Longitudinal At-Home Monitoring of Motor Function in ALS

Topic:

Clinical Trials

Poster Number: M194

Author(s):

Ashkan Vaziri, PhD, Biosensics LLC, Ram kinker Mishra, PhD, BioSensics LLC, Newton, MA, USA, Adonay Sastre Nunes, PhD, BioSensics LLC, Newton, MA, USA, Jose Casado, MS, BioSensics LLC, Newton, MA, USA, Zachary Simmons, MD, Department of Neurology, Penn State College of Medicine, PA, USA, Andrew Geronimo, MD, Department of Neurology, Penn State College of Medicine, PA, USA

Background:
Multifaceted assessments of neurological symptoms and disease progression may facilitate patient care and enhance clinical trial readiness. Our study aims to develop a wearable-based remote monitoring system tailored for use in individuals with amyotrophic lateral sclerosis (ALS). This platform leverages wearable sensors and digital evaluations to track changes in physical activity, fine motor skills, patient-reported outcomes (PRO), and speech.
Methods:
Participants diagnosed with ALS were recruited and followed up to 12 months. Each participant visited the clinical at baseline and then every 3 months. After each clinical visits, they continuously wore a PAMSys™ pendant and two PAMSys ULM™ wrist sensors to measure daily physical activity and hand goal-directed movements. A study-specific version of BioDigit Home tablets were employed for assessments of digital speech, handwriting, and pattern-tracing abilities at bi-weekly intervals. Repeated measure correlation and Linear mixed model analyses were used to analyze the longitudinal data.
Results:
Currently, 12 individuals with ALS have participated in the study with a total of 34 visits (range 1-5 visits per participant). Sensor-extracted features of physical activity exhibited significant correlations with the gross motor subdomain scores of ALSFRS-R (items 7-9) with r = 0.41 to 0.60, p < 0.05. Additionally, the speech metrics, such as articulatory rate and intelligibility, exhibited meaningful to moderate associations with the bulbar and respiratory subdomain scores of the ALSFRS-R (items 1-3 and 10-12, respectively). Participants displayed excellent compliance in using the solution, completing 91.9% of the speech tasks, 96.5% compliance for pendant sensor (sensors worn > 18 hours), and 88% of handwriting and pattern-tracing tasks.
Conclusions:
These pilot results demonstrate the promise and potential of multi-modal at-home monitoring for tracking ALS symptoms and mobility. Furthermore, the digitized assessments offer advantages such as objective measurement, enhanced compliance, scalability, and cost-effectiveness, all of which contribute to promoting health equity.