Abstract
Predicting and analysing individual muscle forces during walking can give a good perspective of anatomical, physiological, and neurological characteristics of human movement. It can help analyse neuromuscular impairments of skeletal system and provide an understanding on how lower limb assistive devices affect wearer’s body, as these assistive devices are vital to assist people with disabilities to carry their daily activities with ease. Estimating force from EMG allows us to assess the contribution of an individual muscle to the over-all force applied by a group of muscles. This finding helps in understanding muscle dynamics during walking, which can serve as input for assistive devices. Thus, electromyography signals (EMG) can be an excellent choice for force estimation in kinesiological studies. This study aims to predict individual muscle force from EMG during walking. The right gastrocnemius lateralis muscle of a 23-year-old-male subject with no neurological/muscular disorder was analysed at normal walking. Two approaches were used to predict forces from EMG using MATLAB. The forces obtained were compared with force predicted using OpenSim. The main parameters used for prediction were muscle length, muscle velocity, pennation angle, and isometric force, along with EMG.
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