Exploring user engagement with real-time verbal feedback from an exoskeleton-based virtual exercise coach

Raju Maharjan, Sanjana Mendu, Milton Mariani, Saeed Abdullah, John Paulin Hansen

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: Engaging users during physical exercise is crucial for fostering long-term commitment, however, sustaining that engagement remains a significant challenge. This study explores the design of a voice-enabled exoskeleton-based virtual exercise coach (VEC) that provides real-time verbal feedback to enhance user engagement. The objectives of this study are twofold: (i) to compare user engagement with real-time verbal feedback from both VEC and human exercise coach (HEC) during physical exercise, and (ii) to understand users’ perceptions and gather their recommendations for improving future VEC technologies. Methods: We developed an exoskeleton-based VEC that delivers real-time verbal feedback on users’ exercise performance. To evaluate its impact on user engagement, we conducted a lab-based mixed-methods study ( (Formula presented.) ) over a period of 6 weeks comparing users’ engagement with the VEC and HEC using User Engagement Scale (UES) questionnaire and conducted semi-structured interviews to understand users’ perceptions of the VEC. Results: Participants in this study found the VEC more engaging than the HEC, in terms of focused attention ( (Formula presented.) ) and perceived usability ( (Formula presented.) ). Post-interaction interviews revealed that (i) users found the VEC to be engaging, intuitive, easy to use, and convenient; (ii) users perceived the VEC as a valuable training companion that could help reduce the emotional insecurities often associated with going to the gym; and (iii) users expressed a desire for the VEC to have a personality and embodiment that motivates and supports personalized interactions. Conclusion: Based on our results, we discuss the challenges and implications for designing future voice-enabled VECs that support engaging physical exercises.

Original languageEnglish (US)
JournalDigital Health
Volume10
DOIs
StatePublished - Jan 1 2024

All Science Journal Classification (ASJC) codes

  • Health Policy
  • Health Informatics
  • Computer Science Applications
  • Health Information Management

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