{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T09:29:11Z","timestamp":1790069351782,"version":"4.0.1"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T00:00:00Z","timestamp":1721174400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T00:00:00Z","timestamp":1721174400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Deutsche Sporthochschule K\u00f6ln (DSHS)"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Behav Nutr Phys Act"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>The more accurate we can assess human physical behaviour in free-living conditions the better we can understand its relationship with health and wellbeing. Thigh-worn accelerometry can be used to identify basic activity types as well as different postures with high accuracy. User-friendly software without the need for specialized programming may support the adoption of this method. This study aims to evaluate the classification accuracy of two novel no-code classification methods, namely SENS motion and ActiPASS.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>A sample of 38 healthy adults (30.8\u2009\u00b1\u20099.6 years; 53% female) wore the SENS motion accelerometer (12.5\u00a0Hz; \u00b14\u00a0g) on their thigh during various physical activities. Participants completed standardized activities with varying intensities in the laboratory. Activities included walking, running, cycling, sitting, standing, and lying down. Subsequently, participants performed unrestricted free-living activities outside of the laboratory while being video-recorded with a chest-mounted camera. Videos were annotated using a predefined labelling scheme and annotations served as a reference for the free-living condition. Classification output from the SENS motion software and ActiPASS software was compared to reference labels.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>A total of 63.6\u00a0h of activity data were analysed. We observed a high level of agreement between the two classification algorithms and their respective references in both conditions. In the free-living condition, Cohen\u2019s kappa coefficients were 0.86 for SENS and 0.92 for ActiPASS. The mean balanced accuracy ranged from 0.81 (cycling) to 0.99 (running) for SENS and from 0.92 (walking) to 0.99 (sedentary) for ActiPASS across all activity types.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>The study shows that two available no-code classification methods can be used to accurately identify basic physical activity types and postures. Our results highlight the accuracy of both methods based on relatively low sampling frequency data. The classification methods showed differences in performance, with lower sensitivity observed in free-living cycling (SENS) and slow treadmill walking (ActiPASS). Both methods use different sets of activity classes with varying definitions, which may explain the observed differences. Our results support the use of the SENS motion system and both no-code classification methods.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12966-024-01627-1","type":"journal-article","created":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T10:01:59Z","timestamp":1721210519000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Thigh-worn accelerometry: a comparative study of two no-code classification methods for identifying physical activity types"],"prefix":"10.1186","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4299-4739","authenticated-orcid":false,"given":"Claas","family":"Lendt","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Theresa","family":"Braun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bianca","family":"Biallas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ingo","family":"Frob\u00f6se","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter J.","family":"Johansson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,7,17]]},"reference":[{"key":"1627_CR1","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1038\/s41569-021-00547-y","volume":"18","author":"DW Dunstan","year":"2021","unstructured":"Dunstan DW, Dogra S, Carter SE, Owen N. Sit less and move more for cardiovascular health: emerging insights and opportunities. Nat Rev Cardiol. 2021;18:637\u201348.","journal-title":"Nat Rev Cardiol"},{"key":"1627_CR2","doi-asserted-by":"publisher","first-page":"S197","DOI":"10.1139\/apnm-2020-0272","volume":"45","author":"TJ Saunders","year":"2020","unstructured":"Saunders TJ, McIsaac T, Douillette K, Gaulton N, Hunter S, Rhodes RE, et al. Sedentary behaviour and health in adults: an overview of systematic reviews. Appl Physiol Nutr Metab. 