{
  "abstract": "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. Author summary: Many people spend most of their day sitting or standing, which increases health risks. Commercial fitness trackers and existing research usually count total sitting time and measure inactivity, but few focus on how long specific postures are held uninterrupted. In this study, we systematically reviewed fourteen research articles on the monitoring of prolonged postures using wearable accelerometers. We examined sensor selection, data processing, analysis methods, and user feedback. Most research focuses on prolonged sitting. Few studies investigate prolonged standing as a separate issue. Only a few studies gave user feedback. None used real-time posture detection to trigger feedback. Our findings show that wearable sensors can monitor prolonged sitting. However, the varied methods across studies make comparison difficult. The field lacks consistent definitions of prolonged postures, detailed reporting of data preparation and analysis approaches, and further actions to turn monitoring into meaningful feedback. Inclusive research and method validation with diverse populations is needed before these tools can support posture and spinal health in daily life.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Electrical Engineering, KU Leuven, Leuven, Belgium",
    "Department of Biosystems, KU Leuven, Leuven, Belgium",
    "Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium",
    "School of Economics and Management, Beihang University, Beijing, China",
    "Department of Rehabilitation, School of Nursing and Medical Technology, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam"
  ],
  "article_type": "Research Article",
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      "name": "Meixing Liao"
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      "name": "Eva Libeert"
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      "name": "Bart Vanrumste"
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    {
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      ],
      "name": "Simon Brumagne"
    },
    {
      "name": "Zhe Chen"
    },
    {
      "name": "Jean-Marie Aerts"
    }
  ],
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  "cited_by": 0,
  "doi": "10.1371/journal.pdig.0001538",
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  "licence_label": "CC BY 4.0",
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  "pmcid": null,
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  "published": "2026-09-15",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/cdamk3bcy1vqq.ris",
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  "title": "A systematic review of prolonged posture monitoring with accelerometer-based wearable sensors",
  "title_text": "A systematic review of prolonged posture monitoring with accelerometer-based wearable sensors",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:49Z",
  "url": "https://research.draconitic.com/paper/cdamk3bcy1vqq",
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