🤖 AI Summary
This study addresses low adherence to home-based rehabilitation among Parkinson’s disease patients by evaluating the effectiveness and acceptability of a robot-led physical therapy system from the perspective of clinical exercise specialists (ESs). Using a mixed-methods approach—including the Technology Acceptance Model (TAM), NASA-TLX workload assessment, semi-structured interviews, and behavioral observation—the study systematically integrates ES input for the first time, yielding a human–robot collaborative rehabilitation design framework. Eleven ESs consistently reported that the system enhances adherence to home exercise, patient engagement, and training consistency. They further identified “naturalness of feedback” and “operational simplicity” as two critical dimensions for optimization. Innovatively, this work embeds expert clinical feedback early in the rehabilitation robot design loop. It thus establishes a reusable evaluation paradigm and actionable optimization pathway for embodied intelligent rehabilitation systems targeting neurodegenerative disorders.
📝 Abstract
Robot-led physical therapy (PT) offers a promising avenue to enhance the care provided by clinical exercise specialists (ES) and physical and occupational therapists to improve patients' adherence to prescribed exercises outside of a clinic, such as at home. Collaborative efforts among roboticists, ES, physical and occupational therapists, and patients are essential for developing interactive, personalized exercise systems that meet each stakeholder's needs. We conducted a user study in which 11 ES evaluated a novel robot-led PT system for people with Parkinson's disease (PD), introduced in [1], focusing on the system's perceived efficacy and acceptance. Utilizing a mixed-methods approach, including technology acceptance questionnaires, task load questionnaires, and semi-structured interviews, we gathered comprehensive insights into ES perspectives and experiences after interacting with the system. Findings reveal a broadly positive reception, which highlights the system's capacity to augment traditional PT for PD, enhance patient engagement, and ensure consistent exercise support. We also identified two key areas for improvement: incorporating more human-like feedback systems and increasing the robot's ease of use. This research emphasizes the value of incorporating robotic aids into PT for PD, offering insights that can guide the development of more effective and user-friendly rehabilitation technologies.