ArticleScientific reports2025
IMU-Based quantitative assessment of stroke from gait.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- [Personalized lower-limb gait assessment method based on musculoskeletal modeling and machine learning].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026Article
- Article
- Freezing of Gait in Parkinson's Disease: A Scoping Review on the Path Towards Real-Time Therapies.Sensors (Basel, Switzerland) · 2026Article
- Smartphone video-based knee extension moments during chair rise relate to MRI measures of muscle function.medRxiv : the preprint server for health sciences · 2026Article
- Smart assistive technologies for neurodisorders: A review on AI, IoT, and wearable systems for enhanced patient care.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Review
- Reproducible candidate kinematic-electromyographic waveform markers of post-stroke gait from public multimodal waveform exports.Frontiers in medical technology · 2026Article
- Development and preliminary validation of a multimodal instrument for spasticity quantification using a composite index: A pilot study.PloS one · 2026Article
- Gait Event Detection From Thigh Segment Kinematics in Children With Crouch Gait.IEEE journal of translational engineering in health and medicine · 2026Article
- IMU-based segmental root mean square analysis of gait in individuals with cerebellar ataxia: a pilot cross-sectional study.Scientific reports · 2025Article
- Augmented Feedback in Post-Stroke Gait Rehabilitation Derived from Sensor-Based Gait Reports-A Longitudinal Case Series.Sensors (Basel, Switzerland) · 2025Article
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Authors and funding
7 authors.
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Abstract
Gait impairment, which is commonly observed in stroke survivors, underscores the imperative of rehabilitating walking function. Wearable inertial measurement units (IMUs) can capture gait parameters in stroke patients, becoming a promising tool for objective and quantifiable gait assessment. Optimal sensor placement for stroke assessment that involves optimal combinations of features (kinematics) is required to improve stroke assessment accuracy while reducing the number of sensors to achieve a convenient IMU scheme for both clinical and home assessment; however, previous studies lack comprehensive discussions on the optimal sensor placement and features. To obtain an optimal sensor placement for stroke assessment, this study investigated the impact of IMU placement on stroke assessment based on gait data and clinical scores of 16 stroke patients. Stepwise regression was performed to select the kinematics most correlated with stroke assessment (lower limb part of Fugl-Meyer assessment). Sensors at different locations were combined into 28 sensor groups and their stroke assessment was compared. First, the reduced number of gait features does not significantly impact the stroke assessment. Second, the selected gait parameters by stepwise regression are found all from sensors at the hip and bilateral thighs. Last, a three-sensor scheme-sensors at the hip and bilateral thighs was suggested, which achieved a high accuracy with an adjusted R
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