AIMC Topic: Electromyography

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Electrophysiological Muscle Classification Using Multiple Instance Learning and Unsupervised Time and Spectral Domain Analysis.

IEEE transactions on bio-medical engineering
OBJECTIVE: Electrophysiological muscle classification (EMC) is a crucial step in the diagnosis of neuromuscular disorders. Existing quantitative techniques are not sufficiently robust and accurate to be reliably clinically used. Here, EMC is modeled ...

Bipedal robotic walking control derived from analysis of human locomotion.

Biological cybernetics
This paper proposes the design of a bipedal robotic controller where the function between the sensory input and motor output is treated as a black box derived from human data. In order to achieve this, we investigated the causal relationship between ...

Implementation of a Surface Electromyography-Based Upper Extremity Exoskeleton Controller Using Learning from Demonstration.

Sensors (Basel, Switzerland)
Upper-extremity exoskeletons have demonstrated potential as augmentative, assistive, and rehabilitative devices. Typical control of upper-extremity exoskeletons have relied on switches, force/torque sensors, and surface electromyography (sEMG), but t...

Permutation Entropy and Signal Energy Increase the Accuracy of Neuropathic Change Detection in Needle EMG.

Computational intelligence and neuroscience
Needle electromyography can be used to detect the number of changes and morphological changes in motor unit potentials of patients with axonal neuropathy. General mathematical methods of pattern recognition and signal analysis were applied to recogn...

Efficacy of the Regent Suit-based rehabilitation on gait EMG patterns in hemiparetic subjects: a pilot study.

European journal of physical and rehabilitation medicine
BACKGROUND: The recovery of the functional limb mobility of patients with cerebral damages can take great benefit of the role offered by proprioceptive rehabilitation. Recently have been developed a special Regent Suit (RS) for rehabilitative applica...

Motor modules during adaptation to walking in a powered ankle exoskeleton.

Journal of neuroengineering and rehabilitation
BACKGROUND: Modules of muscle recruitment can be extracted from electromyography (EMG) during motions, such as walking, running, and swimming, to identify key features of muscle coordination. These features may provide insight into gait adaptation as...

Gait performance and foot pressure distribution during wearable robot-assisted gait in elderly adults.

Journal of neuroengineering and rehabilitation
BACKGROUND: A robotic exoskeleton device is an intelligent system designed to improve gait performance and quality of life for the wearer. Robotic technology has developed rapidly in recent years, and several robot-assisted gait devices were develope...

Relevant Features Selection for Automatic Prediction of Preterm Deliveries from Pregnancy ElectroHysterograhic (EHG) records.

Journal of medical systems
In this study, we proposed an approach able to predict whether a pregnant woman with contractions would give birth earlier than expected (i.e., before the 37 week of gestation (WG)). It only processes non-invasive electrohysterographic (EHG) signals...

Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and h...