of body weight support with a novel robotic walker for over-ground gait rehabilitation.

Medical & biological engineering & computing
Body weight support (BWS) promotes better functional outcomes for neurologically challenged patients. Despite the established effectiveness of BWS in gait rehabilitation, the findings on biomechanical effects of BWS training still remain contradictor...

A biologically-inspired multi-joint soft exosuit that can reduce the energy cost of loaded walking.

Journal of neuroengineering and rehabilitation
BACKGROUND: Carrying load alters normal walking, imposes additional stress to the musculoskeletal system, and results in an increase in energy consumption and a consequent earlier onset of fatigue. This phenomenon is largely due to increased work req...

Cascaded Adaptation Framework for Fast Calibration of Myoelectric Control.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In spite of several decades of intensive research and development, the existing algorithms of myoelectric pattern recognition (MPR) are yet to make significant clinical and commercial impact. This study focuses on the one of the limiting factors of c...

Online Bimanual Manipulation Using Surface Electromyography and Incremental Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The paradigm of simultaneous and proportional myocontrol of hand prostheses is gaining momentum in the rehabilitation robotics community. As opposed to the traditional surface electromyography classification schema, in simultaneous and proportional c...

Neural Data-Driven Musculoskeletal Modeling for Personalized Neurorehabilitation Technologies.

IEEE transactions on bio-medical engineering
OBJECTIVES: The development of neurorehabilitation technologies requires the profound understanding of the mechanisms underlying an individual's motor ability and impairment. A major factor limiting this understanding is the difficulty of bridging be...

Multiple classifier systems for automatic sleep scoring in mice.

Journal of neuroscience methods
BACKGROUND: Electroencephalogram (EEG) and electromyogram (EMG) recordings are often used in rodents to study sleep architecture and sleep-associated neural activity. These recordings must be scored to designate what sleep/wake state the animal is in...

Implementation of EMG- and Force-Based Control Interfaces in Active Elbow Supports for Men With Duchenne Muscular Dystrophy: A Feasibility Study.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
While there is an extensive number of studies on the development and evaluation of electromyography (EMG)- and force-based control interfaces for assistive devices, no studies have focused on testing these control strategies for the specific case of ...

Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation.

PloS one
In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activit...

Predicting Functional Recovery in Chronic Stroke Rehabilitation Using Event-Related Desynchronization-Synchronization during Robot-Assisted Movement.

BioMed research international
Although rehabilitation robotics seems to be a promising therapy in the rehabilitation of the upper limb in stroke patients, consensus is still lacking on its additive effects. Therefore, there is a need for determining the possible success of roboti...

Wavelet-based unsupervised learning method for electrocardiogram suppression in surface electromyograms.

Medical engineering & physics
We present a novel approach aimed at removing electrocardiogram (ECG) perturbation from single-channel surface electromyogram (EMG) recordings by means of unsupervised learning of wavelet-based intensity images. The general idea is to combine the sui...