Background:
Sporadic inclusion body myositis (IBM) results in hand and proximal leg weakness that slowly progresses to involve all muscles, leading to physical disability and loss of independence. The decline of IBM is currently assessed through in-clinic expert muscle strength examination, which is time-consuming and insensitive to change in function, has poor inter-rater variability, and only provides a snapshot of a patient’s disease. Our study aims to develop wearable-based digital health technologies for monitoring upper and lower limb function in IBM that enable frequent, at-home monitoring of motor function, and could be incorporated into future clinical trials and in routine clinical care.
Methods:
Participants diagnosed with IBM wore a PAMSys™ pendant and two PAMSys ULM™ wrist sensor (one on each wrist) for a week to measure daily physical activity and hand goal-directed movements (GDMs). Conventional, 10-point IBM Functional Rating Scale (IBMFRS) was administered to measure disease severity. Spearman correlation analysis was performed to quantify the association between sensor-derived metrics and clinical outcomes.
Results:
10 individuals with IBM (69.7 ± 7.6-year-old, 4 female) participated in the study. Sensor-derived metrics of physical activity exhibited meaningful associations with the lower extremity subdomain score of IBMFRS (sum of items 7-10) with r = -0.558 to -0.846, p < 0.05. Additionally, the GDM-related metrics exhibited moderate to high correlations with the upper extremity subdomain scale of (sum of items 2-6) with r = 0.649 to 0.775.
Conclusions:
These pilot results demonstrate the promise and potential of at-home wearable-based monitoring for tracking motor dysfunction in IBM. Furthermore, the digitized assessments offer advantages such as objective measurement, enhanced compliance, convenience, scalability, and cost-effectiveness, all of which contribute to improving clinical care and research in IBM.