Hierarchy in Algorithm-Based Feedback to Patients Working With a Robotic Rehabilitation System: Toward User-Experience Optimization

Daphne Fruchter, Ronit Feingold Polak, Sigal Berman, Shelly Levy-Tzedek

Research output: Contribution to journalArticlepeer-review

Abstract

When robotic systems are developed for individualized training during rehabilitation, providing effective feedback to the users is essential. We aimed to create a rule-based set of guidelines for the desired hierarchy, timing, content, and modality of feedback such a system should provide to users, such that they receive the necessary feedback, at the relevant time, in a way that enhances their performance, and does not encumber it. We conducted four focus groups with 20 stroke clinicians. The clinicians described the guiding principles they use when giving feedback to patients, and noted different output should be provided to the patient versus the clinician by the rehabilitation system. They delineated a hierarchy for providing feedback during the exercise set: success on the task is the primary goal, and feedback should be given on this aspect first. Once success is achieved, feedback should be given on the quality of the movement. Only when the task is successfully completed, with no compensatory movements (i.e., high quality), feedback should be given on movement speed. Using a follow-up survey and the member-checking approach, it was revealed that this hierarchical structure applies to early stages in the rehabilitation process, and that quality of movement becomes paramount as the rehabilitation process progresses. The clinicians expressed their desire to receive a full report on the patient's performance in each exercise session, which is more comprehensive than the feedback provided to the patient in real time. We conclude with a set of guidelines for developing automated feedback for patient populations.

Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalIEEE Transactions on Human-Machine Systems
DOIs
StateAccepted/In press - 1 Jan 2022

Keywords

  • Artificial intelligence
  • exergames
  • Guidelines
  • Interviews
  • participatory design
  • patient-centered
  • Robot sensing systems
  • Robots
  • socially assistive robotics
  • Stroke (medical condition)
  • Task analysis
  • user experience
  • Visualization

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Control and Systems Engineering
  • Signal Processing
  • Human-Computer Interaction
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

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