2020;45:S197\u2013217.","journal-title":"Appl Physiol Nutr Metab"},{"key":"1627_CR3","doi-asserted-by":"publisher","first-page":"e000874","DOI":"10.1136\/bmjsem-2020-000874","volume":"6","author":"ML Stevens","year":"2020","unstructured":"Stevens ML, Gupta N, Inan Eroglu E, Crowley PJ, Eroglu B, Bauman A, et al. Thigh-worn accelerometry for measuring movement and posture across the 24-hour cycle: a scoping review and expert statement. BMJ Open Sport Exerc Med. 2020;6:e000874.","journal-title":"BMJ Open Sport Exerc Med"},{"key":"1627_CR4","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1136\/bjsports-2019-100786","volume":"54","author":"E Stamatakis","year":"2020","unstructured":"Stamatakis E, Koster A, Hamer M, Rangul V, Lee I-M, Bauman AE, et al. Emerging collaborative research platforms for the next generation of physical activity, sleep and exercise medicine guidelines: the prospective physical activity, sitting, and sleep consortium (ProPASS). Br J Sports Med. 2020;54:435\u20137.","journal-title":"Br J Sports Med"},{"key":"1627_CR5","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1186\/s12966-019-0835-0","volume":"16","author":"P Crowley","year":"2019","unstructured":"Crowley P, Skotte J, Stamatakis E, Hamer M, Aadahl M, Stevens ML, et al. Comparison of physical behavior estimates from three different thigh-worn accelerometers brands: a proof-of-concept for the prospective physical activity, sitting, and sleep consortium (ProPASS). Int J Behav Nutr Phys Act. 2019;16:65.","journal-title":"Int J Behav Nutr Phys Act"},{"key":"1627_CR6","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.1136\/bjsports-2014-093546","volume":"48","author":"RP Troiano","year":"2014","unstructured":"Troiano RP, McClain JJ, Brychta RJ, Chen KY. Evolution of accelerometer methods for physical activity research. Br J Sports Med. 2014;48:1019\u201323.","journal-title":"Br J Sports Med"},{"key":"1627_CR7","doi-asserted-by":"publisher","first-page":"e80","DOI":"10.1093\/ije\/dyac095","volume":"52","author":"BO \u00c5svold","year":"2023","unstructured":"\u00c5svold BO, Langhammer A, Rehn TA, Kjelvik G, Gr\u00f8ntvedt TV, S\u00f8rgjerd EP, et al. Cohort profile update: the HUNT study, Norway. Int J Epidemiol. 2023;52:e91\u2013e80.","journal-title":"Int J Epidemiol"},{"key":"1627_CR8","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1123\/jpah.2011-0347","volume":"11","author":"J Skotte","year":"2014","unstructured":"Skotte J, Korsh\u00f8j M, Kristiansen J, Hanisch C, Holtermann A. Detection of physical activity types using triaxial accelerometers. J Phys Act Health. 2014;11:76\u201384.","journal-title":"J Phys Act Health"},{"key":"1627_CR9","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1123\/jmpb.2021-0015","volume":"5","author":"K Bach","year":"2022","unstructured":"Bach K, Kongsvold A, B\u00e5rdstu H, Bardal EM, Kj\u00e6rnli HS, Herland S, et al. A machine learning classifier for detection of physical activity types and postures during free-living. J Meas Phys Behav. 2022;5:24\u201331.","journal-title":"J Meas Phys Behav"},{"key":"1627_CR10","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1080\/00140139.2014.998724","volume":"58","author":"I Stemland","year":"2015","unstructured":"Stemland I, Ingebrigtsen J, Christiansen CS, Jensen BR, Hanisch C, Skotte J, et al. Validity of the Acti4 method for detection of physical activity types in free-living settings: comparison with video analysis. Ergonomics. 2015;58:953\u201365.","journal-title":"Ergonomics"},{"key":"1627_CR11","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1249\/MSS.0000000000002107","volume":"52","author":"A Narayanan","year":"2020","unstructured":"Narayanan A, Stewart T, Mackay L. A dual-accelerometer system for detecting human movement in a free-living environment. Med Sci Sports Exerc. 2020;52:252\u20138.","journal-title":"Med Sci Sports Exerc"},{"key":"1627_CR12","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1123\/jmpb.2022-0024","volume":"5","author":"TL Petersen","year":"2022","unstructured":"Petersen TL, Br\u00f8nd JC, Benfeldt E, Jepsen R. Integrity and performance of four tape solutions for mounting Accelerometry devices: Lolland-Falster health study. J Meas Phys Behav. 