Characterization of Electromyographical Signals from Biceps and Rectus Femoris Muscles to Evaluate the Performance of Squats Coupled with Countermeasure Gravitational Load Modulating Bodygear

Shankhwar, Vishwajeet; Singh, Dilbag; Deepak, K K

doi:10.1007/s12217-021-09899-z

Cited by 4 publications

(1 citation statement)

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“…By employing both time-domain and frequency-domain feature extraction methods, researchers aim to capture essential information from the sEMG signals and improve the accuracy and reliability of the subsequent classification and identification tasks [27][28][29][30].…”

Section: Semg Signal Feature Extractionmentioning

confidence: 99%

Positional analysis of assisting muscles for handling-assisted exoskeleton

Wang,

Guan,

et al. 2024

Preprint

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In order to better design the Handling-assisted exoskeleton, it is necessary to analyze the biomechanics of humane handling movements. In this study, Anybody Modeling System(AMS) simulation was used to analyze the movement state of muscles during humane handling. Combined with surface electromyography(sEMG) experiments, specific analysis and verification were carried out to obtain the position of muscles that the human body needs to assist during handling. In this study, the simulation and experiment were carried out for the manual handling process. The treatment group and the experimental group were set up. This study found that the vastus medialis muscle, vastus lateralis muscle, latissimus dorsi muscle, trapezius muscle, deltoid muscle and triceps brachii muscle needs more power in the process of handling, and it is reasonable and effective to combine sEMG signals with simulation of the musculoskeletal model to analyze the muscle condition of humane movement.

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Section: Semg Signal Feature Extractionmentioning

confidence: 99%