EMG Signals Case Study: A Time and Frequency Domain Analysis

Munteanu, Mihai; Rusu, Corneliu; Moga, Daniel; Moga, Rozica; Tont, Gabriela

doi:10.1007/978-3-642-22586-4_44

Cited by 2 publications

(1 citation statement)

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“…It should be noticed that we restrict the feature extraction procedure in this work to time-domain features, as we are interested in the identification of muscular activity rather than its classification and evaluation. From this perspective, the employment of further EMG features expressed in the frequency domain, e.g., mean frequency, median frequency or power spectral density [50], or mixed time-frequency domain, e.g., spectrogram or signal phase [51], assume a rather computationally complex extraction which is unjustified for our work.…”

Section: Lower-limb Emg Assessmentmentioning

confidence: 99%

A Novel Wearable Foot and Ankle Monitoring System for the Assessment of Gait Biomechanics

2020

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Walking is the most basic form of human activity for achieving mobility. As an essential function of the human body, the examination of walking is directed towards the assessment of body mechanics in posture and during movement. This work proposes a wearable smart system for the monitoring and objective evaluation of foot biomechanics during gait. The proposed solution assumes the cross-correlation of the plantar pressure with lower-limb muscular activity, throughout the stance phase of walking. Plantar pressure is acquired with an array of resistive pressure sensors deployed onto a shoe insole along the center of gravity progression line. Lower-limb muscular activity is determined from the electromyogram of the tibialis anterior and gastrocnemius lower limb muscles respectively. Under this scenario, physiological gait assumes the interdependency of plantar pressure on the heel area with activation of the tibialis anterior, as well as plantar pressure on the metatarsal arch/toe area with activation of the gastrocnemius. As such, assessment of gait physiology is performed by comparison of a gait map, formulated based on the footprint–lower-limb muscle cross-correlation results, to a reference gait template. A laboratory proof of concept validates the proposed solution in a test scenario which assumes a normal walking and two pathological walking patterns.

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Section: Lower-limb Emg Assessmentmentioning

confidence: 99%