ArticleNPJ digital medicine2023
A "one-size-fits-most" walking recognition method for smartphones, smartwatches, and wearable accelerometers.
Article in NPJ digital medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
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Who cites it
26 citing papers in PubMed.
- HEART-Watch: A multimodal physiological dataset from a Google Pixel Watch across different physical states.PLOS digital health · 2026Article
- An Information-Driven Approach for the Early Health Technology Sustainability Assessment and the Frugal Design of the Internet of Medical Things: Exploratory Study of Wearable Activity Monitoring Devices.JMIR mHealth and uHealth · 2026Article
- Wearable-Derived Data for Patient Frailty: Extending Hospital Frailty Risk Score While Confronting Bias and Inequities.Journal of general internal medicine · 2026Article
- Time-stratified daily walking speed measurement via smartphone and its predictive utility for mild cognitive impairment.Scientific reports · 2026Article
- Recognition of Gait Alterations Induced by Alcohol-Impairment Simulation Goggles Using Smartphone Accelerometer Signals.Sensors (Basel, Switzerland) · 2026Article
- Assessment of Dog-Leash Pulling Force and the Impact of Dog-Walking on Gait Kinematics.Annals of biomedical engineering · 2026Article
- Low-Burden Detection of Clinical Worsening in Body Dysmorphic Disorder Using Smartphone Sensor and Demographic Data.Behavior therapy · 2026Observational
- Validation of Inertial Sensor-Based Step Detection Algorithms for Edge Device Deployment.Sensors (Basel, Switzerland) · 2026Article
- Short prescribed exercises can quantify upper limb functioning in neurodegenerative disease.Journal of neuroengineering and rehabilitation · 2026Article
- An in-home engagement and usability study of GeRI: an open-source platform for remote symptom assessment and wearable activity monitoring in men with prostate cancer.Frontiers in digital health · 2026Article
- Analytical and clinical validation of step counting method in people living with amyotrophic lateral sclerosis.Scientific reports · 2025Article
- Designing a Gait Recognition Algorithm for Older Adults Using Mobility Aids: Prospective Cohort Study.JMIR formative research · 2025Article
- Article
- Harnessing Geospatial Artificial Intelligence (GeoAI) for Environmental Epidemiology: A Narrative Review.Current environmental health reports · 2025Review
- Measuring Psychological Well-Being and Behaviors Using Smartphone-Based Digital Phenotyping: An Intensive Longitudinal Observational mHealth Pilot Study Embedded in a Prospective Cohort of Women.JMIR mHealth and uHealth · 2025Observational
- Predicting the strength of next-day negative emotion states in body dysmorphic disorder using passive smartphone data: An intensive longitudinal assessment study.Internet interventions · 2025Article
- Comparing Step-Counting Algorithms for High-Resolution Wrist Accelerometry Data in Older Adults in the ARIC Study.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025Article
- Improved running gait parameter estimation from single foot-mounted IMU data based on refined event detection.Frontiers in bioengineering and biotechnology · 2025Article
- Using a Quality-Controlled Dataset From ViSi Mobile Monitoring for Analyzing Posture Patterns of Hospitalized Patients: Retrospective Observational Study.JMIR mHealth and uHealth · 2024Observational
- Measuring Environmental and Behavioral Drivers of Chronic Diseases Using Smartphone-Based Digital Phenotyping: Intensive Longitudinal Observational mHealth Substudy Embedded in 2 Prospective Cohorts of Adults.JMIR public health and surveillance · 2024Observational
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The ubiquity of personal digital devices offers unprecedented opportunities to study human behavior. Current state-of-the-art methods quantify physical activity using "activity counts," a measure which overlooks specific types of physical activities. We propose a walking recognition method for sub-second tri-axial accelerometer data, in which activity classification is based on the inherent features of walking: intensity, periodicity, and duration. We validate our method against 20 publicly available, annotated datasets on walking activity data collected at various body locations (thigh, waist, chest, arm, wrist). We demonstrate that our method can estimate walking periods with high sensitivity and specificity: average sensitivity ranged between 0.92 and 0.97 across various body locations, and average specificity for common daily activities was typically above 0.95. We also assess the method's algorithmic fairness to demographic and anthropometric variables and measurement contexts (body location, environment). Finally, we release our method as open-source software in Python and MATLAB.
Identifiers
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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 OpenQuestion graph.