ArticleAnnals of clinical and translational neurology2024
Tracking amyotrophic lateral sclerosis disease progression using passively collected smartphone sensor data.
Article in Annals of clinical and translational neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Use of Digital Devices to Monitor Physical Behavior in Motor Neuron Disease: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Comparison of Consumer Smartwatch and Research-Grade Accelerometer-Derived Step Counts in Amyotrophic Lateral Sclerosis.Muscle & nerve · 2026Observational
- Digital Phenotyping in Health Research: Scoping Review of Methods, Gaps, and Opportunities.Journal of medical Internet research · 2026Article
- Digital Remote Assessment of Motor and Speech Changes in Amyotrophic Lateral Sclerosis: Longitudinal Observational Study.JMIR formative research · 2026Observational
- Low-Burden Detection of Clinical Worsening in Body Dysmorphic Disorder Using Smartphone Sensor and Demographic Data.Behavior therapy · 2026Observational
- Short prescribed exercises can quantify upper limb functioning in neurodegenerative disease.Journal of neuroengineering and rehabilitation · 2026Article
- Analytical and clinical validation of step counting method in people living with amyotrophic lateral sclerosis.Scientific reports · 2025Article
- Design considerations for C9orf72 disease prevention trials.Brain : a journal of neurology · 2025Review
- Towards the Operationalization of Health Technology Sustainability Assessment and the Early Eco Design of the Internet of Medical Things.Sensors (Basel, Switzerland) · 2025Article
- Exploratory analysis of smartphone-based step counts as a digital biomarker for survival in ALS patients.Frontiers in digital health · 2025Article
- Free-living monitoring of ALS progression in upper limbs using wearable accelerometers.Journal of neuroengineering and rehabilitation · 2024Observational
- Wearable Sensor-Based Assessments for Remotely Screening Early-Stage Parkinson's Disease.Sensors (Basel, Switzerland) · 2024Observational
- Examining Associations Between Smartphone Use and Clinical Severity in Frontotemporal Dementia: Proof-of-Concept Study.JMIR aging · 2024Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
backgroundPassively collected smartphone sensor data provide an opportunity to study physical activity and mobility unobtrusively over long periods of time and may enable disease monitoring in people with amyotrophic lateral sclerosis (PALS).
methodsWe enrolled 63 PALS who used Beiwe mobile application that collected their smartphone accelerometer and GPS data and administered the self-entry ALS Functional Rating Scale-Revised (ALSFRS-RSE) survey. We identified individual steps from accelerometer data and used the Activity Index to summarize activity at the minute level. Walking, Activity Index, and GPS outcomes were then aggregated into day-level measures. We used linear mixed effect models (LMMs) to estimate baseline and monthly change for ALSFRS-RSE scores (total score, subscores Q1-3, Q4-6, Q7-9, Q10-12) and smartphone sensor data measures, as well as the associations between them.
findingsThe analytic sample (N = 45) was 64.4% male with a mean age of 60.1 years. The mean observation period was 292.3 days. The ALSFRS-RSE total score baseline mean was 35.8 and had a monthly rate of decline of -0.48 (p-value <0.001). We observed statistically significant change over time and association with ALSFRS-RSE total score for four smartphone sensor data-derived measures: walking cadence from top 1 min and log-transformed step count, step count from top 1 min, and Activity Index from top 1 min.
interpretationSmartphone sensors can unobtrusively track physical changes in PALS, potentially aiding disease monitoring and future research.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.