• Title/Summary/Keyword: Rehabilitative Technologies

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A Survey of Multimodal Systems and Techniques for Motor Learning

  • Tadayon, Ramin;McDaniel, Troy;Panchanathan, Sethuraman
    • Journal of Information Processing Systems
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    • v.13 no.1
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    • pp.8-25
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    • 2017
  • This survey paper explores the application of multimodal feedback in automated systems for motor learning. In this paper, we review the findings shown in recent studies in this field using rehabilitation and various motor training scenarios as context. We discuss popular feedback delivery and sensing mechanisms for motion capture and processing in terms of requirements, benefits, and limitations. The selection of modalities is presented via our having reviewed the best-practice approaches for each modality relative to motor task complexity with example implementations in recent work. We summarize the advantages and disadvantages of several approaches for integrating modalities in terms of fusion and frequency of feedback during motor tasks. Finally, we review the limitations of perceptual bandwidth and provide an evaluation of the information transfer for each modality.

Real-Time, Simultaneous and Proportional Myoelectric Control for Robotic Rehabilitation Therapy of Stroke Survivors (뇌졸중 환자의 로봇 재활 치료를 위한 실시간, 동시 및 비례형 근전도 제어)

  • Jung, YoungJin;Park, Hae Yean;Maitra, Kinsuk;Prabakar, Nagarajan;Kim, Jong-Hoon
    • Therapeutic Science for Rehabilitation
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    • v.7 no.1
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    • pp.79-88
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    • 2018
  • Objective : Conventional therapy approaches for stroke survivors have required considerable demands on therapist's effort and patient's expense. Thus, new robotics rehabilitation therapy technologies have been proposed but they have suffered from less than optimal control algorithms. This article presents a novel technical healthcare solution for the real-time, simultaneous and propositional myoelectric control for stroke survivors' upper limb robotic rehabilitation therapy. Methods : To implement an appropriate computational algorithm for controlling a portable rehabilitative robot, a linear regression model was employed, and a simple game experiment was conducted to identify its potential of clinical utilization. Results : The results suggest that the proposed device and computational algorithm can be used for stroke robot rehabilitation. Conclusion : Moreover, we believe that these techniques will be used as a prominent tool in making a device or finding new therapy approaches in robot-assisted rehabilitation for stroke survivors.