{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T10:24:31Z","timestamp":1790677471920,"version":"4.1.0"},"reference-count":46,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Res Protoc"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Wearable devices enable continuous measurement of physical activity, sedentary behavior, sleep, and heart rate under free-living conditions. However, most validation studies rely on small, homogeneous samples; are conducted under laboratory conditions; or lack gold standard ground-truth measurements, limiting the generalizability and accuracy of derived metrics. There is a pressing need for open-access, large-scale, free-living validation datasets that include multisensor data from diverse body locations and participant demographics to aid in model development.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>The Oxford Wearable ECG, Activity, Circadian Rhythm, and Sleep Validation Study (OxWEARS) aims to (1) validate accelerometer-based measurement of physical behaviors across 5 body sites against annotated camera data; (2) validate measurements of sleep and sleep staging from 5 different body sites against polysomnography; (3) validate wrist-worn photoplethysmography heart rate measurements against chest-worn electrocardiogram; and (4) generate a comprehensive, annotated, and anonymized dataset for open-access research use.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This cross-sectional study will recruit approximately 160 adults (aged \u226540 years) stratified by age, sex, and BMI from the Oxford BioBank. Over 3 days and 4 nights, participants will wear sensors on the wrists, chest, hip, thigh, and ankle. Ground-truth measures will be obtained from a chest electrocardiogram patch for heart rate, a first-person camera for activity annotation, an ankle-worn accelerometer for step count, and at-home polysomnography for sleep. An under-mattress sensor will collect measures of sleep, respiration rate, and bedtime, and a subjective sleep diary will also be obtained. Signals from different wear locations will be compared against the ground truth using precision, recall,\n                      <jats:italic>F<\/jats:italic>\n                      <jats:sub>1<\/jats:sub>\n                      -score, \u03ba, and agreement metrics.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Recruitment commenced in November 2024, with 15 participants enrolled by May 2025. Overall, 50% of eligible adults contacted were happy to consent to the study, with excellent compliance with the protocol observed to date. Data collection is ongoing and expected to conclude in 2026, with the final annotated dataset made publicly available as soon as possible thereafter.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The OxWEARS study will generate an openly accessible dataset containing more than 10,000 annotated hours from a stratified sample of adults. This will directly support scalable, generalizable human activity recognition efforts, while also enabling robust development and benchmarking of wearable-derived health metrics.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/78779","type":"journal-article","created":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T22:51:16Z","timestamp":1767048676000},"page":"e78779-e78779","source":"Crossref","is-referenced-by-count":1,"title":["Generation of a Free-Living Ground-Truth Validation Dataset for Wearable Measures of Physical Activity, Sedentary Behavior, Sleep, and Heart Rate in Adults (OxWEARS): Protocol for a Cross-Sectional Study"],"prefix":"10.2196","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4503-0479","authenticated-orcid":false,"given":"Benjamin D","family":"Maylor","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3603-8062","authenticated-orcid":false,"given":"Scott R","family":"Small","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8270-4655","authenticated-orcid":false,"given":"Tatiana","family":"Plekhanova","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4493-0426","authenticated-orcid":false,"given":"Laura","family":"Brocklebank","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8897-558X","authenticated-orcid":false,"given":"Stefan","family":"van Duijvenboden","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1683-0477","authenticated-orcid":false,"given":"Rachel","family":"Sharman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9290-9734","authenticated-orcid":false,"given":"Elizabeth