Modeling and Emulating a Physiotherapist's Role in Robot‐Assisted Rehabilitation

In home‐based rehabilitation, one possible approach is haptic teleoperation in which a hospital‐based therapist is haptically linked and tele‐presented to a home‐based patient to effectively simulate traditional in‐hospital therapies over a distance. In this context, this article proposes a learn‐and‐replay (LAR) paradigm that consists of two phases: a therapist‐in‐loop (interactive) phase where the therapist interacts through the haptic teleoperation loop with the patient to perform the cooperative therapy task, and a therapist‐out‐of‐loop (standalone) phase where the therapist's task is played by the patient‐side robot in future repetitions. During the interactive phase, the therapist demonstrates impedance during cooperating with the patient. During the standalone phase, the patient‐side robot is automatically controlled to mimic the therapist's demonstrated impedance which is learned in the interactive phase. The direct force reflection (DFR) architecture is utilized as the control method for the bilateral telerehabilitation system. Case studies involving 1‐degree‐of‐freedom and 2‐degree‐of‐freedom cooperative manipulation tasks are tested for proof of concept. The results show that the impedance of the therapist's arm can be replicated by the patient‐side robot for both tasks and proposed LAR telerehabilitation paradigm that assists the therapist in the rehabilitation procedure to take care of other tasks or attend to other patients.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Modeling and Emulating a Physiotherapist's Role in Robot‐Assisted Rehabilitation ; volume:2 ; number:7 ; year:2020 ; extent:16 ; Advanced intelligent systems ; 2, Heft 7 (2020) (gesamt 16)

Contributors, Places and Time

• Creator: Tao, Ran ; Ocampo, Renz ; Fong, Jason ; Soleymani, Abed ; Tavakoli, Mahdi

Further information

• DOI: 10.1002/aisy.201900181
• URN: urn:nbn:de:101:1-2022062910533813586721
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:23 AM CEST