Selecting the best number of synergies in gait: Preliminary results on young and elderly people

Fiorenzo Artoni, Vito Monaco, Silvestro Micera

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Matrix factorization algorithms are increasingly used to extract meaningful information from multivariate EMG datasets. However a key issue is the selection of the number of synergies (i.e., model order) to retain. In this preliminary work a set of criteria, based on Independent Component Analysis, was developed to determine the number of synergies to extract from a multivariate EMG dataset, and applied on EMG signals acquired from 12 leg muscles during walking at different cadences (40, 60,., 140 strides per minute) in young and elderly subjects. The method was tested on ad-hoc created datasets with a predetermined number of embedded sources and amplitude of added noise. Young subjects walking patterns are explained by a number of synergies not significantly different with respect to elderly subjects. The inter-subject variability is greater at high (elderly) and low (young and elderly) cadences suggesting that the walking pattern is more stable at central frequencies. The type of preprocessing influences the number of underlying synergies: an increased number of independent components is needed to explain the variability of unfiltered data. The proposed method could serve as a guideline to scientists in the evaluation of walking performance. Further developments will include a validation of the method and its extension to other factorization algorithms.

Original languageEnglish
Title of host publicationIEEE International Conference on Rehabilitation Robotics
DOIs
Publication statusPublished - 2013
Event2013 IEEE 13th International Conference on Rehabilitation Robotics, ICORR 2013 - Seattle, WA, United States
Duration: Jun 24 2013Jun 26 2013

Other

Other2013 IEEE 13th International Conference on Rehabilitation Robotics, ICORR 2013
CountryUnited States
CitySeattle, WA
Period6/24/136/26/13

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Rehabilitation
  • Medicine(all)

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    Artoni, F., Monaco, V., & Micera, S. (2013). Selecting the best number of synergies in gait: Preliminary results on young and elderly people. In IEEE International Conference on Rehabilitation Robotics [6650416] https://doi.org/10.1109/ICORR.2013.6650416