ArticleFrontiers in aging neuroscience2018
Improved Prediction of Falls in Community-Dwelling Older Adults Through Phase-Dependent Entropy of Daily-Life Walking.
Article in Frontiers in aging neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Beyond gait speed: a multidimensional motor signature of motoric cognitive risk syndrome identified through domain-specific anomaly detection.GeroScience · 2026Article
- Development of a Tool for Comprehensive Balance Assessment Based on Artificial Intelligence and Anomaly Detection.Life (Basel, Switzerland) · 2025Article
- A framework to automatically detect near-falls using a wearable inertial measurement cluster.Communications engineering · 2024Article
- Leveraging feature selection for enhanced fall risk prediction in elderly using gait analysis.Medical & biological engineering & computing · 2024Article
- Monitoring Age-Related Changes in Gait Complexity in the Wild with a Smartphone Accelerometer System.Sensors (Basel, Switzerland) · 2024Article
- Gait Features in Different Environments Contributing to Participation in Outdoor Activities in Old Age (GaitAge): Protocol for an Observational Cross-Sectional Study.JMIR research protocols · 2024Observational
- Biomechanical Assessment Methods Used in Chronic Stroke: A Scoping Review of Non-Linear Approaches.Sensors (Basel, Switzerland) · 2024Article
- Predictability of Fall Risk Assessments in Community-Dwelling Older Adults: A Scoping Review.Sensors (Basel, Switzerland) · 2023Article
- Systematic review of candidate prognostic factors for falling in older adults identified from motion analysis of challenging walking tasks.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2023Review
- Mobility recorded by wearable devices and gold standards: the Mobilise-D procedure for data standardization.Scientific data · 2023Article
- Nonlinear Dynamic Measures of Walking in Healthy Older Adults: A Systematic Scoping Review.Sensors (Basel, Switzerland) · 2022Article
- Gait analysis under the lens of statistical physics.Computational and structural biotechnology journal · 2022Review
- Validity and Sensitivity of an Inertial Measurement Unit-Driven Biomechanical Model of Motor Variability for Gait.Sensors (Basel, Switzerland) · 2021Article
- Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes.NPJ digital medicine · 2021Article
- Sensor-based fall risk assessment in older adults with or without cognitive impairment: a systematic review.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2021Review
- Entropy Analysis in Gait Research: Methodological Considerations and Recommendations.Annals of biomedical engineering · 2021Review
- The validation of new phase-dependent gait stability measures: a modelling approach.Royal Society open science · 2021Article
- Review
- Acceleration Gait Measures as Proxies for Motor Skill of Walking: A Narrative Review.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2021Review
- Gait Variability Using Waist- and Ankle-Worn Inertial Measurement Units in Healthy Older Adults.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
Age and age-related diseases have been suggested to decrease entropy of human gait kinematics, which is thought to make older adults more susceptible to falls. In this study we introduce a new entropy measure, called phase-dependent generalized multiscale entropy (PGME), and test whether this measure improves fall-risk prediction in community-dwelling older adults. PGME can assess phase-dependent changes in the stability of gait dynamics that result from kinematic changes in events such as heel strike and toe-off. PGME was assessed for trunk acceleration of 30 s walking epochs in a re-analysis of 1 week of daily-life activity data from the FARAO study, originally described by van Schooten et al. (2016). The re-analyzed data set contained inertial sensor data from 52 single- and 46 multiple-time prospective fallers in a 6 months follow-up period, and an equal number of non-falling controls matched by age, weight, height, gender, and the use of walking aids. The predictive ability of PGME for falls was assessed using a partial least squares regression. PGME had a superior predictive ability of falls among single-time prospective fallers when compared to the other gait features. The single-time fallers had a higher PGME (
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