ArticleJournal of neuroengineering and rehabilitation2016
Characteristics of daily life gait in fall and non fall-prone stroke survivors and controls.
Article in Journal of neuroengineering and rehabilitation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.
- Wearable Sensors in Gait Assessment for Parkinson Disease and Stroke in Real-World Environments: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Wearable airbag technology and machine learned models to mitigate falls after stroke.Journal of neuroengineering and rehabilitation · 2022Trial
- Examining the feasibility and preliminary effects of eyes-open and eyes-closed backward treadmill training on balance, mobility, and fear of falling in sub-acute stroke survivors: a pilot randomized clinical trial.Pilot and feasibility studies · 2026Article
- Association Between Lower Limb Strength Asymmetry and Gait Asymmetry: Implications for Gait Variability in Stroke Survivors.Journal of clinical medicine · 2025Article
- Predicting community walking after stroke.Frontiers in stroke · 2025Article
- Differences in Trunk Acceleration-Derived Gait Indexes in Stroke Subjects with and without Stroke-Induced Immunosuppression.Sensors (Basel, Switzerland) · 2024Article
- Effects of metronome walking on long-term attractor divergence and correlation structure of gait: a validation study in older people.Scientific reports · 2024Article
- Beyond gait speed: exploring the added value of Inertial Measurement Unit-based measurements of gait in the estimation of the walking ability in daily life.BMC neurology · 2024Article
- Comparison of sensitivity among dynamic balance measures during walking with different tasks.Royal Society open science · 2024Article
- Exploring unsupervised feature extraction of IMU-based gait data in stroke rehabilitation using a variational autoencoder.PloS one · 2024Article
- Exploring Teslasuit's Potential in Detecting Sequential Slip-Induced Kinematic Changes among Healthy Young Adults.Sensors (Basel, Switzerland) · 2023Article
- Gait Kinematics and Asymmetries Affecting Fall Risk in People with Chronic Stroke: A Retrospective Study.Biomechanics (Basel, Switzerland) · 2022Article
- Patients' perceived walking abilities, daily-life gait behavior and gait quality before and 3 months after total knee arthroplasty.Archives of orthopaedic and trauma surgery · 2022Article
- Walking orientation randomness metric (WORM) score: pilot study of a novel gait parameter to assess walking stability and discriminate fallers from non-fallers using wearable sensors.BMC musculoskeletal disorders · 2022Article
- Reliability of IMU-Based Gait Assessment in Clinical Stroke Rehabilitation.Sensors (Basel, Switzerland) · 2022Article
- Kinematic Analysis of 360° Turning in Stroke Survivors Using Wearable Motion Sensors.Sensors (Basel, Switzerland) · 2022Article
- Objectifying clinical gait assessment: using a single-point wearable sensor to quantify the spatiotemporal gait metrics of people with lumbar spinal stenosis.Journal of spine surgery (Hong Kong) · 2021Article
- Proof of Concept of Novel Visuo-Spatial-Motor Fall Prevention Training for Old People.Geriatrics (Basel, Switzerland) · 2021Article
- Machine learning in human movement biomechanics: Best practices, common pitfalls, and new opportunities.Journal of biomechanics · 2018Review
- Faller Classification in Older Adults Using Wearable Sensors Based on Turn and Straight-Walking Accelerometer-Based Features.Sensors (Basel, Switzerland) · 2017Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFalls in stroke survivors can lead to serious injuries and medical costs. Fall risk in older adults can be predicted based on gait characteristics measured in daily life. Given the different gait patterns that stroke survivors exhibit it is unclear whether a similar fall-prediction model could be used in this group. Therefore the main purpose of this study was to examine whether fall-prediction models that have been used in older adults can also be used in a population of stroke survivors, or if modifications are needed, either in the cut-off values of such models, or in the gait characteristics of interest.
methodsThis study investigated gait characteristics by assessing accelerations of the lower back measured during seven consecutive days in 31 non fall-prone stroke survivors, 25 fall-prone stroke survivors, 20 neurologically intact fall-prone older adults and 30 non fall-prone older adults. We created a binary logistic regression model to assess the ability of predicting falls for each gait characteristic. We included health status and the interaction between health status (stroke survivors versus older adults) and gait characteristic in the model.
resultsWe found four significant interactions between gait characteristics and health status. Furthermore we found another four gait characteristics that had similar predictive capacity in both stroke survivors and older adults.
conclusionThe interactions between gait characteristics and health status indicate that gait characteristics are differently associated with fall history between stroke survivors and older adults. Thus specific models are needed to predict fall risk in stroke survivors.
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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.