ArticleScientific data2025
Multimodal sensor dataset for monitoring older adults post lower limb fractures in community settings.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Sensor-Based Technologies for the Detection of Unwanted Loneliness in Older Adults: A Systematic Review.Sensors (Basel, Switzerland) · 2026Pooled it
- Database for Prevalence and Determinants of Frailty in the Elderly with Quantifying Functional Mobility.Scientific data · 2026Article
- Effect of unaccompanied care model in postoperative care for elderly patients with lower limb fractures: factors influencing postoperative heart failure.American journal of translational research · 2026Article
- The digital intelligent precise nursing framework: theory development in health recommender system.BMC nursing · 2025Article
- Multimodal sensor dataset for monitoring older adults post lower limb fractures in community settings.Scientific data · 2025Article
- Community-based multisensory environments as preventive public health interventions for mental well-being in older adults: evidence from a large-scale study in China.Frontiers in public health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lower limb fractures (LLF) significantly impact older adults, leading to reduced mobility, prolonged recovery, and impaired independence. During recovery, older adults frequently face social isolation and functional decline, complicating rehabilitation and adversely affecting their physical and mental health. Multimodal sensor platforms that continuously collect data and analyze it using machine learning algorithms can remotely monitor this population and infer health outcomes. These platforms can also alert clinicians to individuals at risk of social isolation and functional decline. This paper presents a new publicly available multimodal sensor dataset, MAISON-LLF, collected from older adults recovering from LLF in community settings. The dataset includes data from smartphone and smartwatch sensors, motion detection sensors, sleep-tracking mattresses, and clinical questionnaires on social isolation and functional decline. The dataset was collected from ten older adults living alone at home for eight weeks each, totaling 560 days of 24-hour sensor data. For technical validation, machine learning algorithms were developed using the sensor and clinical questionnaire data, providing a foundational comparison for the research community.
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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 Socratic graph.