Trajectory Optimization Framework for Rehabilitation Robots With Multi-Workspace Objectives and Constraints

Sommerhalder, Michael; Zimmermann, Yves; Simovic, Leonardo; Hutter, Marco; Wolf, Peter; Riener, Robert

doi:10.1109/lra.2023.3311229

Cited by 2 publications

(1 citation statement)

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“…2). Exercise types consisted of 1D, 2D and 3D games either with joint movements in clinical coordinates (plane and angle of elevation, internal and external rotation, elbow flexion and extension, and wrist movements [17]) or hand movements in world coordinates (x, y, z, and rotational degrees of freedom [18]). Some exercises required to reach specific target coordinates (reach goal), while others required to follow a predefined reference path (nominal path).…”

Section: Influencing Variablesmentioning

confidence: 99%

Can Robotic Feedback and Adaptation Possibilities match Therapeutic Needs? - An Observational Study

Sommerhalder,

Büchi,

Risch

et al. 2024

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Purpose: An observational study on therapists was executed as a joint project between the Sensory-Motor Systems Lab, ETH Zurich, and the Swiss Paraplegic Centre, Nottwil. The primary goal was to establish a methodology to reasonably tailor current robotic systems to the therapist's preferences in terms of their interaction strategies with the patient. Methods: Therapist's interactions with the patient were recorded, either directly or through a robotic device with extended analysis tools and adaptation possibilities. Experience, operability bias and adaptation confidence of therapists were acquired through questionnaires. Correlation maps were derived to quantify the interaction strategies of the therapists. Results: A total of three distinct interaction strategies emerged based on therapist's personal preferences: Observation of compensatory movement and posture issues caused tactile reaction, issues with robotic settings led to robotic support adaptations, and robotic support adaptations preceded support adaptations. Two strategies emerged based on the exercise type: Mainly direct tactile reactions for reach-goal exercises, and mainly robotic support adaptations for nominal path exercises. The adaptation confidence of therapists strongly depended on the chosen strategies. Conclusion: Robotic systems can be tailored to the therapist's preferences in terms of their interaction strategies by quantifying the therapist's interactions with the robot and the patient. Missing parameters and analysis tools can be found by identifying compensatory strategies, i.e., situations where therapists are forced to swap to direct patient interactions or random parameter adaptations. With this study we presented a method to quantify these strategies with feasible effort.

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Section: Influencing Variablesmentioning

confidence: 99%