2007
DOI: 10.1016/j.jelekin.2006.06.001
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Effect of electrode location on EMG signal envelope in leg muscles during gait

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Cited by 107 publications
(87 citation statements)
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“…The discharge rates, signal amplitude, spectral analysis could be investigated to estimate the neural control strategies involved in the muscles management. 27 These instrumental assessments should be performed applying the correct protocols; in fact, the myoelectric activity signal may vary due to many factors such as change in the electrode location, change in the tissue properties, tissue temperature, muscle resting length, velocity of contraction and fiber type [27][28][29][30] . In the last 30 years the effect of electrodes position on conduction velocity estimation (CV), amplitude and spectral variables of the surface EMG has been addressed in a number of methodological and clinical publications taking into account muscles (or groups of muscles) ranging from the masticatory muscles to the muscles of the shoulder, of the arm and leg too 31 .…”
Section: Discussionmentioning
confidence: 99%
“…The discharge rates, signal amplitude, spectral analysis could be investigated to estimate the neural control strategies involved in the muscles management. 27 These instrumental assessments should be performed applying the correct protocols; in fact, the myoelectric activity signal may vary due to many factors such as change in the electrode location, change in the tissue properties, tissue temperature, muscle resting length, velocity of contraction and fiber type [27][28][29][30] . In the last 30 years the effect of electrodes position on conduction velocity estimation (CV), amplitude and spectral variables of the surface EMG has been addressed in a number of methodological and clinical publications taking into account muscles (or groups of muscles) ranging from the masticatory muscles to the muscles of the shoulder, of the arm and leg too 31 .…”
Section: Discussionmentioning
confidence: 99%
“…The methods of information extraction about the representative features of the sEMG recordings are based on calculation of their coefficients of variation and autoregression, and on an analysis of their time-frequency and time-space characteristics [48]. Classification of signals can be performed with a variety of methods including linear discriminate analysis, Bayesian statistics, vector analysis, and the artificial neural network method [41,[49][50][51][52][53][54][55].…”
Section: Historical Backgroundmentioning
confidence: 99%
“…The side advantage is to use only one recording channel. Campanini et al [9] recorded five muscles of the leg of 10 normal adults walking at their comfortable speed with matrix of ECG electrodes spaced out 2 cm apart. From EMG envelope they concluded "... the estimate of muscle activation intensity during gait from surface EMG is variable with location of the electrodes while timing of muscle activity is more robust to electrode displacement and can be reliably extracted in those case in which crosstalk is limited."…”
Section: Minimal Crosstalk Area (Mca)mentioning
confidence: 99%