The Overview of Challenges in Detecting Patients' Hazards During Robot-Aided Remote Home Motor Rehabilitation

Authors

  • Julia Wilk Łukasiewicz Research Network - Industrial Research Institute for Automation and Measurements PIAP, Warsaw University of Technology
  • Piotr Falkowski Łukasiewicz Research Network - Industrial Research Institute for Automation and Measurements PIAP, Warsaw University of Technology
  • Tomasz Osiak Łukasiewicz Research Network - Industrial Research Institute for Automation and Measurements PIAP, The Józef Piłsudski University of Physical Education in Warsaw
Keywords: biosignals, biomechanics, home rehabilitation, kinesiotherapy, minimally-supervised treatment, rehabilitation robotics

Abstract

Home, minimally‐supervised rehabilitation has become an arising technological trend due to the shortages in medical staff. Implementing such requires providing advanced tools for automatic real‐time safety monitoring. The paper presents an approach to designing the mentioned safety system based on measurements and modelling the interface between a patient’s musculoskeletal system and a rehabilitation device. The content covers the segmentation of patients regarding their health conditions and assigns them suitable measurement techniques. The defined groups are described with the hazards, which they are most endangered, and their causes. Each case is correlated with the appropriate data type that may be used to detect potential risk. Moreover, a concept of using presented knowledge for tracking the safety of bones and soft tissues according to the biomechanical standards is included. The paper forms a set of guidelines for designing safety systems based on measurements for robot‐aided home kinesiotherapy. It can be used to select an appropriate approach regarding a specific case; so to decrease costs and increase the accuracy of the designed tools.

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Published
07.03.2024
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Articles

How to Cite

Wilk, J., Falkowski, P., & Osiak, T. (2024). The Overview of Challenges in Detecting Patients’ Hazards During Robot-Aided Remote Home Motor Rehabilitation. Journal of Automation, Mobile Robotics and Intelligent Systems, 17(4), 17-27. https://doi.org/10.14313/JAMRIS/4-2023/27