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Smart Web-Based Platform to Support Physical Rehabilitation.

Yves Rybarczyk1,2, Jan Kleine Deters3, Clément Cointe4

  • 1Intelligent & Interactive Lab (SI² Lab), Universidad de Las Américas, Quito 170124, Ecuador. yr@uninova.pt.

Sensors (Basel, Switzerland)
|April 28, 2018
PubMed
Summary

This study introduces a smart, web-based platform using Hidden Markov Models (HMMs) for real-time assessment of post-hip surgery rehabilitation exercises. The system accurately identifies movement errors, matching physiotherapist reliability.

Keywords:
Hidden Markov Modelmotion assessmentmotor rehabilitationnatural user interfacetelemedicine

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Area of Science:

  • Rehabilitation Technology
  • Medical Informatics
  • Biomechanical Analysis

Background:

  • Ubiquitous computing offers new avenues for medical rehabilitation.
  • Post-hip replacement surgery requires effective patient reeducation.
  • Tele-rehabilitation platforms need to be affordable and provide real-time feedback.

Purpose of the Study:

  • To develop a smart, web-based platform for hip replacement surgery rehabilitation.
  • To assess the correctness of patient movements in real-time.
  • To utilize affordable technology for accessible tele-rehabilitation.

Main Methods:

  • Development and training of ten Hidden Markov Models (HMMs).
  • A probabilistic approach to discriminate movement faults during therapeutic exercises.
  • Two experiments conducted in laboratory and clinical settings to evaluate algorithm precision.

Main Results:

  • The HMM-based algorithm accurately classifies movement errors in real-time.
  • Comparative analysis shows the models are as reliable as physiotherapists in identifying motion errors.
  • The system demonstrates high precision in both laboratory and clinical environments.

Conclusions:

  • The developed tele-rehabilitation platform is a reliable tool for post-hip surgery recovery.
  • The system's accuracy in movement error detection is comparable to that of human physiotherapists.
  • Further implementations can enhance the accuracy and usability of the smart rehabilitation system.