Journal
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
Volume 26, Issue 4, Pages 882-893Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSRE.2018.2810859
Keywords
Muscle synergies; upper limb; arm-reaching movements; EMG; factor analysis; data pre-processing
Categories
Funding
- Wyss Center for Bio and Neuroengineering
- RONDA Regione Toscana, Bando FAS Salute [2014 PAR FAS2007-2013]
- European Union's Horizon research and innovation programme under Marie Sklodowska Curie [750947]
- Marie Curie Actions (MSCA) [750947] Funding Source: Marie Curie Actions (MSCA)
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Muscle synergies have been used for decades to explain a variety of motor behaviors, both in humans and animals and, more recently, to steer rehabilitation strategies. However, many sources of variability such as factorization algorithms, criteria for dimensionality reduction and data pre-processing constitute a major obstacle to the successful comparison of the results obtained by different research groups. Starting from the canonical EMG processing we determined how variations in filter cut-off frequencies and normalization methods, commonly found in literature, affect synergy weights and inter-subject similarity (ISS) using experimental data related to a 15-muscles upper-limb reaching task. Synergy weights were not significantly altered by either normalization (maximum voluntary contraction - MVC - or maximum amplitude of the signal - SELF) or band-pass filter ([20-500 Hz] or [50-500] Hz). Normalization did, however, alter the amount of variance explained by a set of synergies, which is a criterion often used for model order selection. Comparing different low-pass (LP) filters (0.5 Hz, 4 Hz, 10 Hz, 20 Hz cut-offs) we showed that increasing the low pass filter cut-off had the effect of decreasing the variance accounted for by a set number of synergies and affected individual muscle contributions. Extreme smoothing (i.e., LP cut-off 0.5 Hz) enhanced the contrast between active and inactivemuscles but had an unpredictable effect on the ISS. The results presented here constitute a further step towards a thoughtful EMG pre-processing for the extraction of muscle synergies.
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