Automatic detection of Spasticity from flexible wearable sensors

Luca Lonini, Nicholas Shawen, Roozbeh Ghaffari, John Rogers, Arun Jayarman

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

3 Scopus citations

Abstract

Spasticity is a condition that impairs voluntary muscle movements and physically debilitates persons across several neurological disorders, including stroke, multiple sclerosis and cerebral palsy. Assessing the progression of spasticity during clinical interventions and at home is key to rehabilitation efficacy and care management. Here we present electromyography (EMG) and motion data using skin-mounted, flexible and wireless sensors in a cohort of 13 individuals with stroke. We compute a set of 15 features from the EMG data and use machine learning to infer whether spasticity is present during movements of the knee and ankle joints. Using a Linear Discriminant Analysis (LDA) classifier, we show that our approach successfully discriminates voluntary contractions from spastic muscle contractions (AUC=0.94). These results show that continuous and non-invasive monitoring of spasticity symptoms could be applied to optimize and personalize rehabilitation regimens.

Original languageEnglish (US)
Title of host publicationUbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
PublisherAssociation for Computing Machinery, Inc
Pages133-136
Number of pages4
ISBN (Electronic)9781450351904
DOIs
StatePublished - Sep 11 2017
Event2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017 - Maui, United States
Duration: Sep 11 2017Sep 15 2017

Publication series

NameUbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers

Other

Other2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017
CountryUnited States
CityMaui
Period9/11/179/15/17

Keywords

  • Flexible electronics
  • Machine learning
  • Rehabilitation

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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  • Cite this

    Lonini, L., Shawen, N., Ghaffari, R., Rogers, J., & Jayarman, A. (2017). Automatic detection of Spasticity from flexible wearable sensors. In UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers (pp. 133-136). (UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers). Association for Computing Machinery, Inc. https://doi.org/10.1145/3123024.3123098