The objectives of the present study were to test the hypothesis that the dual-tasking effect on gait variability is larger in healthy older adults than it is in healthy young adults; that this effect is larger in idiopathic elderly fallers than it is in healthy older adults; and that the dual-tasking effects on gait variability are correlated with executive function (EF). Young adults and older adults who were classified as fallers and nonfallers were studied. Gait speed, swing time, and swing time variability, a marker of fall risk, were measured during usual walking and during three different dual-tasking conditions. EF and memory were evaluated. When performing dual tasks, all three groups significantly decreased their gait speed. Dual tasking did not affect swing time variability in the young adults and in the nonfallers. Conversely, dual tasking markedly increased swing time variability in the fallers. While memory was similar in fallers and nonfallers, EF was different. The faller-specific response to dual tasking was significantly correlated with tests of EF. These findings demonstrate that dual tasking does not affect the gait variability of elderly nonfallers or young adults. In contrast, dual tasking destabilizes the gait of idiopathic elderly fallers, an effect that appears to be mediated in part by a decline in EF.
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J Addict Dis
December 2024
Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA.
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December 2024
Department of Life Sciences, Centre for Clinical and Cognitive Neuroscience, Brunel University London, Kingston Lane, Uxbridge, Middlesex, United Kingdom.
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December 2024
College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, 266590, China.
The imperative development of point-of-care diagnosis for accurate and rapid medical image segmentation, has become increasingly urgent in recent years. Although some pioneering work has applied complex modules to improve segmentation performance, resulting models are often heavy, which is not practical for the modern clinical setting of point-of-care diagnosis. To address these challenges, we propose UltraNet, a state-of-the-art lightweight model that achieves competitive performance in segmenting multiple parts of medical images with the lowest parameters and computational complexity.
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School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China.
Humanoid robots are becoming a global research focus. Due to the limitations of bipedal walking technology, mobile humanoid robots equipped with a wheeled chassis and dual arms have emerged as the most suitable configuration for performing complex tasks in factory or home environments. To address the high redundancy issue arising from the wheeled chassis and dual-arm design of mobile humanoid robots, this study proposes a whole-body coordinated motion control algorithm based on arm potential energy optimization.
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December 2024
School of Artificial Intelligence, Tongmyong University, Busan 48520, Republic of Korea.
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