ArticleSensors (Basel, Switzerland)2020
Principal Characteristics of Affected and Unaffected Side Trunk Movement and Gait Event Parameters during Hemiplegic Stroke Gait with IMU Sensor.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
- The Relation Between Hemiparetic Gait Patterns and Walking Function After Stroke, as Measured with Wearable Sensors.Annals of biomedical engineering · 2025Observational
- Development of an IMU-Based Post-Stroke Gait Data Acquisition and Analysis System for the Gait Assessment and Intervention Tool.Sensors (Basel, Switzerland) · 2025Article
- IMU-Based quantitative assessment of stroke from gait.Scientific reports · 2025Article
- Characteristics of Gait Event and Muscle Activation Parameters of the Lower Limb on the Affected Side in Patients With Hemiplegia After Stroke: A Pilot Study.Archives of rehabilitation research and clinical translation · 2023Article
- Effect of core stabilization exercises in addition to conventional therapy in improving trunk mobility, function, ambulation and quality of life in stroke patients: a randomized controlled trial.BMC sports science, medicine & rehabilitation · 2022Article
- Wearable Sensors Improve Prediction of Post-Stroke Walking Function Following Inpatient Rehabilitation.IEEE journal of translational engineering in health and medicine · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
This study describe the characteristics of hemiplegic stroke gait with principal component analysis (PCA) of trunk movement (TM) and gait event (GE) parameters by the inertial measurement unit (IMU) sensors: (1) Background: This process can determine dominant variables through multivariate examination to identify the affected, unaffected, and healthy lower-limb sides; (2) Methods: The study monitored forty patients with stroke and twenty-eight healthy individuals comprising the control group for comparison. The IMU sensors were attached to each subject while performing a 6 m walking test. Sixteen variables extracted from the measured data were divided into 7 GE and 9 TM variables explaining pelvis tilt, oblique, and rotation. (3) Results: The tilt range variables of the trunk movement on the affected and unaffected sides were lower than those of the healthy side; this showed between-group differences in various GE variables. For the healthy and affected sides, 80% of variances were explained with 2 or 3 PCs involving only a few dominant variables; and (4) Conclusions: The difference between each side leg should be considered during the development of a diagnosis method. This research can be utilized to develop functional assessment tools for personalized treatment and to design appropriate training protocols.
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Registered trials
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