Low-complexity inertial sensor-based characterization of the UPDRS score in the gait task of parkinsonians

Federico Parisi, Gianluigi Ferrari, Matteo Giuberti, Laura Contin, Veronica Cimolin, Corrado Azzaro, Giovanni Albani, Alessandro Mauro

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

Abstract

In this paper, we focus on the Gait Analysis (GA) for patients affected by Parkinson's Disease (PD) using a wireless Body Sensor Network (BSN) equipped with Inertial Measurement Units (IMUs). We estimate spatio-temporal parameters and other kinematic variables to characterize the gait, in both Parkinsonians and healthy people. Gait features are compared with scores assigned by neurologists within the Unified Parkinson's Disease Rating Scale (UPDRS), with the ultimate goal of automatically determining the UPDRS score of the Gait Task (GT) carried out by Parkinsonians. Preliminary results show a high correlation between a few gait parameters (such as double support, stride length, and thigh range of rotation) and UPDRS scores.

Original languageEnglish
Title of host publicationBODYNETS 2014 - 9th International Conference on Body Area Networks
PublisherICST
Pages69-75
Number of pages7
ISBN (Print)9781631900471
DOIs
Publication statusPublished - Nov 21 2014
Event9th International Conference on Body Area Networks, BODYNETS 2014 - London, United Kingdom
Duration: Sep 29 2014Oct 1 2014

Other

Other9th International Conference on Body Area Networks, BODYNETS 2014
CountryUnited Kingdom
CityLondon
Period9/29/1410/1/14

Keywords

  • Gait Analysis (GA)
  • Inertial measurement unit (IMU)
  • Parkinson's disease
  • Unified Parkinson's Disease Rating Scale (UPDRS)

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications

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