Implementation and assessment of an intelligent motor tele-rehabilitation platform

Yves Rybarczyk, Jorge Luis Pérez Medina, Louis Leconte, Karina Jimenes, Mario González, Danilo Esparza

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


Over the past few years, software applications for medical assistance, including tele-rehabilitation, have known an increasing presence in the health arena. Despite the several therapeutic and economic advantages of this new paradigm, it is important to follow certain guidelines, in order to build a safe, useful, scalable, and ergonomic tool. This work proposes to address all these points, through the case study of a physical tele-rehabilitation platform for patients after hip replacement surgery. The scalability and versatility of the system is handled by the implementation of a modular architecture. The safeness and effectiveness of the tool is ensured by an artificial intelligence module that assesses the quality of the movements performed by the user. The usability of the application is evaluated by a cognitive walkthrough method. Results show that the system (i) is able to properly assess the correctness of the human’s motion through two possible methods (Dynamic Time Warping and Hidden Markov Model), and (ii) provides a good user experience. The discussion addresses (i) the advantages and disadvantages of the main approaches for a gesture recognition of therapeutic movements, and (ii) critical aspects to provide the patient with the best usability of a tele-rehabilitation platform.

Original languageEnglish
Article number58
JournalElectronics (Switzerland)
Issue number1
Publication statusPublished - 1 Jan 2019


  • Dynamic time warping
  • EHealth
  • Gesture recognition
  • Hidden Markov model
  • Software engineering
  • Usability


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