ArticleSensors (Basel, Switzerland)2022
Reliability of IMU-Based Gait Assessment in Clinical Stroke Rehabilitation.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it, 59 citations in OpenAlex.
- Assessment of ambulation functions through kinematic analysis in individuals with stroke: a systematic review.European journal of physical and rehabilitation medicine · 2025Pooled it
- An open-source, externally validated neural network algorithm to recognize daily-life gait of older adults based on a lower-back sensor.Medical & biological engineering & computing · 2026Article
- A deep learning pipeline for detecting vestibular schwannoma patients with unilateral vestibular loss based on kinematic data.Scientific reports · 2025Article
- Comparing the Informative Value of 2-Minute Segments of the 6-Minute Walk Test: Insights into a Prospective Study on Parkinson's Disease.Sensors (Basel, Switzerland) · 2025Article
- Gait Event Detection and Gait Parameter Estimation from a Single Waist-Worn IMU Sensor.Sensors (Basel, Switzerland) · 2025Article
- Classification of Hemiplegic Gait and Mimicked Hemiplegic Gait: A Treadmill Gait Analysis Study in Stroke Patients and Healthy Individuals.Bioengineering (Basel, Switzerland) · 2025Article
- The added value of sensor-based tests in explaining the variance in walking and ADL independency after stroke: An exploratory study.Clinical rehabilitation · 2025Article
- A High-Fidelity mmWave Radar Dataset for Privacy-Sensitive Human Pose Estimation.Bioengineering (Basel, Switzerland) · 2025Article
- Augmented Feedback in Post-Stroke Gait Rehabilitation Derived from Sensor-Based Gait Reports-A Longitudinal Case Series.Sensors (Basel, Switzerland) · 2025Article
- Reliability of Muscle Oxygen Saturation for Evaluating Exercise Intensity and Knee Joint Load Indicators.Journal of functional morphology and kinesiology · 2025Article
- Monitoring of child-specific activities in ambulatory children with and without developmental disabilities.BMC pediatrics · 2025Article
- Predicting community walking after stroke.Frontiers in stroke · 2025Article
- Validity of Valor Inertial Measurement Unit for Upper and Lower Extremity Joint Angles.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
- Optimizing Rare Disease Gait Classification through Data Balancing and Generative AI: Insights from Hereditary Cerebellar Ataxia.Sensors (Basel, Switzerland) · 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
- Characterization of Walking in Mild Parkinson's Disease: Reliability, Validity and Discriminant Ability of the Six-Minute Walk Test Instrumented with a Single Inertial Sensor.Sensors (Basel, Switzerland) · 2024Article
- Exploring unsupervised feature extraction of IMU-based gait data in stroke rehabilitation using a variational autoencoder.PloS one · 2024Article
- Minimal detectable change in inertial measurement unit-based trunk acceleration indices during gait in inpatients with subacute stroke.Scientific reports · 2023Article
- Automatic Body Segment and Side Recognition of an Inertial Measurement Unit Sensor during Gait.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundGait is often impaired in people after stroke, restricting personal independence and affecting quality of life. During stroke rehabilitation, walking capacity is conventionally assessed by measuring walking distance and speed. Gait features, such as asymmetry and variability, are not routinely determined, but may provide more specific insights into the patient's walking capacity. Inertial measurement units offer a feasible and promising tool to determine these gait features.
objectiveWe examined the test-retest reliability of inertial measurement units-based gait features measured in a two-minute walking assessment in people after stroke and while in clinical rehabilitation.
methodThirty-one people after stroke performed two assessments with a test-retest interval of 24 h. Each assessment consisted of a two-minute walking test on a 14-m walking path. Participants were equipped with three inertial measurement units, placed at both feet and at the low back. In total, 166 gait features were calculated for each assessment, consisting of spatio-temporal (56), frequency (26), complexity (63), and asymmetry (14) features. The reliability was determined using the intraclass correlation coefficient. Additionally, the minimal detectable change and the relative minimal detectable change were computed.
resultsOverall, 107 gait features had good-excellent reliability, consisting of 50 spatio-temporal, 8 frequency, 36 complexity, and 13 symmetry features. The relative minimal detectable change of these features ranged between 0.5 and 1.5 standard deviations.
conclusionGait can reliably be assessed in people after stroke in clinical stroke rehabilitation using three inertial measurement units.
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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.