A","family":"Hill","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2751-1770","authenticated-orcid":false,"given":"Fredrik","family":"Karpe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9581-5311","authenticated-orcid":false,"given":"Simon D","family":"Kyle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1840-0451","authenticated-orcid":false,"given":"Aiden","family":"Doherty","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2025,12,29]]},"reference":[{"issue":"1","key":"R1","doi-asserted-by":"publisher","DOI":"10.1186\/1479-5868-5-56","article-title":"A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review","volume":"5","author":"Prince","journal-title":"Int J Behav Nutr Phys Act"},{"issue":"1","key":"R2","doi-asserted-by":"publisher","DOI":"10.1186\/s12966-020-00938-3","article-title":"A comparison of self-reported and device measured sedentary behaviour in adults: a systematic review and meta-analysis","volume":"17","author":"Prince","journal-title":"Int J Behav Nutr Phys Act"},{"issue":"2","key":"R3","doi-asserted-by":"publisher","DOI":"10.1111\/jsr.13802","article-title":"How many hours do you sleep? A comparison of subjective and objective sleep duration measures in a sample of insomnia patients and good sleepers","volume":"32","author":"Benz","journal-title":"J Sleep Res"},{"issue":"6","key":"R4","doi-asserted-by":"publisher","DOI":"10.2196\/36377","article-title":"Quality evaluation of free-living validation studies for the assessment of 24-hour physical behavior in adults via wearables: systematic review","volume":"10","author":"Giurgiu","journal-title":"JMIR Mhealth Uhealth"},{"key":"R5","doi-asserted-by":"publisher","DOI":"10.1016\/j.jshs.2024.101006","article-title":"The wearable landscape: issues pertaining to the validation of the measurement of 24-h physical activity, sedentary, and sleep behavior assessment","volume":"14","author":"Giurgiu","journal-title":"J Sport Health Sci"},{"issue":"1","key":"R6","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-26174-1","article-title":"Statistical machine learning of sleep and physical activity phenotypes from sensor data in 96,220 UK Biobank participants","volume":"8","author":"Willetts","journal-title":"Sci Rep"},{"issue":"1","key":"R7","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-024-03960-3","article-title":"CAPTURE-24: a large dataset of wrist-worn activity tracker data collected in the wild for human activity recognition","volume":"11","author":"Chan","journal-title":"Sci Data"},{"issue":"2","key":"R8","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0169649","article-title":"Large scale population assessment of physical activity using wrist worn accelerometers: the UK Biobank study","volume":"12","author":"Doherty","journal-title":"PLoS ONE"},{"issue":"18","key":"R9","doi-asserted-by":"publisher","first-page":"1008","DOI":"10.1136\/bjsports-2021-104050","article-title":"Reallocation of time between device-measured movement behaviours and risk of incident cardiovascular disease","volume":"56","author":"Walmsley","journal-title":"Br J Sports Med"},{"issue":"1","key":"R10","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1177\/0081175019884591","article-title":"Testing self-report time-use diaries against objective instruments in real time","volume":"50","author":"Gershuny","journal-title":"Sociol Methodol"},{"issue":"10","key":"R11","doi-asserted-by":"publisher","first-page":"1926","DOI":"10.1249\/MSS.0000000000003497","article-title":"NHANES 2011-2014: objective physical activity is the strongest predictor of all-cause mortality","volume":"56","author":"Leroux","journal-title":"Med Sci Sports Exerc"},{"issue":"1","key":"R12","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1249\/mss.0b013e31815a51b3","article-title":"Physical activity in the United States measured by accelerometer","volume":"40","author":"Troiano","journal-title":"Med Sci Sports Exerc"},{"issue":"1","key":"R13","doi-asserted-by":"publisher","first-page":"e80","DOI":"10.1093\/ije\/dyac095","article-title":"Cohort profile update: the HUNT study, Norway","volume":"52","author":"\u00c5svold","journal-title":"Int J Epidemiol"},{"key":"R14","doi-asserted-by":"publisher","DOI":"10.14283\/jarlife.2024.14","article-title":"Sedentary behaviour and fall-related injuries in aging adults: results from the Canadian Longitudinal Study on Aging (CLSA)","volume":"13","author":"Gallibois","journal-title":"JAR