ArticleJournal for the measurement of physical behaviour2019
An Open-Source Monitor-Independent Movement Summary for Accelerometer Data Processing.
Article in Journal for the measurement of physical behaviour, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 papers.
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Who cites it
97 citing papers in PubMed, 213 citations in OpenAlex.
- Device-Based Physical Activity Surveillance in Asian American Children and Adolescents: Participation and Activity Patterns in NHANES 2011-2014.Children (Basel, Switzerland) · 2026Article
- Wearable sensor-derived continuous physical activity dimensions and all-cause mortality in adults with diabetes and hypertension: insights from two population-based accelerometry cohorts.Acta diabetologica · 2026Article
- Variable Selection for Fixed and Random Effects in Multilevel Functional Mixed Effects Models.Statistics in medicine · 2026Article
- Association between circadian rest-activity rhythm and meal timing: NHANES 2013-2014.Sleep health · 2026Article
- Sedentary behavior type matters: compositional analysis of 24-hour movement behaviors and cognitive function in older adults.Journal of activity, sedentary and sleep behaviors · 2026Article
- The Association Between Non-exercise Activity Thermogenesis and Diabetes Status in U.S. Adults: NHANES 2013-2014.American journal of lifestyle medicine · 2026Article
- Do adults with cardiovascular disease risk show meaningful reactivity to physical activity measurement? Coordinated analysis across six studies.British journal of health psychology · 2026Article
- Universal approach to actigraphic sleep/wake scoring, verified against 5 classic algorithms on 3 datasets.Scientific reports · 2026Article
- Sex- and Ethnic Differences in the Cross-sectional Association Between Sleep Regularity and Obesity Among US Adults, NHANES 2011-2014.Journal of biological rhythms · 2026Article
- Cleaning and pre-processing of actigraphy data for physical activity and sleep research: a scoping review.Physiological measurement · 2026Article
- The Concurrent Validity of the ActiGraph LEAP Compared to the ActiGraph GT9X Link for Measuring Physical Activity.Journal for the measurement of physical behaviour · 2026Article
- Reducing bias and enhancing equity in AI-enabled precision nutrition: addressing measurement error across wearables, multiomics, and dietary data.Frontiers in digital health · 2026Review
- Head kinematic analysis in idiopathic scoliosis: a case-control study.Journal of orthopaedic surgery and research · 2025Article
- Impact of accelerometer epoch summary measure on associations between physical activity and all-cause mortality in Whitehall II and UK Biobank.Scientific reports · 2025Article
- A Context-Assisted, Semi-Automated Activity Recall Interface Allowing Uncertainty.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2025Article
- Exploring person-centred sleep and rest-activity cycle dynamics over 6 months.Journal of sleep research · 2025Article
- The Modular Actigraphy Platform: A Data Science Solution for Processing High-Resolution Time Series Sensor Data for Sleep and Physical Activity Assessment.medRxiv : the preprint server for health sciences · 2025Article
- Analytical and clinical validation of step counting method in people living with amyotrophic lateral sclerosis.Scientific reports · 2025Article
- Visualising accelerometer-based 24/7 human movement behaviour data: an umbrella review and framework development from the LABDA project.Journal of activity, sedentary and sleep behaviors · 2025Review
- Sleep regularity and duration are associated with depression severity in a nationally representative United States sample.Neurobiology of sleep and circadian rhythms · 2025Article
37 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
backgroundPhysical behavior researchers using motion sensors often use acceleration summaries to visualize, clean, and interpret data. Such output is dependent on device specifications (e.g., dynamic range, sampling rate) and/or are proprietary, which invalidate cross-study comparison of findings when using different devices. This limits flexibility in selecting devices to measure physical activity, sedentary behavior, and sleep. PURPOSE: Develop an open-source, universal acceleration summary metric that accounts for discrepancies in raw data among research and consumer devices.
methodsWe used signal processing techniques to generate a Monitor-Independent Movement Summary unit (MIMS-unit) optimized to capture normal human motion. Methodological steps included raw signal harmonization to eliminate inter-device variability (e.g., dynamic g-range, sampling rate), bandpass filtering (0.2-5.0 Hz) to eliminate non-human movement, and signal aggregation to reduce data to simplify visualization and summarization. We examined the consistency of MIMS-units using orbital shaker testing on eight accelerometers with varying dynamic range (±2 to ±8 g) and sampling rates (20-100 Hz), and human data (N = 60) from an ActiGraph GT9X.
resultsDuring shaker testing, MIMS-units yielded lower between-device coefficient of variations than proprietary ActiGraph and ENMO acceleration summaries. Unlike the widely used ActiGraph activity counts, MIMS-units were sensitive in detecting subtle wrist movements during sedentary behaviors.
conclusionsOpen-source MIMS-units may provide a means to summarize high-resolution raw data in a device-independent manner, thereby increasing standardization of data cleaning and analytical procedures to estimate selected attributes of physical behavior across studies.
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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.