AIMC Topic: Electromyography

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The Role of Surface Electromyography in Data Fusion with Inertial Sensors to Enhance Locomotion Recognition and Prediction.

Sensors (Basel, Switzerland) Sep 19, 2021
Locomotion recognition and prediction is essential for real-time human-machine interactive control. The integration of electromyography (EMG) with mechanical sensors could improve the performance of locomotion recognition. However, the potential of E...
Humans Neural Networks, Computer Algorithms Support Vector Machine Electromyography Locomotion
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Home-based self-help telerehabilitation of the upper limb assisted by an electromyography-driven wrist/hand exoneuromusculoskeleton after stroke.

Journal of neuroengineering and rehabilitation Sep 15, 2021
BACKGROUND: Most stroke survivors have sustained upper limb impairment in their distal joints. An electromyography (EMG)-driven wrist/hand exoneuromusculoskeleton (WH-ENMS) was developed previously. The present study investigated the feasibility of a...
Electromyography Stroke Upper Extremity Telerehabilitation Wrist Stroke Rehabilitation Treatment Outcome Robotics Humans
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Action Recognition of Lower Limbs Based on Surface Electromyography Weighted Feature Method.

Sensors (Basel, Switzerland) Sep 13, 2021
To improve the recognition rate of lower limb actions based on surface electromyography (sEMG), an effective weighted feature method is proposed, and an improved genetic algorithm support vector machine (IGA-SVM) is designed in this paper. First, for...
Lower Extremity Electromyography Algorithms Support Vector Machine
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Speed controller-based fuzzy logic for a biosignal-feedbacked cycloergometer.

Computer methods in biomechanics and biomedical engineering Sep 11, 2021
Nowadays, fuzzy-logic systems are implemented to control machinery or processes that previously required human manipulation. The main objective of this research is to propose a controller based on fuzzy-logic that uses bio-signals for decision making...
Fuzzy Logic Electroencephalography Electromyography Humans
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Classifying muscle parameters with artificial neural networks and simulated lateral pinch data.

PloS one Sep 2, 2021
OBJECTIVE: Hill-type muscle models are widely employed in simulations of human movement. Yet, the parameters underlying these models are difficult or impossible to measure in vivo. Prior studies demonstrate that Hill-type muscle parameters are encode...
Muscle, Skeletal Electromyography Computer Simulation Humans Tendons Thumb Neural Networks, Computer Biomechanical Phenomena Hand Strength
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MuscleNET: mapping electromyography to kinematic and dynamic biomechanical variables by machine learning.

Journal of neural engineering Aug 19, 2021
This paper proposes machine learning models for mapping surface electromyography (sEMG) signals to regression of joint angle, joint velocity, joint acceleration, joint torque, and activation torque.The regression models, collectively known as MuscleN...
Machine Learning Biomechanical Phenomena Muscle, Skeletal Humans Neural Networks, Computer Electromyography Torque
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Targeted muscle effort distribution with exercise robots: Trajectory and resistance effects.

Medical engineering & physics Jul 3, 2021
The objective of this work is to relate muscle effort distributions to the trajectory and resistance settings of a robotic exercise and rehabilitation machine. Muscular effort distribution, representing the participation of each muscle in the trainin...
Exercise Muscle, Skeletal Electromyography Torque Robotics
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Muscle network topology analysis for the classification of chronic neck pain based on EMG biomarkers extracted during walking.

PloS one Jun 21, 2021
Neuromuscular impairments are frequently observed in patients with chronic neck pain (CNP). This study uniquely investigates whether changes in neck muscle synergies detected during gait are sensitive enough to differentiate between people with and w...
Young Adult Adult Male Algorithms Neck Pain Female Humans Chronic Pain Superficial Back Muscles Electromyography Models, Theoretical Paraspinal Muscles Walking Musculoskeletal System Support Vector Machine Neck Muscles Gait
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Classification of Walking Environments Using Deep Learning Approach Based on Surface EMG Sensors Only.

Sensors (Basel, Switzerland) Jun 18, 2021
Classification of terrain is a vital component in giving suitable control to a walking assistive device for the various walking conditions. Although surface electromyography (sEMG) signals have been combined with inputs from other sensors to detect w...
Humans Muscle, Skeletal Electromyography Deep Learning Walking Leg
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Soft pneumatic elbow exoskeleton reduces the muscle activity, metabolic cost and fatigue during holding and carrying of loads.

Scientific reports Jun 15, 2021
To minimize fatigue, sustain workloads, and reduce the risk of injuries, the exoskeleton Carry was developed. Carry combines a soft human-machine interface and soft pneumatic actuation to assist the elbow in load holding and carrying. We hypothesize ...
Fatigue Exoskeleton Device Muscle Fatigue Robotics Gait Elbow Energy Metabolism Workload Humans Walking Biomechanical Phenomena Electromyography Muscle, Skeletal
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