ArticleSensors (Basel, Switzerland)2021
Digital Biomarkers of Physical Frailty and Frailty Phenotypes Using Sensor-Based Physical Activity and Machine Learning.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06032091 (Digital Phenotyping for Changes in Activity at the End of Life in People With Dementia), which is not on this map. Cited by 30 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Digital Phenotyping for Changes in Activity at the End of Life in People With Dementia: an Observational Trial Based on Sensing Technology
Who cites it
30 citing papers in PubMed.
- AI-Based Measurement Tools for Intrinsic Capacity in Older Adults: Scoping Review.Journal of medical Internet research · 2026Article
- Development and validation of machine-learning diagnostic models for identifying frailty in older adults with tuberculosis: a multicentre observational study protocol.BMC pulmonary medicine · 2026Observational
- Database for Prevalence and Determinants of Frailty in the Elderly with Quantifying Functional Mobility.Scientific data · 2026Article
- Using Indoor Movement Complexity in Smart Homes to Detect Frailty in Older Adults: Multiple-Methods Case Series Study.JMIR aging · 2026Article
- Application of Digital Twin Technology to Enhance Chronic Diseases Management: A Systematic Review.International journal of telemedicine and applications · 2026Review
- Identifying minimal risk factors for adolescent suicidal ideation and suicide attempts: A machine learning-optimized approach.PloS one · 2026Article
- Assessment of Frailty in Community-Dwelling Older Adults Using Smartphone-Based Digital Lifelogging: A Multi-Center, Prospective Observational Study.Sensors (Basel, Switzerland) · 2025Observational
- High-Accuracy Indoor Positioning and Smart Home Technologies for Assessing and Monitoring Frailty in Older Adults.Sensors (Basel, Switzerland) · 2025Article
- Article
- Development and multi-cohort validation of a machine learning-based simplified frailty assessment tool for clinical risk prediction.Journal of translational medicine · 2025Article
- SmartBoot: Real-Time Monitoring of Patient Activity via Remote Edge Computing Technologies.Sensors (Basel, Switzerland) · 2025Article
- Retrospective Frailty Assessment in Older Adults Using Inertial Measurement Unit-Based Deep Learning on Gait Spectrograms.Sensors (Basel, Switzerland) · 2025Article
- Predicting cognitive frailty in community-dwelling older adults: a machine learning approach based on multidomain risk factors.Scientific reports · 2025Article
- Article
- Advancing fall risk prediction in older adults with cognitive frailty: A machine learning approach using 2-year clinical data.PloS one · 2025Article
- Modeling and validation in Parkinson's disease patients with frailty.Frontiers in neuroscience · 2025Article
- Identifying and Estimating Frailty Phenotypes by Vocal Biomarkers: Cross-Sectional Study.Journal of medical Internet research · 2024Article
- Remotely monitored physical activity from older people with cardiac devices associates with physical functioning.BMC geriatrics · 2024Article
- The Application of Digital Frailty Screening to Triage Nonhealing and Complex Wounds.Journal of diabetes science and technology · 2024Article
- Harnessing physical activity monitoring and digital biomarkers of frailty from pendant based wearables to predict chemotherapy resilience in veterans with cancer.Scientific reports · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Remote monitoring of physical frailty is important to personalize care for slowing down the frailty process and/or for the healthy recovery of older adults following acute or chronic stressors. Taking the Fried frailty criteria as a reference to determine physical frailty and frailty phenotypes (slowness, weakness, exhaustion, inactivity), this study aimed to explore the benefit of machine learning to determine the least number of digital biomarkers of physical frailty measurable from a pendant sensor during activities of daily living. Two hundred and fifty-nine older adults were classified into robust or pre-frail/frail groups based on the physical frailty assessments by the Fried frailty criteria. All participants wore a pendant sensor at the sternum level for 48 h. Of seventeen sensor-derived features extracted from a pendant sensor, fourteen significant features were used for machine learning based on logistic regression modeling and a recursive feature elimination technique incorporating bootstrapping. The combination of percentage time standing, percentage time walking, walking cadence, and longest walking bout were identified as optimal digital biomarkers of physical frailty and frailty phenotypes. These findings suggest that a combination of sensor-measured exhaustion, inactivity, and speed have potential to screen and monitor people for physical frailty and frailty phenotypes.
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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 OpenQuestion graph.