Abstract Details

Title Identification of Novel Smartphone-Based Digital Biomarkers to Characterize Lower and Upper Limb Motor Functions in Patients with Duchenne Muscular Dystrophy

Topic Neuromuscular and Clinical Neurophysiology (EMG)

Presentation(s) P3 - Poster Session 3 (5:30 PM-6:30 PM)

Poster/Presentation
Number 11-005

Background DMD is a severe muscular dystrophy characterized by progressive muscle atrophy and weakness. Current clinical measures have limitations (eg., inter-rater variability) and are infrequent, which could impede patient’s care. These challenges could be overcome with smartphone-based dBMKs that offer innovative approaches to track the progression of functional parameters, from the patient's home.

Objective To assess the feasibility of smartphone-based digital biomarkers (dBMKs) to objectively measure lower and upper limb motor functions in patients with Duchenne muscular dystrophy (DMD).

Design/Methods A literature review and interviews with 11 experts (neuropaediatricians, physiotherapists, occupational therapists) was performed to identify and prioritize meaningful health concepts (HCs) and candidate dBMKs. A Proof-of-Concept study was conducted at a myology institute with 2 physiotherapists simulating different degrees of disease severity (mild, moderate, severe). We then assessed the feasibility of the measurement process (sensors and algorithms) to collect and transform these dBMKs in a Timed-up-and-Go (TUG) test and upper limb motor (ULM) test.

Results Ambulation, balance and transition tasks were prioritized as main HCs to capture key motor functions. 11 candidate dBMKs derived from accelerometer and gyroscope were selected for TUG and first results confirmed feasibility with a mean absolute error (MAE) of 1.6±1s when automatically detecting transition phases. Error was severity-dependent with a MAE of 0.8s in mild, versus 2.1s in severe phenotypes. The ULM test (ability to bring the hand to mouth, head and above), was captured using camera recording and an automated keypoint detection model. Feasibility was confirmed and a larger list of dBMKs was identified to measure arm function and compensation strategies.

Conclusions These insights pave the way for a promising approach to develop a smartphone-based measurement device to collect dBMKs in people living with DMD, and may provide clinicians with objective data collected from the patient's home to support medical decisions.

Authors/Disclosures
Clarissa Gorin, Other (Ad Scientiam) PRESENTER	Dr. Gorin has received personal compensation for serving as an employee of Ad Scientiam.
Shotaro Tachibana (Hospices Civils de Lyon)	No disclosure on file
Allison Grange (I-Motion / Institut de Myologie)	No disclosure on file
Dominique Vincent-Genod (Hospices Civils de Lyon)	No disclosure on file
Adeline Allara	No disclosure on file
Mathilde Hirel	No disclosure on file
Claude Cances	No disclosure on file
Nicolas Chrestian, MD	Dr. Chrestian has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Novartis. Dr. Chrestian has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Roche. Dr. Chrestian has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Peer choice.
Loic Carment	No disclosure on file
Arthur Feyt	No disclosure on file
Cedric Gormond (AdScientiam)	No disclosure on file
Juan Luna (Ad Scientiam)	No disclosure on file
Alexandre Petitmangin	No disclosure on file
Cecile Halbert (CHU Timone enfant / service de neurologie pédiatrique)	No disclosure on file
Vincent Laugel	No disclosure on file