JMIR Publications

ABSTRACT

Background:

Home-based exercise programs for congenital muscular torticollis (CMT) depend heavily on caregivers, yet adherence is often hindered by cognitive and emotional burdens.

Objective:

This study conducted a formative usability evaluation of an AI-based CMT rehabilitation system comprising a clinician web interface and a caregiver mobile application to identify usability-related issues and preliminary design requirements during early development.

Methods:

A formative usability evaluation was conducted with eight clinical experts (rehabilitation physicians, nurses, and physical therapists). Participants engaged in focus group interviews (FGIs) following a demonstration of the system and completed the System Usability Scale (SUS) for the overall system, including a proxy evaluation of the caregiver mobile application. Qualitative data were analyzed using thematic analysis, and SUS scores were analyzed descriptively as a supplementary quantitative measure of perceived usability.

Results:

The thematic analysis identified two core themes, “Usability Barriers of the CMT Rehabilitation System” and “Improvement Requirements,” encompassing 10 subthemes and 21 concepts. Key findings highlighted concerns regarding the reliability and interpretability of AI-generated feedback and the need to simplify data visualization to reduce the potential cognitive burden on caregivers. The mean SUS score for the overall system was 73.44 (SD 18.01). This result was interpreted descriptively and considered supplementary to the qualitative findings.

Conclusions:

The formative evaluation identified preliminary usability strengths and areas for improvement from clinicians’ perspectives, with particular concerns regarding the reliability and interpretability of AI-generated feedback. The experts emphasized that the AI-based CMT rehabilitation system should function as a therapeutic bridge between clinicians and caregivers. As actual caregivers were not included in this evaluation, the findings represent preliminary formative design inputs based on clinicians’ proxy perspectives rather than evidence of usability for caregivers. Future iterations should incorporate the identified improvements and undergo evaluation with actual caregivers in home environments, along with separate technical verification of the accuracy of the AI feedback algorithm.