Life"},{"issue":"3","key":"R15","doi-asserted-by":"publisher","first-page":"e179","DOI":"10.1093\/ije\/dyac148","article-title":"Cohort profile update: the 1970 British Cohort Study (BCS70)","volume":"52","author":"Sullivan","journal-title":"Int J Epidemiol"},{"issue":"4","key":"R16","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1249\/JES.0000000000000206","article-title":"A framework to evaluate devices that assess physical behavior","volume":"47","author":"Keadle","journal-title":"Exerc Sport Sci Rev"},{"issue":"3","key":"R17","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1016\/j.amepre.2012.11.006","article-title":"An ethical framework for automated, wearable cameras in health behavior research","volume":"44","author":"Kelly","journal-title":"Am J Prev Med"},{"issue":"1","key":"R18","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1109\/TAFFC.2022.3222524","article-title":"Ethical considerations and checklist for affective research with wearables","volume":"15","author":"Behnke","journal-title":"IEEE Trans Affective Comput"},{"issue":"1","key":"R19","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1093\/ije\/dyx132","article-title":"Cohort profile: the Oxford Biobank","volume":"47","author":"Karpe","journal-title":"Int J Epidemiol"},{"issue":"1","key":"R20","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-07743-4","article-title":"GWAS identifies 14 loci for device-measured physical activity and sleep duration","volume":"9","author":"Doherty","journal-title":"Nat Commun"},{"issue":"12","key":"R21","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0142198","article-title":"Developing a method to test the validity of 24 hour time use diaries using wearable cameras: a feasibility pilot","volume":"10","author":"Kelly","journal-title":"PLoS ONE"},{"issue":"Suppl 2","key":"R22","doi-asserted-by":"publisher","DOI":"10.1186\/s12889-019-6761-x","article-title":"A validation study of the Eurostat harmonised European time use study (HETUS) diary using wearable technology","volume":"19","author":"Harms","journal-title":"BMC Public Health"},{"key":"R23","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(13)60391-8","article-title":"Use of wearable cameras to assess population physical activity behaviours: an observational study","volume":"380","author":"Doherty","journal-title":"The Lancet"},{"key":"R24","volume":"52","author":"Klem","journal-title":"Electroencephalogr Clin Neurophysiol Suppl"},{"key":"R25","unstructured":"Troester MM . The AASM manual for the scoring of sleep and associated events: rules, terminology and technical specifications. American Academy of Sleep Medicine. 2023. URL: https:\/\/pulmo-ua.com\/wp-content\/uploads\/2021\/12\/AASM-sleep-scoring-2017.pdf [Accessed 05-05-2025]"},{"issue":"6","key":"R26","doi-asserted-by":"publisher","first-page":"1315","DOI":"10.1249\/MSS.0000000000001569","article-title":"Video-recorded validation of wearable step counters under free-living conditions","volume":"50","author":"Toth","journal-title":"Med Sci Sports Exerc"},{"issue":"6","key":"R27","doi-asserted-by":"publisher","DOI":"10.1101\/2024.09.09.24312921","article-title":"Performance evaluation of an under-mattress sleep sensor versus polysomnography in \u2265 400 nights with healthy and unhealthy sleep","volume":"34","author":"Manners","journal-title":"Health Informatics"},{"issue":"2","key":"R28","doi-asserted-by":"publisher","first-page":"287","DOI":"10.5665\/sleep.1642","article-title":"The consensus sleep diary: standardizing prospective sleep self-monitoring","volume":"35","author":"Carney","journal-title":"Sleep"},{"key":"R29","doi-asserted-by":"publisher","DOI":"10.1016\/j.trf.2019.09.015","article-title":"HeartPy: a novel heart rate algorithm for the analysis of noisy signals","volume":"66","author":"van Gent","journal-title":"Transp Res F Traffic Psychol Behav"},{"issue":"3","key":"R30","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1123\/jmpb.2022-0048","article-title":"Evaluation of within- and between-site agreement for direct observation of physical behavior across four research groups","volume":"6","author":"Keadle","journal-title":"J Meas Phys Behav"},{"issue":"1","key":"R31","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-21350-6","article-title":"Reducing annotation burden in physical activity research using vision language models","volume":"15","author":"Sch\u00f6nfeldt","journal-title":"Sci Rep"},{"issue":"1","key":"R32","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-024-01062-3","article-title":"Self-supervised