HomeSenseALS: A Mobile Sensing and Self-Monitoring System to Monitor Patients with ALS in Everyday Life

Progressive neurological conditions like Amyotrophic Lateral Sclerosis (ALS) require regular and detailed monitoring to track functional decline and support timely clinical decisions. Traditional in-clinic assessments, however, can be burdensome and infrequent, often missing daily symptom variability. Smartphones and wearables offer a promising alternative for remote data collection. We present HomeSenseALS, a smartphone-based digital phenotyping application developed for ALS patients and caregivers, using a user-centered design approach involving patients, caregivers, and clinicians. HomeSenseALS collects multimodal data, including self-reported data from the Revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R), speech and respiratory recordings, and human movement passive data. To assess its potential for tracking ALS progression, we conducted a cross-sectional in-clinic study with 27 ALS patients and a longitudinal at-home study with 11 ALS patients over 21 weeks. Self-reported ALSFRS-R scores showed a strong correlation with in-clinic assessments. High-level physical activity features, such as time spent indoors, were associated with gross motor function. Speech analysis differentiated patients with and without bulbar dysfunction and correlated with respiratory parameters. Home spirometry aligned with clinical respiratory measures. These findings support the feasibility of using HomeSenseALS for remote, multimodal monitoring of ALS progression, potentially reducing patient burden while enabling more continuous and granular tracking of functional decline.