Oh no! She is Flying! Interaction Analysis of Therapist-Robot Collaboration in Gait Rehabilitation

Strokes are a leading cause of disability, with many survivors experiencing significant mobility impairments. While robot-assisted rehabilitation offers a promising solution, its adoption seems challenged by high upfront costs, low flexibility and complex configuration workflows. To address these challenges, this study conducts an interaction analysis to identify key requirements for empowering therapists to self-configure and adapt a flexible, cost-effective robot during gait rehabilitation tasks. Our analysis is based on 20 training sequences from a 60-hour video dataset collected across three experimental setups, involving young adults with motor impairments training with the assistance of the robot. Drawing methods from Ethnomethodology and Conversation Analysis (EMCA), we examined the sequential organization of actions between technology, therapist and participant, identifying three main stages: setup, training, and completion. During setup, coordinated actions prepare the participant and the robot for the main training task; during training, participant and robot engage in movement while the therapist iterates adjustments; and in completion, coordinated actions prepare the participant for transitioning back to their conventional support system. Our analysis highlights some requirements and strategies for developing End-User Development (EUD) environments for robot-assisted physiotherapy, emphasizing user-driven workflows, multimodal transitions between robot’s assistance modes, and real-time robotic feedback that maintains coherence with therapists’ practices. • Robot-assisted physical training follows a structured sequence with 3 main phases. • The gaze, speech, and touch of the therapists indicate transitions between phases. • Robot control modes adapt across phases to support evolving therapeutic goals. • Software engagement varies with each phase of therapy and the patient’s condition. • Therapists can adjust assistance settings before, during, and after active therapy.

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Publication Details

Journal
International Journal of Human-Computer Studies
Published
2025-10-27
DOI
https://doi.org/10.1016/j.ijhcs.2025.103620
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Field-Weighted Citation Impact
0.00

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article

Oh no! She is Flying! Interaction Analysis of Therapist-Robot Collaboration in Gait Rehabilitation

Gitte Rasmussen, Jose Pablo De la Rosa, Thiago Rocha Silva, Anders Stengaard Sørensen
International Journal of Human-Computer Studies
Stroke Rehabilitation and Recovery
article

Oh no! She is Flying! Interaction Analysis of Therapist-Robot Collaboration in Gait Rehabilitation

Gitte Rasmussen, Jose Pablo De la Rosa, Thiago Rocha Silva, Anders Stengaard Sørensen
article en

Abstract

Strokes are a leading cause of disability, with many survivors experiencing significant mobility impairments. While robot-assisted rehabilitation offers a promising solution, its adoption seems challenged by high upfront costs, low flexibility and complex configuration workflows. To address these challenges, this study conducts an interaction analysis to identify key requirements for empowering therapists to self-configure and adapt a flexible, cost-effective robot during gait rehabilitation tasks. Our analysis is based on 20 training sequences from a 60-hour video dataset collected across three experimental setups, involving young adults with motor impairments training with the assistance of the robot. Drawing methods from Ethnomethodology and Conversation Analysis (EMCA), we examined the sequential organization of actions between technology, therapist and participant, identifying three main stages: setup, training, and completion. During setup, coordinated actions prepare the participant and the robot for the main training task; during training, participant and robot engage in movement while the therapist iterates adjustments; and in completion, coordinated actions prepare the participant for transitioning back to their conventional support system. Our analysis highlights some requirements and strategies for developing End-User Development (EUD) environments for robot-assisted physiotherapy, emphasizing user-driven workflows, multimodal transitions between robot’s assistance modes, and real-time robotic feedback that maintains coherence with therapists’ practices. • Robot-assisted physical training follows a structured sequence with 3 main phases. • The gaze, speech, and touch of the therapists indicate transitions between phases. • Robot control modes adapt across phases to support evolving therapeutic goals. • Software engagement varies with each phase of therapy and the patient’s condition. • Therapists can adjust assistance settings before, during, and after active therapy.

International Journal of Human-Computer StudiesVol. 206
University of Southern Denmark (DK), Maersk (Denmark) (DK)
Syddansk Universitet
Openalex Percentile: Top 62%
Stroke Rehabilitation and Recovery
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