learning for human activity recognition using 700,000 person-days of wearable data","volume":"7","author":"Yuan","journal-title":"NPJ Digit Med"},{"issue":"5","key":"R33","doi-asserted-by":"publisher","DOI":"10.1101\/2023.08.01.23293507","article-title":"A systematic review of the performance of actigraphy in measuring sleep stages","volume":"33","author":"Yuan","journal-title":"Health Informatics"},{"issue":"1","key":"R34","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-024-01065-0","article-title":"Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality","volume":"7","author":"Yuan","journal-title":"NPJ Digit Med"},{"issue":"10","key":"R35","doi-asserted-by":"publisher","first-page":"1945","DOI":"10.1249\/MSS.0000000000003478","article-title":"Self-supervised machine learning to characterize step counts from wrist-worn accelerometers in the UK Biobank","volume":"56","author":"Small","journal-title":"Med Sci Sports Exerc"},{"key":"R36","unstructured":"Cohen J . Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Erlbaum Associates; 1988. ISBN: 9780805802832"},{"issue":"8476","key":"R37","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1016\/S0140-6736(86)90837-8","article-title":"Statistical methods for assessing agreement between two methods of clinical measurement","volume":"327","author":"Martin Bland","journal-title":"Lancet"},{"issue":"3","key":"R38","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0193971","article-title":"Using Bluetooth proximity sensing to determine where office workers spend time at work","volume":"13","author":"Clark","journal-title":"PLoS ONE"},{"issue":"1","key":"R39","doi-asserted-by":"publisher","DOI":"10.1186\/s12966-022-01388-9","article-title":"The impact of selected methodological factors on data collection outcomes in observational studies of device-measured physical behaviour in adults: a systematic review","volume":"20","author":"Pulsford","journal-title":"Int J Behav Nutr Phys Act"},{"key":"R40","unstructured":"UK biobank cardiac monitoring project. UK Biobank Limited. URL: https:\/\/www.ukbiobank.ac.uk\/taking-part\/participant-opportunities\/imaging-project\/heart-monitor [Accessed 11-04-2025]"},{"issue":"1","key":"R41","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-62330-6","article-title":"Measuring gait parameters from a single chest-worn accelerometer in healthy individuals: a validation study","volume":"14","author":"Camerlingo","journal-title":"Sci Rep"},{"issue":"1","key":"R42","doi-asserted-by":"publisher","DOI":"10.1186\/s13102-024-00991-6","article-title":"Classifying physical activity levels using mean amplitude deviation in adults using a chest worn accelerometer: validation of the Vivalink ECG patch","volume":"16","author":"Luckhurst","journal-title":"BMC Sports Sci Med Rehabil"},{"issue":"1","key":"R43","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1093\/epirev\/mxab004","article-title":"Assessment of physical activity in adults using wrist accelerometers","volume":"43","author":"Liu","journal-title":"Epidemiol Rev"},{"issue":"2","key":"R44","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1080\/00222895.2017.1306481","article-title":"Influence of accelerometer placement and\/or heart rate on energy expenditure prediction during uphill exercise","volume":"50","author":"Kuo","journal-title":"J Mot Behav"},{"issue":"12","key":"R45","doi-asserted-by":"publisher","DOI":"10.1093\/sleep\/zsz180","article-title":"Sleep stage prediction with raw acceleration and photoplethysmography heart rate data derived from a consumer wearable device","volume":"42","author":"Walch","journal-title":"Sleep"},{"issue":"10","key":"R46","doi-asserted-by":"publisher","first-page":"1351","DOI":"10.1093\/jamia\/ocy064","article-title":"The National Sleep Research Resource: towards a sleep data commons","volume":"25","author":"Zhang","journal-title":"J Am Med Inform Assoc"}],"container-title":["JMIR Research Protocols"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.researchprotocols.org\/2025\/1\/e78779","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T18:11:31Z","timestamp":1782843091000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.researchprotocols.org\/2025\/1\/e78779"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,29]]},"references-count":46,"URL":"https:\/\/doi.org\/10.2196\/78779","relation":{},"ISSN":["1929-0748"],"issn-type":[{"value":"1929-0748","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,29]]},"article-number":"v14i1e78779"}}