Accepted for/Published in: JMIR Formative Research
Date Submitted: Jul 28, 2022
Date Accepted: Feb 7, 2023
Smartphone and wearables sensors for the estimation of Facioscapulohumeral Muscular Dystrophy (FSHD) disease severity: A cross-sectional study
ABSTRACT
Background:
Estimation of the clinical severity of Facioscapulohumeral Muscular Dystrophy (FSHD) using smartphone and remote monitoring sensor data
Objective:
Facioscapulohumeral muscular dystrophy (FSHD) is a progressive neuromuscular disease. The slow and variable disease progression of FSHD makes the development of new treatments highly dependent on validated biomarkers that can quantify disease progression and response to drug interventions. The objective of this study was to build a tool that estimates FSHD clinical severity based on behavioral features captured using smartphone and remote sensor data.
Methods:
38 genetically confirmed FSHD patients were enrolled in this study. The FSHD Clinical Score and the Timed Up-And-Go (TUG) test were used to assess FSHD symptom severity at the first and last day of the trial. The remote sensor data were collected using an Android smartphone, Withings Steel HR+, Body+ and BPM Connect+ for 6 continuous weeks. We created two single-task regression models that estimated the FSHD Clinical Score and TUG separately. In addition, we built one multi-task regression model that estimated the two clinical assessments simultaneously. Further, we assessed how an increasingly incremental time windows affected the model performance.
Results:
The single-task regression models achieved an R2 of 0.57 and 0.59 when estimating FSHD Clinical Score and TUG, respectively. The multi-task model achieved an R2 of 0.74 and therefore outperformed the single-task models in estimating clinical severity. We found that using an increasing time window (starting from day 1 to day 14) for the FSHD Clinical Score, TUG, and multi-task estimation yielded an average R2 of 0.76, 0.65, and 0.79 respectively.
Conclusions:
We demonstrated that smartphone and remote sensor data could be used to estimate FSHD clinical severity and therefore complement the assessment of FSHD outside the clinic. Longitudinal follow-up studies should be conducted to further validate the reliability and validity of the multi-task model as a tool to monitor disease progression over a longer period. Clinical Trial: NL69288.056.19
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