Automated classification of bimanual movements in stroke telerehabilitation: A comparison of dimensionality reduction algorithms

Roni Barak Ventura, Francesco Vincenzo Surano, Maurizio Porfiri

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

Abstract

Stroke survivors commonly experience unilateral muscle weakness, which limits their engagement in daily activities. Bimanual training has been demonstrated to effectively recover coordinated movements among those patients. We developed a low cost telerehabilitation platform dedicated to bimanual exercise, where the patient manipulates a dowel to control a computer program. Data on movement is collected using a Microsoft Kinect sensor and an inertial measurement unit to interface the platform, as well as to assess motor performance remotely. Toward automatic classification of bimanual movements executed by the user, we test the performance of a linear and a nonlinear dimensionality reduction techniques.

Original languageEnglish (US)
Title of host publicationNano-, Bio-, Info-Tech Sensors and Wearable Systems
EditorsJaehwan Kim
PublisherSPIE
ISBN (Electronic)9781510640092
DOIs
StatePublished - 2021
Externally publishedYes
EventNano-, Bio-, Info-Tech Sensors and Wearable Systems 2021 - Virtual, Online, United States
Duration: Mar 22 2021Mar 26 2021

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11590
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceNano-, Bio-, Info-Tech Sensors and Wearable Systems 2021
Country/TerritoryUnited States
CityVirtual, Online
Period3/22/213/26/21

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Keywords

  • Data science
  • Dimensionality reduction
  • Motion analysis
  • Rehabilitation

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