Vibration stimulation as an exercise intervention has been studied increasingly for its potential benefits and applications in sports and rehabilitation. Vibratory exercise devices should be capable of generating highly precise and repeatable vibrations and should be capable of generating a range of vibration amplitudes and frequencies in order to provide different training protocols. Many devices used to exercise the upper body provide limited variations to exercise regimes mostly due to the fact that only vibration frequency can be controlled. The authors present an upper limb vibration exercise device with a novel actuator system and design which attempts to address these limitations. Preliminary results show that this device is capable of generating highly precise and repeatable vibrations with independent control over amplitude and frequency. Furthermore, the results also show that this solution provides a higher neuromuscular stimulation (i.e. electromyography activity) when compared with a control condition. The portability of this device is an advantage, and though in its current configuration it may not be suitable for applications requiring higher amplitude levels the technology is scalable.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5327731 | PMC |
http://dx.doi.org/10.1049/htl.2016.0069 | DOI Listing |
In unsupervised transfer learning for medical image segmentation, where existing algorithms face the challenge of error propagation due to inaccessible source domain data. In response to this scenario, source-free domain transfer algorithm with reduced style sensitivity (SFDT-RSS) is designed. SFDT-RSS initially pre-trains the source domain model by using the generalization strategy and subsequently adapts the pre-trained model to target domain without accessing source data.
View Article and Find Full Text PDFPLoS One
December 2024
Group of Atmospheric Optics (GOA-UVa), Universidad de Valladolid, Valladolid, Spain.
This work introduces CAECENET, a new system capable of automatically retrieving columnar and vertically-resolved aerosol properties running the GRASP (Generalized Retrieval of Atmosphere and Surface Properties) algorithm using sun-sky photometer (aerosol optical depth, AOD; and sky radiance measurements) and ceilometer (range corrected signal; RCS) data as input. This method, so called GRASPpac, is implemented in CAECENET, which assimilates sun-sky photometers data from CÆLIS database and ceilometer data from ICENET database (Iberian Ceilometer Network). CAECENET allows for continuous and near-real-time monitoring of both vertical and columnar aerosol properties.
View Article and Find Full Text PDFJ Chem Inf Model
December 2024
Computer-Aided Drug Design Center, Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland Baltimore, Baltimore, Maryland 21201, United States.
Drug efficacy often correlates better with dissociation kinetics than binding affinity alone. To study binding kinetics computationally, it is necessary to identify all of the possible ligand dissociation pathways. The site identification by ligand competitive saturation (SILCS) method involves the precomputation of a set of maps (FragMaps), which describe the free energy landscapes of typical chemical functionalities in and around a target protein or RNA.
View Article and Find Full Text PDFJ Med Internet Res
December 2024
Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China.
Background: Large language models (LLMs) are increasingly integrated into medical education, with transformative potential for learning and assessment. However, their performance across diverse medical exams globally has remained underexplored.
Objective: This study aims to introduce MedExamLLM, a comprehensive platform designed to systematically evaluate the performance of LLMs on medical exams worldwide.
Interdiscip Sci
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.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!