ArticleBMC musculoskeletal disorders2023
Quantitative assessment of thenar to evaluate hand function after stroke by Bayes discriminant.
Article in BMC musculoskeletal disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Predictive Value of circ_0020850 for Functional Outcomes After Acute Ischemic Stroke in Hospitalized Convalescent Patients.Biochemical genetics · 2026Article
- From Qualitative to Quantitative Functional Assessment in Stroke Rehabilitation with a Focus on Ultrasound Role.Biomedicines · 2025Review
- Review
- Design of upper limb muscle strength assessment system based on surface electromyography signals and joint motion.Frontiers in neurology · 2024Article
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundThe incidence rate of stroke or cerebrovascular accidents ranks first in China. More than 85% of stroke patients have residual upper limb motor dysfunction, especially hand dysfunction. Normalizing the rehabilitation evaluation process and standard quantitative evaluation method is a complex and key point in rehabilitation therapy. The study aimed to establish a function model based on the Bayes discriminant by measuring the thenar stiffness with shear wave elastography (SWE) to quantitatively evaluate the hand motor function of hemiplegic patients after stroke.
methodsThis study collected 60 patients diagnosed with hemiplegia after stroke from October 2021 to October 2022. Therapists used the Brunnstrom assessment (BA)scale to divide the patients into the stage. All the patients underwent the measurement of SWE examination of abductor pollicis brevis (APB), opponens pollicis (OP), flexor pollicis long tendon (FPLT), and flexor pollicis brevis (FPB) by two sonographers. The SWE change rate of four parts of the thenar area was calculated prospectively with the non-hemiplegic side as the reference, the function equation was established by the Bayes discriminant method, and the evaluation model was fitted according to the acquired training set data. Lastly, the model was verified by self-validation, cross-validation, and external data validation methods. The classification performance was evaluated regarding the area under the ROC curve (AUC), sensitivity, and specificity.
resultsThe median SWE values of the hemiplegic side of patients were lower than those of the non-hemiplegic side. According to the BA stage and SWE
conclusionThis Bayes discriminant model built by measuring thenar stiffness was of diagnostic value and can provide an objective basis for evaluating clinical rehabilitation.
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