2022;5:224\u201332.","journal-title":"J Meas Phys Behav"},{"key":"1627_CR13","doi-asserted-by":"publisher","first-page":"e35697","DOI":"10.2196\/35697","volume":"11","author":"P Crowley","year":"2022","unstructured":"Crowley P, Ikeda E, Islam SMS, Kildedal R, Schade Jacobsen S, Roslyng Larsen J, et al. The surveillance of physical activity, sedentary behavior, and sleep: protocol for the development and feasibility evaluation of a novel measurement system. JMIR Res Protoc. 2022;11:e35697.","journal-title":"JMIR Res Protoc"},{"key":"1627_CR14","doi-asserted-by":"publisher","first-page":"e001286","DOI":"10.1136\/bmjsem-2021-001286","volume":"8","author":"BM Albrecht","year":"2022","unstructured":"Albrecht BM, Fla\u00dfkamp FT, Koster A, Eskofier BM, Bammann K. Cross-sectional survey on researchers\u2019 experience in using accelerometers in health-related studies. BMJ Open Sport Exerc Med. 2022;8:e001286.","journal-title":"BMJ Open Sport Exerc Med"},{"key":"1627_CR15","unstructured":"Hettiarachchi P, Johansson P, ActiPASS. Zenodo; 2023 [Accessed 30 Aug 2023]. https:\/\/zenodo.org\/record\/7701098."},{"key":"1627_CR16","unstructured":"Egh\u00f8j M, Rossen M\u00f8ller S, Kildedal R, Rasmussen M, Brandt Petersen M, Gupta N, et al. Fysisk Aktivitet, stillesiddende adf\u00e6rd og s\u00f8vn - resultater fra monitorering med accelerometre i danskernes sundhed 2023. Statens Institut for Folkesundhed; 2024."},{"key":"1627_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2018\/6596278","volume":"2018","author":"C Bartholdy","year":"2018","unstructured":"Bartholdy C, Gudbergsen H, Bliddal H, Kj\u00e6rgaard M, Lykkegaard KL, Henriksen M. Reliability and construct validity of the SENS motion\u00ae activity measurement system as a tool to detect sedentary behaviour in patients with knee osteoarthritis. Arthritis. 2018;2018:9\u20131.","journal-title":"Arthritis"},{"key":"1627_CR18","doi-asserted-by":"crossref","unstructured":"Pedersen BS, Kristensen MT, Josefsen CO, Lykkegaard KL, J\u00f8nsson LR, Pedersen MM. Validation of two activity monitors in slow and fast walking hospitalized patients. Rehabil Res Pract. 2022;2022:9230081.","DOI":"10.1155\/2022\/9230081"},{"key":"1627_CR19","doi-asserted-by":"crossref","unstructured":"Milther C, Winther L, Stahlhut M, Curtis DJ, Aadahl M, Kristensen MT, et al. Validation of an accelerometer system for measuring physical activity and sedentary behavior in healthy children and adolescents. Eur J Pediatr. 2023;182:3647\u20133639.","DOI":"10.1007\/s00431-023-05014-z"},{"key":"1627_CR20","first-page":"338","volume":"17","author":"S Thomas","year":"1992","unstructured":"Thomas S, Reading J, Shephard RJ. Revision of the physical activity readiness questionnaire (PAR-Q). Can J Sport Sci. 1992;17:338\u201345.","journal-title":"Can J Sport Sci"},{"key":"1627_CR21","unstructured":"R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. 2023. Available from: https:\/\/www.r-project.org."},{"key":"1627_CR22","unstructured":"Chang W, Cheng J, Allaire JJ, Sievert C, Schloerke B, Xie Y, et al. Shiny: web application framework for R. 2023. https:\/\/CRAN.R-project.org\/package=shiny."},{"key":"1627_CR23","doi-asserted-by":"publisher","first-page":"738","DOI":"10.1152\/japplphysiol.00421.2014","volume":"117","author":"VT Van Hees","year":"2014","unstructured":"Van Hees VT, Fang Z, Langford J, Assah F, Mohammad A, Da Silva ICM, et al. Autocalibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: an evaluation on four continents. J Appl Physiol. 2014;117:738\u201344.","journal-title":"J Appl Physiol"},{"key":"1627_CR24","unstructured":"The National Research Centre for the Working Environment (NFA). Acti4. 2024. https:\/\/github.com\/motus-nfa\/Acti4. Accessed 11 Apr 2024."},{"key":"1627_CR25","unstructured":"ELAN, Nijmegen. Max Planck Institute for Psycholinguistics, The Language Archive; 2022. https:\/\/archive.mpi.nl\/tla\/elan."},{"key":"1627_CR26","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1177\/001316446002000104","volume":"20","author":"J Cohen","year":"1960","unstructured":"Cohen J. A coefficient of agreement for nominal scales. Educ Psychol Meas. 1960;20:46\u201337.","journal-title":"Educ Psychol Meas"},{"key":"1627_CR27","unstructured":"Gamer M, Lemon J, Fellows I, Signh P. irr: various coefficients of interrater reliability and agreement. 2019. https:\/\/CRAN.R-project.org\/package=irr."