With the growing accessibility of computer-assisted technology, rehabilitation programs for individuals with cerebral palsy (CP) increasingly use virtual reality environments to enhance motor practice. Thus, it is important to examine whether performance improvements in the virtual environment generalize to the natural environment. To examine this issue, we had 64 individuals, 32 of which were individuals with CP and 32 typically developing individuals, practice two coincidence-timing tasks. In the more tangible button-press task, the individuals were required to 'intercept' a falling virtual object at the moment it reached the interception point by pressing a key. In the more abstract, less tangible task, they were instructed to 'intercept' the virtual object by making a hand movement in a virtual environment. The results showed that individuals with CP timed less accurate than typically developing individuals, especially for the more abstract task in the virtual environment. The individuals with CP did-as did their typically developing peers-improve coincidence timing with practice on both tasks. Importantly, however, these improvements were specific to the practice environment; there was no transfer of learning. It is concluded that the implementation of virtual environments for motor rehabilitation in individuals with CP should not be taken for granted but needs to be considered carefully.
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http://dx.doi.org/10.1016/j.ridd.2014.06.006 | DOI Listing |
BMC Med Inform Decis Mak
January 2025
Great Ormond Street Institute of Child Health, University College London, London, UK.
Introduction: Unsupervised feature learning methods inspired by natural language processing (NLP) models are capable of constructing patient-specific features from longitudinal Electronic Health Records (EHR).
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View Article and Find Full Text PDFSci Rep
January 2025
School of Information Engineering, Sanming University, Sanming, 365004, China.
Today, with the increasing use of the Internet of Things (IoT) in the world, various workflows that need to be stored and processed on the computing platforms. But this issue, causes an increase in costs for computing resources providers, and as a result, system Energy Consumption (EC) is also reduced. Therefore, this paper examines the workflow scheduling problem of IoT devices in the fog-cloud environment, where reducing the EC of the computing system and reducing the MakeSpan Time (MST) of workflows as main objectives, under the constraints of priority, deadline and reliability.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
I3A, LoUISE Research Group, University of Castilla-La Mancha, Albacete, Spain.
Background: Laparoscopic surgery training is a demanding process requiring technical and nontechnical skills. Surgical training has evolved from traditional approaches to the use of immersive digital technologies such as virtual, augmented, and mixed reality. These technologies are now integral to laparoscopic surgery training.
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
Department of Molecular Pharmacology, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, 300060, China.
Efficient virtual screening methods can expedite drug discovery and facilitate the development of innovative therapeutics. This study presents a novel transfer learning model based on network target theory, integrating deep learning techniques with diverse biological molecular networks to predict drug-disease interactions. By incorporating network techniques that leverage vast existing knowledge, the approach enables the extraction of more precise and informative drug features, resulting in the identification of 88,161 drug-disease interactions involving 7,940 drugs and 2,986 diseases.
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