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Objective: Using robotic technology, we examined the ability of a visually guided reaching task to assess the sensorimotor function of patients with stroke.
Methods: Ninety-one healthy participants and 52 with subacute stroke of mild to moderate severity (26 with left- and 26 with right-affected body sides) performed an unassisted reaching task using the KINARM robot. Each participant was assessed using 12 movement parameters that were grouped into 5 attributes of sensorimotor control.
Results: A number of movement parameters individually identified a large number of stroke participants as being different from 95% of the controls-most notably initial direction error, which identified 81% of left-affected patients. We also found interlimb differences in performance between the arms of those with stroke compared with controls. For example, whereas only 31% of left-affected participants showed differences in reaction time with their affected arm, 54% showed abnormal interlimb differences in reaction time. Good interrater reliability (r > 0.7) was observed for 9 of the 12 movement parameters. Finally, many stroke patients deemed impaired on the reaching task had been scored 6 or less on the arm portion of the Chedoke-McMaster Stroke Assessment Scale, but some who scored a normal 7 were also deemed impaired in reaching.
Conclusions: Robotic technology using a visually guided reaching task can provide reliable information with greater sensitivity about a patient's sensorimotor impairments following stroke than a standard clinical assessment scale.
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http://dx.doi.org/10.1177/1545968309356091 | DOI Listing |
World J Urol
September 2025
Department of Urology, Hospital Clínico San Borja Arriarán, Santiago, Chile.
Purpose: Percutaneous nephrolithotomy (PCNL) is a common technique in the surgical management of renal lithiasis, but it also represents a significant workload for surgeons. Factors such as the patient's position and the type of lithotripter used influence the physical and mental load on the surgeon. The study aimed to identify stressors related to PCNL by comparing the physical and mental workload experienced by urologists during PCNL under different patient positions and using two lithotripters.
View Article and Find Full Text PDFAfr J Prim Health Care Fam Med
August 2025
Department of Family and Emergency Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town.
Background: Mental health disorders are increasing globally. In South Africa, primary healthcare (PHC) services are tasked with mental healthcare, with limited resources. A task-sharing approach between PHC role-players has also been met with barriers, including negative attitudes towards mental health care, organisational constraints and insufficiently trained staff.
View Article and Find Full Text PDFMov Disord Clin Pract
September 2025
Neurology Unit, Neuromotor and Rehabilitation Department, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
Background: GBA1 variants are the major genetic risk factor for Parkinson's Disease (PD) and account for 5-30% of PD cases depending on the population and age at onset of the disease.
Objectives: The aim of this study was to assess whether Artificial Intelligence (AI) could predict GBA1-mutated genotype in PD (GBA1-PD). Particularly, the main objective was to identify a Machine Learning (ML) model capable of accurately providing a pre-test estimate of GBA1-mutated status, relying on the clinical and demographic variables with the highest predictive value.
PLoS One
September 2025
Symbiosis Institute of Technology, Symbiosis International University, Pune, India.
With the rapid development of industrial automation and intelligent manufacturing, defect detection of electronic products has become crucial in the production process. Traditional defect detection methods often face the problems of insufficient accuracy and inefficiency when dealing with complex backgrounds, tiny defects, and multiple defect types. To overcome these problems, this paper proposes Y-MaskNet, a multi-task joint learning framework based on YOLOv5 and Mask R-CNN, which aims to improve the accuracy and efficiency of defect detection and segmentation in electronic products.
View Article and Find Full Text PDFAging Cell
September 2025
Division of Biomedical and Life Sciences, Lancaster University, Lancaster, UK.
Almost half of pregnant women globally are currently estimated to be overweight or obese. Rates of childhood obesity are also on the rise, in part because of increased consumption of dietary saturated fats. However, the long-term effect of peri- and postnatal high fat (HF) feeding on cognitive function and neuronal expression has not yet been investigated.
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