ArticleFrontiers in physiology2022
Using Wearable Inertial Sensors to Estimate Clinical Scores of Upper Limb Movement Quality in Stroke.
Article in Frontiers in physiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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.
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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
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Remotely Assessing Motor Function and Activity of the Upper Extremity After Stroke: A Systematic Review of Validity and Clinical Utility of Tele-Assessments.Clinical rehabilitation · 2024Pooled it
- White Matter Structural Biomarkers Derived from Diffusion Tensor Imaging to Estimate Upper-Extremity Motor Function in Stroke Using Machine Learning.Brain topography · 2026Article
- Wearable Sensor Technology and Biomechanical Gait Analysis in Post-Stroke Rehabilitation: A Review with Implications for the Saudi Healthcare System.Neurosciences (Riyadh, Saudi Arabia) · 2026Review
- Digital biomarkers derived from wearable sensors in neurorehabilitation: a scoping review.Frontiers in neurology · 2026Article
- Automated EMG-Based Classification of Upper Extremity Motor Impairment Levels in Subacute Stroke.Sensors (Basel, Switzerland) · 2025Article
- Enhancing rehabilitation in stroke survivors: a deep learning approach to access upper extremity movement using accelerometry data.Frontiers in artificial intelligence · 2025Article
- Using deep learning to detect upper limb compensation in individuals post-stroke using consumer-grade webcams-A feasibility study.Frontiers in medicine · 2025Article
- Trends and Innovations in Wearable Technology for Motor Rehabilitation, Prediction, and Monitoring: A Comprehensive Review.Sensors (Basel, Switzerland) · 2024Review
- Post-stroke hand gesture recognition via one-shot transfer learning using prototypical networks.Journal of neuroengineering and rehabilitation · 2024Article
- Evaluating the Accuracy of Upper Limb Movement in the Sagittal Plane among Computer Users during the COVID-19 Pandemic.Healthcare (Basel, Switzerland) · 2024Article
- Responsiveness and construct validity of two outcome measures of bilateral upper limb function in patients with chronic stroke.Frontiers in neurology · 2024Article
- Physical activity monitoring-based interventions in geriatric patients: a scoping review on intervention components and clinical applicability.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2023Article
- Current Technology Developments Can Improve the Quality of Research and Level of Evidence for Rehabilitation Interventions: A Narrative Review.Sensors (Basel, Switzerland) · 2023Review
- Ensemble averaging for categorical variables: Validation study of imputing lost data in 24-h recorded postures of inpatients.Frontiers in physiology · 2023Article
- Article
- Classification of functional and non-functional arm use by inertial measurement units in individuals with upper limb impairment after stroke.Frontiers in physiology · 2022Article
- Global trends in wearable sensors for stroke motor rehabilitation: A bibliometric analysis.Digital healthArticle
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
Neurorehabilitation is progressively shifting from purely in-clinic treatment to therapy that is provided in both clinical and home-based settings. This transition generates a pressing need for assessments that can be performed across the entire continuum of care, a need that might be accommodated by application of wearable sensors. A first step toward ubiquitous assessments is to augment validated and well-understood standard clinical tests. This route has been pursued for the assessment of motor functioning, which in clinical research and practice is observation-based and requires specially trained personnel. In our study, 21 patients performed movement tasks of the Action Research Arm Test (ARAT), one of the most widely used clinical tests of upper limb motor functioning, while trained evaluators scored each task on pre-defined criteria. We collected data with just two wrist-worn inertial sensors to guarantee applicability across the continuum of care and used machine learning algorithms to estimate the ARAT task scores from sensor-derived features. Tasks scores were classified with approximately 80% accuracy. Linear regression between summed clinical task scores (across all tasks per patient) and estimates of sum task scores yielded a good fit (
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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.