P.222 Wearable inertial sensors for longitudinal follow-up of patients with amyotrophic lateral sclerosis.

Abstract

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease characterized by the loss of motor neuron leading to weakness and death often resulting from failure of the respiratory muscles. There have been numerous recent discoveries in ALS research leading to potential therapies that will need testing in clinical trials. Due to outcome measures limitations, trials, especially for neurodegenerative disorders, require large sample sizes, long durations and have a high risk for failure. Digital biomarkers collected with wearable devices could provide powerful outcome measures through an objective assessment performed in real-life. Remote continuous monitoring is an innovative method for quantifying disease progression in ALS patients providing for motor function assessment through patients' loss of ambulation. This opportunity for shorter and less burdensome clinical trials should be confirmed by further data collection. We designed a longitudinal natural history study in ALS. Participants were assessed with standard evaluations including the amyotrophic lateral sclerosis functional rating scale, six-minute walk test, Medical Research Council scores, Ashworth score, hand dynamometer, pulmonary function and cognitive tests every 3 months for 1 year. After each visit, patients were asked to wear for one month one inertial sensor at the ankle and one at the wrist for continuous assessment of motor function in real-life. These data will be compared with already acquired normative data. At the present time, 11 patients with ALS (3 females, 8 males) aged from 44 to 72 years old were included. Four patients discontinued the study due to death or permanent ventilation. Initial results suggest that upper and lower limb variables are lower in patient with ALS than in controls and show a downward trend over time. We will present longitudinal data along with correlation between change in traditional and digital outcome measures. We will show comparison between patients and controls.