2026-10-11T18:38:17Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33813973 2026-09-15T17:54:29Z category_734 category_931 portal_5 item_type_3 month_year_09_2026

<p>Extracted data items.</p> Meixing Liao (24949963) Kai Huang (3983) Eva Libeert (24949966) Bart Vanrumste (40373) Simon Brumagne (384524) Zhe Chen (196097) Jean-Marie Aerts (4434310) Biological Sciences not elsewhere classified Information Systems not elsewhere classified reviewed journal articles full conference proceedings acm digital library uninterrupted bout segmentation bout duration thresholds worn activpal devices none used real least ten minutes including data collection inclusive external validation interpretable feedback systems heterogeneous data preparation assessed using design yet current accelerometer limited specific detection prolonged posture monitoring monitoring prolonged sitting prolonged sitting specific detection dedicated bout ten databases posture measurement including web frequently used validation reporting transition detection specific tools sitting recognition sensor validation worn accelerometer user feedback trigger feedback feedback pipeline actionable feedback prolonged standing systematic review strongest performance sectional studies reproducible pipelines reference criteria prospero registration proquest central primary target level outcome jbi checklists ieee xplore health risks future research fourteen studies feasible basis <div><p>Prolonged sitting and standing are associated with health risks. Unlike generic sedentary behaviour monitoring based on energy expenditure, prolonged posture monitoring requires posture-specific detection and uninterrupted bout segmentation, yet current accelerometer-based approaches remain heterogeneous. This systematic review synthesises current practices and identifies research gaps across the sensing-to-feedback pipeline, including data collection, preparation, analysis, and user feedback. Ten databases, including Web of Science, Scopus, ProQuest Central, PubMed/MEDLINE, EMBASE, CINAHL, SPORTDiscus, IEEE Xplore, ACM Digital Library, and Engineering Village, were searched. Eligible studies monitored uninterrupted sitting or standing bouts of at least ten minutes during wake time using body-worn accelerometer-based sensors, provided sufficient methodological detail, and were published as peer-reviewed journal articles or full conference proceedings in English. From 27,334 records, fourteen studies were included. Risk of bias was assessed using design-specific tools: JBI checklists for randomised and cross-sectional studies, and WEAR-BOT for wearable-sensor validation or algorithm-development studies. Prolonged sitting was the primary target, while prolonged standing was not assessed as a dedicated bout-level outcome. Thigh-worn activPAL devices were most frequently used for posture measurement or as reference criteria. Bout duration thresholds and interruption rules varied substantially. Deep learning models reported the strongest performance for sitting recognition and transition detection. Four studies included feedback components, but none used real-time posture monitoring outcomes to trigger feedback. Substantial heterogeneity precluded quantitative synthesis, and the evidence base was concentrated in Western, office-based populations. Overall, accelerometer-based wearable sensors provide a feasible basis for monitoring prolonged sitting. Key gaps include inconsistent definitions, limited specific detection, heterogeneous data preparation and validation reporting, and a lack of translation from monitoring to actionable feedback. Future research should prioritise transparent bout definitions, reproducible pipelines, inclusive external validation, and interpretable feedback systems. PROSPERO registration: CRD42025637387.</p></div> 2026-09-15T17:54:13Z Dataset Dataset 10.1371/journal.pdig.0001538.t001 https://figshare.com/articles/dataset/_p_Extracted_data_items_p_/33813973 CC BY 4.0