},{"key":"1627_CR28","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.medengphy.2014.10.003","volume":"37","author":"B Stansfield","year":"2015","unstructured":"Stansfield B, Hajarnis M, Sudarshan R. Characteristics of very slow stepping in healthy adults and validity of the activPAL3\u2122 activity monitor in detecting these steps. Med Eng Phys. 2015;37:42\u20137.","journal-title":"Med Eng Phys"},{"key":"1627_CR29","unstructured":"SENS motion. Description of activity categories. https:\/\/support.sens.dk\/hc\/en-us\/articles\/15580259064093-Description-of-activity-categories. Accessed 28 June 2024."},{"key":"1627_CR30","doi-asserted-by":"publisher","first-page":"2595","DOI":"10.1249\/MSS.0000000000001717","volume":"50","author":"T Stewart","year":"2018","unstructured":"Stewart T, Narayanan A, Hedayatrad L, Neville J, Mackay L, Duncan S. A dual-accelerometer system for classifying physical activity in children and adults. Med Sci Sports Exerc. 2018;50:2595\u2013602.","journal-title":"Med Sci Sports Exerc"},{"key":"1627_CR31","doi-asserted-by":"publisher","first-page":"742","DOI":"10.1249\/MSS.0000000000000804","volume":"48","author":"K Lyden","year":"2016","unstructured":"Lyden K, John D, Dall P, Granat MH. Differentiating sitting and lying using a thigh-worn accelerometer. Med Sci Sports Exerc. 2016;48:742\u20137.","journal-title":"Med Sci Sports Exerc"},{"key":"1627_CR32","doi-asserted-by":"publisher","first-page":"904","DOI":"10.3390\/s21030904","volume":"21","author":"P Hettiarachchi","year":"2021","unstructured":"Hettiarachchi P, Aili K, Holtermann A, Stamatakis E, Svartengren M, Palm P. Validity of a non-proprietary algorithm for identifying lying down using raw data from thigh-worn triaxial accelerometers. Sensors. 2021;21:904.","journal-title":"Sensors"},{"key":"1627_CR33","doi-asserted-by":"publisher","first-page":"587","DOI":"10.3390\/s23020587","volume":"23","author":"MW O\u2019Brien","year":"2023","unstructured":"O\u2019Brien MW, Daley WS, Schwartz BD, Shivgulam ME, Wu Y, Kimmerly DS, et al. Characterization of detailed sedentary postures using a tri-monitor activPAL configuration in free-living conditions. Sensors. 2023;23:587.","journal-title":"Sensors"},{"key":"1627_CR34","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1249\/JES.0000000000000206","volume":"47","author":"SK Keadle","year":"2019","unstructured":"Keadle SK, Lyden KA, Strath SJ, Staudenmayer JW, Freedson PS. A framework to evaluate devices that assess physical behavior. Exerc Sport Sci Rev. 2019;47:206\u201314.","journal-title":"Exerc Sport Sci Rev"},{"key":"1627_CR35","doi-asserted-by":"publisher","first-page":"1051","DOI":"10.1007\/s00125-024-06090-y","volume":"67","author":"MN Ahmadi","year":"2024","unstructured":"Ahmadi MN, Blodgett JM, Atkin AJ, Chan H-W, Del Pozo Cruz B, Suorsa K, et al. Relationship of device measured physical activity type and posture with cardiometabolic health markers: pooled dose\u2013response associations from the prospective physical activity, sitting and sleep consortium. Diabetologia. 2024;67:1051\u201365.","journal-title":"Diabetologia"}],"container-title":["International Journal of Behavioral Nutrition and Physical Activity"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12966-024-01627-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12966-024-01627-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12966-024-01627-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T10:05:51Z","timestamp":1721210751000},"score":1,"resource":{"primary":{"URL":"https:\/\/ijbnpa.biomedcentral.com\/articles\/10.1186\/s12966-024-01627-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,17]]},"references-count":35,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["1627"],"URL":"https:\/\/doi.org\/10.1186\/s12966-024-01627-1","relation":{},"ISSN":["1479-5868"],"issn-type":[{"value":"1479-5868","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,17]]},"assertion":[{"value":"12 February 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 July 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 July 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All participants provided written informed consent. Ethical approval was obtained from the Ethics Committee of the German Sport University Cologne (reference number 094\/2022).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Written consent for publication was obtained from any person whose individual data is appearing in this manuscript.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"PJJ is a project leader in the development of the non-profit, open-source ActiPASS software. All other authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"77"}}