Abstract
Abstract
Congenital muscular torticollis (CMT) is a common musculoskeletal problem associated with unilateral sternocleidomastoid muscle stiffness. We evaluated the feasibility of the newly developed digital therapeutics (DTx) ACESO-APP, a personalized exercise app with real-time feedback, using skeleton-based motion analysis and artificial intelligence-driven body reconstruction models. Fourteen participants were randomized to undergo either weekly PT with standard home program education (SE group) or weekly PT with digital therapeutics lead home program (DTx group). A 12-week home exercise program (HEP) comprising stretching exercises was encouraged in both groups with weekly in-hospital PT. Clinical changes were assessed using the torticollis overall assessment at 4, 8, and 12 weeks, and participants’ HEP adherence over 1 week was assessed using a questionnaire. Recruitment and completion rates, adherence rate, System Usability Scale scores, and adverse events were summarized using descriptive statistics. Eight participants (4 in each group) completed the study. The overall recruitment rate was approximately 5.2 participants per month, and the completion rate was 57.1% for both groups. The DTx group demonstrated higher adherence, with no reported adverse events. ACESO-APP demonstrated feasibility but achieved a suboptimal completion rate. These preliminary findings support large-scale trials and further optimization of HEP using the ACESO-APP in children with CMT.