The purpose of this study was to assess the efficacy of a combined training program (CTP) in reducing the effects of dual tasking on the temporal parameters and kinematics of gait, as compared with single-task gait. A controlled, randomized, intervention study was performed in an intervention group and a control group. The intervention group attended three weekly CTP sessions for 24 weeks. Gait pattern was evaluated prior to the baseline intervention, at 12 weeks, and at 24 weeks (Repost). The sample was composed of 22 subjects diagnosed with multiple sclerosis with an Expanded Disability Status Scale score of 0-5.5. A total of 12 patients were allocated to the intervention group and another 10 to the control group. A three-dimensional photogrammetry scanner was connected to a selective attention system designed to present a dual-task gait condition. Dual tasking had an impact on all spatiotemporal parameters of gait, and the most remarkable effect of dual tasking was on double-support time, which increased by 9% with respect to normal walking. In contrast, dual tasking had a trivial effect on single-support time. The CTP was effective in reducing the effects of dual tasking on stride length and velocity of the center of mass after Repost of training (p < .05). The CTP reduced time in double-support phase, whereas single-support time increased after Repost of intervention. The application of the CTP had no effect on the cost of the double task after 12 weeks of intervention. It is suggested to increase the application time over Repost.
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Brief Bioinform
November 2024
School of Medicine, Institute of Biomedicine, University of Eastern Finland, Yliopistonranta 1, PO Box 1627, 70211 Kuopio, Finland.
The selection of biomarker panels in omics data, challenged by numerous molecular features and limited samples, often requires the use of machine learning methods paired with wrapper feature selection techniques, like genetic algorithms. They test various feature sets-potential biomarker solutions-to fine-tune a machine learning model's performance for supervised tasks, such as classifying cancer subtypes. This optimization process is undertaken using validation sets to evaluate and identify the most effective feature combinations.
View Article and Find Full Text PDFFront Psychol
December 2024
Laboratory of Functional Neurosciences (UR UPJV 4559), Jules Verne University of Picardie, Amiens, France.
Introduction: Numerous studies have explored the linguistic and executive processes underlying verbal fluency using association designs, which provide limited evidence. To assess the validity of our model, we aimed to refine the cognitive architecture of verbal fluency using an interference design.
Methods: A total of 487 healthy participants performed letter and semantic fluency tests under the single condition and dual conditions while concurrently performing a secondary task that interferes with speed, semantics, phonology, or flexibility.
Front Robot AI
December 2024
MSc SmartEdTech, Université Côte d'Azur, Nice, France.
Creative Problem Solving (CPS) is an important competency when using digital artifacts for educational purposes. Using a dual-process approach, this study examines the divergent thinking scores (fluidity, flexibility, and originality) and problem-solving speed in CPS of different age groups. Participants engaged in CreaCube CPS tasks with educational robotics for two consecutive instances, with performance analyzed to explore the influence of prior experience and creative intentions.
View Article and Find Full Text PDFJ 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.
No FDA-approved medications for methamphetamine (MA) use disorder (MUD) are available. Suvorexant (SUVO), a dual orexin receptor antagonist that is FDA approved for insomnia treatment, reduces MA self-administration and MA-induced reinstatement responding in preclinical studies. SUVO may also reduce MA use by targeting substance use risk factors, including insomnia, stress, cue reactivity, and craving.
View Article and Find Full Text PDFPLoS One
December 2024
Department of Life Sciences, Centre for Clinical and Cognitive Neuroscience, Brunel University London, Kingston Lane, Uxbridge, Middlesex, United Kingdom.
Multitasking (MT)-performing more than one task at a time-has become ubiquitous in everyday life. Understanding of how MT is learned could enable optimizing learning regimes for tasks and occupations that necessitate frequent MT. Previous research has distinguished between MT learning regimes in which all tasks are learned in parallel, single-task (ST) learning regimes in which all tasks are learned individually, and mixed learning regimes (Mix) in which MT and ST regimes are mixed.
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