Background: Dual-task training using one walking and one cognitive task is effective in improving post-stroke motor functions.
Objective: We aimed to investigate the effectiveness of dual-task training using various cognitive tasks for the assessment of attention, executive function, and motor function in stroke patients.
Methods: This was a single-center, randomized trial involving 30 stroke patients who were divided into a dual-task (test) group (n = 15) using different cognitive tests, and a conventional occupational therapy (control) group (n = 15). In both groups, interventions were conducted 18 times, at 30 minutes per session, 3 sessions per week, for 6 weeks. Primary outcome measures were the Trail Making Test A&B, the Digit Span Test (DST) Forward and Backward, and the Stroop (ST) Color and Word test. Secondary outcome measures were the Fugl-Meyer Assessment, the Modified Functional Reach Test, and the Berg Balance Scale. Each test was applied pre-and post- intervention.
Results: Post-intervention, the dual-task group showed a significantly stronger effect than the occupational therapy group in the DST-Forward (p = 0.04), DST-Backward (p = 0.001), ST-Color (p = 0.023), and Berg Balance Scale (p = 0.009) assessments.
Conclusions: Dual-task training using various cognitive tasks had a greater positive effect than conventional occupational therapy on auditory attention, memory span, executive function, and balance.
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http://dx.doi.org/10.3233/NRE-182563 | DOI Listing |
Sci Rep
January 2025
Department of ECE, Kallam Haranadhareddy Institute of Technology, Guntur, Andhra Pradesh, India.
Cognitive load stimulates neural activity, essential for understanding the brain's response to stress-inducing stimuli or mental strain. This study examines the feasibility of evaluating cognitive load by extracting, selection, and classifying features from electroencephalogram (EEG) signals. We employed robust local mean decomposition (R-LMD) to decompose EEG data from each channel, recorded over a four-second period, into five modes.
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January 2025
Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, 1151 Richmond Street, North London, ON, N6A 5C1, Canada.
The dual task cost of gait (DTC) is an accessible and cost-effective test that can help identify individuals with cognitive decline and dementia. However, its neural substrate has not been widely described. This study aims to investigate the neural substrate of the high DTC in older adults across the spectrum of cognitive decline.
View Article and Find Full Text PDFNeurosci Biobehav Rev
January 2025
Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA; Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany. Electronic address:
Understanding how the brain distinguishes emotional from neutral scenes is crucial for advancing brain-computer interfaces, enabling real-time emotion detection for faster, more effective responses, and improving treatments for emotional disorders like depression and anxiety. However, inconsistent research findings have arisen from differences in study settings, such as variations in the time windows, brain regions, and emotion categories examined across studies. This review sought to compile the existing literature on the timing at which the adult brain differentiates basic affective from neutral scenes in less than one second, as previous studies have consistently shown that the brain can begin recognizing emotions within just a few milliseconds.
View Article and Find Full Text PDFAccid Anal Prev
January 2025
Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India. Electronic address:
Pedestrians use visual cues (i.e., gaze) to communicate with the other road users, and visual attention towards the surrounding environment is essential to be situationally aware and avoid oncoming conflicts.
View Article and Find Full Text PDFActa Psychol (Amst)
January 2025
Department of English Language, College of Arts, King Faisal University, Al Ahsa, Saudi Arabia.
This study investigates the combined impact of artificial intelligence (AI) tools and Uncertain Motivation (UM) strategies on the argumentative writing performance of Saudi EFL learners, using the Toulmin Model. Sixty Saudi EFL students participated in four writing tasks, with results demonstrating significant improvements in essay quality, particularly in clarity, structure, and depth. AI tools provided real-time feedback, enhancing students' ability to refine claims, data, backing, and counterarguments.
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