Smartphone-based assessment of motor function in patients with Facioscapulohumeral muscular dystrophy


Topic:

Other

Poster Number: 314 T

Author(s):

Jon Street, BSc, Sheffield Teaching Hospitals / University of Sheffield, Tecla Bonci, PhD, University of Sheffield, Alexander Jakubiec, PhD, University of Sheffield, Laura Castillo, PhD, Indivi, Óscar Reyes, PhD, Indivi, Shibeshih Belachew, MD, PhD, Indivi AG, Channa Hewamadduma, MBBS, FRCP (Neuro), FRCPE, PhD, Academic Neuroscience Unit, Sheffield Teaching Hospitals NHS FT, and SITraN, Univ. of Sheffield, UK, Claudia Mazzà, PhD, Indivi

Facioscapulohumeral muscular dystrophy (FSHD) affects the face, shoulders, and upper and lower limb muscles with symptoms varying in severity and slowly progressing. Despite the increasing number of candidate therapeutics for FSHD from pre-clinical studies, heterogeneity of muscle involvement and shortage of robust FSHD biomarkers challenge the implementation of informative FSHD clinical trials. Smartphone-based assessments might augment outcomes collected during in-clinic visits by providing more frequent and objective disability assessment through data collected remotely in the daily life of patients with FSHD. Specifically, inertial sensor data from functional smartphone-based tests can be transformed through signal processing pipelines into objective numerical outcomes, called sensor-derived measures (SDMs), comprehensively quantifying the loss of ability and the response to treatment. In this study we are testing the feasibility of such an approach by instrumenting with a Smartphone seven motor tests covering the function of the upper limbs (Shoulder Range of Motion exploration) and of the lower limbs (Two-minute walking, Repeated chair-stand, Timed Up and Go, 10m walk/run, U-turn). Furthermore, we are establishing the test-retest reliability of SDMs extracted for each of these tests and evaluating their accuracy by comparing the Smartphone data to those collected from a gold-standard motion capture system. Eleven of the expected 15 participants (Age: Mean 49.4 (SD 14.2); FSHD Clinical Score: Mean 7.6 (SD 2.6)) have already completed the assessments. While the data analysis is still in progress, preliminary observations confirmed the feasibility of administering the selected tests with a Smartphone, of identifying meaningful events in the data series (e.g. isolating individual motion cycles) and of extracting meaningful SDMs (e.g. shoulder angle, trunk accelerations, turn speed) from the Smartphone data. These preliminary observations support the potential of using a Smartphone to remotely monitor treatment effects within a clinical trial setting involving patients with FSHD.