Letter to the EditorSmoothing of electromyographic signals can influence the number of extracted muscle synergies
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Utilising dynamic motor control index to identify age-related differences in neuromuscular control
2024, Human Movement ScienceConsistency of muscle activation signatures across different walking speeds
2024, Gait and PostureMuscle synergies are modified with improved task performance in skill learning
2022, Human Movement ScienceCitation Excerpt :EMG data from trials before (Pre-L) and after practice (RetI) were subjected to muscle synergy analysis. Before performing MSA, EMG data were interpolated to 360 data points per crank cycle after detrending, band-pass filtering (20–450 Hz), rectification, and smoothing with a low pass Butterworth filter at 6 Hz (Barroso et al., 2014; Hug, Turpin, Dorel, & Guével, 2012). At least 7 crank revolutions were completed in all trials, so the last seven consecutive crank cycles for each trial were selected for MSA.
Locomotor coordination in patients with Hereditary Spastic Paraplegia
2019, Journal of Electromyography and KinesiologyAn automatic, adaptive, information-based algorithm for the extraction of the sEMG envelope
2018, Journal of Electromyography and KinesiologyCitation Excerpt :Moreover, recent studies have shown that selection of the cut-off frequency for envelope estimation can significantly impact the information obtained from muscle synergies analysis. In particular, it has been shown (Hug et al., 2012; Schuman et al., 2017) that different settings of the filtering procedure give raise to a high variability in the determination of the correct number of synergies. In this scenario our algorithm selecting the point-by-point optimal window length should theoretically facilitate the identification process.