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In the biomechanics of striking tasks, different types of visual feedback for the upper extremities influence motor learning and control in distinct ways. Quantitative feedback (QN), which provides precise numerical data, and qualitative feedback (QL), which offers descriptive or interpretive guidance, may facilitate different aspects of motor skill acquisition. Given that ballistic motor skills, such as the badminton underhand-clear stroke, require not only rapid and coordinated movement execution but also precise control of distal joints for accuracy, the underlying feedback processing mechanisms play a crucial role in optimizing motor control. Therefore, this study aims to determine the most effective type of visual feedback for enhancing motor learning in the badminton underhand-clear stroke by examining its impact on movement efficiency and accuracy. Participants ( = 36, all male; mean age 25.1 ± 1.2 years) were recruited into three groups: QN group, QL group, and the control group. Each participant completed a pretest, post-test, and retention-test of 20 trials each for the badminton underhand-clear stroke, along with three practice sessions consisting of 50 trials each. Performance accuracy and coordination patterns were significantly improved in the QN group compared to the QL and control groups in the retention test [performance accuracy (mean radial error) = QN-control: .01, QN-QL: .01; coordination pattern (discrete relative phase) = QN-control: .001, QN-QL: .01]. Additionally, the kinematics of the wrist joint were significantly improved in the QN group compared to the QL and control group in the retention test (maximum extension angle of wrist joint = QN-control: .001, QN-QL: < .01). These findings suggest that quantitative feedback may be more effective than qualitative feedback in facilitating motor learning in a badminton striking task, particularly in terms of long-term retention of movement accuracy and coordination. By analyzing motor coordination patterns, this study provides insight into the role of different types of visual feedback in motor learning and offers practical implications for instructors aiming to optimize skill acquisition in striking tasks.
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http://dx.doi.org/10.1080/00222895.2025.2550373 | DOI Listing |
PLoS Comput Biol
September 2025
Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, United Kingdom.
Individually foraging ants use egocentric views as a dominant navigation strategy for learning and retracing routes. Evidence suggests that route retracing can be achieved by algorithms which use views as 'visual compasses', where individuals choose the heading that leads to the most familiar visual scene when compared to route memories. However, such a mechanism does not naturally lead to route approach, and alternative strategies are required to enable convergence when off-route and for correcting on-route divergence.
View Article and Find Full Text PDFSci Adv
September 2025
Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Subthalamic deep brain stimulation (STN-DBS) provides unprecedented spatiotemporal precision for the treatment of Parkinson's disease (PD), allowing for direct real-time state-specific adjustments. Inspired by findings from optogenetic stimulation in mice, we hypothesized that STN-DBS can mimic dopaminergic reinforcement of ongoing movement kinematics during stimulation. To investigate this hypothesis, we delivered DBS bursts during particularly fast and slow movements in 24 patients with PD.
View Article and Find Full Text PDFIEEE Trans Biomed Eng
September 2025
Objective: Frequent and objective assessment of ataxia severity is essential for tracking disease progression and evaluating the effectiveness of potential treatments. Wearable-based assessments have emerged as a promising solution. However, existing methods rely on inertial data features directly correlated with subjective and coarse clinician-evaluated rating scales, which serve as imperfect gold standards.
View Article and Find Full Text PDFStroke
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Brain Language Laboratory, Freie Universität Berlin, Germany (A.-T.P.J., M.R.O., A.S., F.P.).
Background: Intensive language-action therapy treats language deficits and depressive symptoms in chronic poststroke aphasia, yet the underlying neural mechanisms remain underexplored. Long-range temporal correlations (LRTCs) in blood oxygenation level-dependent signals indicate persistence in brain activity patterns and may relate to learning and levels of depression. This observational study investigates blood oxygenation level-dependent LRTC changes alongside therapy-induced language and mood improvements in perisylvian and domain-general brain areas.
View Article and Find Full Text PDFComput Methods Biomech Biomed Engin
September 2025
Institute of Radio Physics and Electronics, University of Calcutta, Kolkata, India.
Parkinson's disease (PD) is a neurodegenerative condition that impairs motor functions. Accurate and early diagnosis is essential for enhancing well-being and ensuring effective treatment. This study proposes a deep learning-based approach for PD detection using EEG signals.
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