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 paper 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 one or more repetitions of the cooperative therapy task, and a therapist-out-of-loop (standalone) phase where the therapist’s cooperative role of the task is played by the patient-side robot in future repetitions. During the interactive phase, the therapist demonstrates impedance during cooperating with the patient in performing the task. 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 one degree-of-freedom and two-degree-of- freedom cooperative manipulation tasks are tested for proof of concept. In the experiment, the therapists and patients were simulated by using healthy participants (the authors of the paper) and were located in the same room to show a proof-of-concept idea of the work. 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 assists the therapist in the rehabilitation procedure to take care of other tasks or attend to other patients.