In athletic training and research, the evaluation of sprint speed is widely used, and its accurate measurement is especially demanding. High-cost photocells are the gold-standard system for sprint time assessment, although low-cost smartphone applications can be a suitable option. This study assesses the validity and reliability of an application to measure sprint time compared to photocells. Five physically active subjects completed six sprints of 10 m and 20 m at maximal speed and a 5 m go and return sprint to evaluate the validity of the Photo Finish app (Version 2.30). To assess reliability, six trials of 5 m go and return sprints were measured by two smartphones. The validity results showed a mean bias of 0.012 s (95% CL: 0.000, 0.024) between the application and the photocells for the 10 m sprint, 0.007 s (95% CL: -0.007, 0.022) for the 20 m sprint and 0.005 s (95% CL: -0.005, 0.017) for the 5 m go and return test. The results also found R between both systems (R= 0.9863, 0.990 and 0.958) for each distance (10 m, 20 m and 5 m go and return, respectively). As for reliability, the application showed outstanding consistency between two smartphones operating simultaneously (ICC 0.999; R: 0.999). This study shows that the Photo Finish app is an accurate and reliable tool to measure sprint time with an error of 0.09 s.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11511534 | PMC |
http://dx.doi.org/10.3390/s24206719 | DOI Listing |
Alzheimers Dement
December 2024
Indiana University School of Medicine, Indianapolis, IN, USA.
Background: Screening for cognitive impairment in primary care faces challenges, including time constraints, provider apprehension, and limited diagnostic confidence. An effective initiative for improving screening must include strategies to foster behavioral change, and active provider engagement. Agile implementation science integrates findings from behavioral economics, complexity science, and network science, to address these challenges by confirming the demand to solve the problem; local solution adaptation; and the iterative 'sprints', or tests of change, that are focused on execution.
View Article and Find Full Text PDFCrit Care Resusc
December 2024
Australian and New Zealand Intensive Care - Research Centre, School of Public Health and Preventive Medicine, Monash University, Melbourne Australia.
Objective: To describe the use of and outcomes from awake prone positioning (APP) in nonintubated patients with COVID-19 in Australian intensive care units (ICUs) in comparison to those who did not receive APP, and to explore the temporal relationship between publication of APP research and changes in clinical practice.
Design: Multicentre, observational cohort study.
Setting: Seventy-eight Australian ICUs participating in SPRINT-SARI Australia.
Front Public Health
January 2025
AstraZeneca SpA, Milano Innovation District (MIND), Milano, Italy.
Background: Software as a Medical Device (SaMD) and mobile health (mHealth) applications have revolutionized the healthcare landscape in the areas of remote patient monitoring (RPM) and digital therapeutics (DTx). These technological advancements offer a range of benefits, from improved patient engagement and real-time monitoring, to evidence-based personalized treatment plans, risk prediction, and enhanced clinical outcomes.
Objective: The systematic literature review aims to provide a comprehensive overview of the status of SaMD and mHealth apps, highlight the promising results, and discuss what is the potential of these technologies for improving health outcomes.
J Alzheimers Dis
January 2025
Department of Neurology, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Background: Black adults have higher dementia risk than White adults. Whether tighter population-level blood pressure (BP) control reduces this disparity is unknown.
Objective: Estimate the impact of optimal BP treatment intensity on racial disparities in dementia.
Sensors (Basel)
December 2024
Department of Computer Engineering, Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia.
In the field of muscle fatigue models (MFMs), the prior research has demonstrated success in fitting data in specific contexts, but it falls short in addressing the diverse efforts and rapid changes in exertion typical of soccer matches. This study builds upon the existing model, aiming to enhance its applicability and robustness to dynamic demand shifts. The objective is to encapsulate the complexities of soccer dynamics with a streamlined set of parameters.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!