Temporal parameters are crucial for understanding running performance, especially in elite sports environments. Traditional measurement methods are often labor-intensive and not suitable for field conditions. This study seeks to provide greater clarity in parameter estimation using a single device by comparing it to the gold standard. Specifically, this study aims to investigate how the temporal parameters and vertical stiffness (K) of running stride exerted by IMU sensors are related to the parameters of the smart insole for outdoor acquisition. Ten healthy male subjects performed four 60-meter high-speed runs. Data were collected using the WIMU PRO™ device and smart insoles. Contact time (CT) and flight time (FT) were identified, and K was calculated using Morin's method. Statistical analyses assessed data normality, correlations, and reliability. WIMU measured longer CT, with differences ranging from 26.3% to 38.5%, and shorter FT, with differences ranging from 27.3% to 54.5%, compared to smart insoles, across different running speeds. K values were lower with WIMU, with differences ranging from 23.96% to 45.01% depending on the running activity, indicating significant differences ( < 0.001). Using these results, a multiple linear regression model was developed for the correction of WIMU's K values, improving the accuracy. The improved accuracy of K measurements has significant implications for athletic performance. It provides sports scientists with a more reliable metric to estimate player fatigue, potentially leading to more effective training regimens and injury prevention strategies. This advancement is particularly valuable in team sports settings, where easy-to-use and accurate biomechanical assessments of multiple athletes are essential.
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http://dx.doi.org/10.3390/s24248087 | DOI Listing |
Sensors (Basel)
December 2024
Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, 40127 Bologna, Italy.
Temporal parameters are crucial for understanding running performance, especially in elite sports environments. Traditional measurement methods are often labor-intensive and not suitable for field conditions. This study seeks to provide greater clarity in parameter estimation using a single device by comparing it to the gold standard.
View Article and Find Full Text PDFBioengineering (Basel)
December 2024
Chair of Biomechanics, Faculty of Engineering Science, University of Bayreuth, D-95440 Bayreuth, Germany.
Although diabetic polyneuropathy (DPN) has a very high prevalence among people with diabetes, gait analysis using cyclograms is very limited, and cyclogram research, in general, is limited to standard measures available in software packages. In this study, cyclograms (movements of the centre of pressure, COP, on and between the plantar surfaces) of diabetics and healthy individuals recorded with a smart insole were compared in terms of geometry and balance index, BI. The latter was calculated as the summed product of standard deviations of cyclogram markers, i.
View Article and Find Full Text PDFYonsei Med J
January 2025
Department of Rehabilitation Medicine, Rehabilitation Institute of Neuromuscular Disease, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
Purpose: This study aims to evaluate a new method for the five times sit to stand test (FTSST), crucial for addressing frailty in an aging population. It utilizes a smart insole for plantar pressure analysis and a marker-less motion capture device for head height analysis.
Materials And Methods: Thirty-five participants aged 50 years or older underwent FTSST assessment using three methods: manual measurement with a stopwatch (FTSST-M), plantar pressure analysis with smart insoles (FTSST-P), and head height analysis with a marker-less motion capture device (FTSST-H).
Med Pharm Rep
October 2024
1st Surgery Clinic, Faculty of Medicine, "Vasile Goldis" West University, Arad, Romania.
Diabetic foot ulcers represent a serious and costly complication of diabetes, with significant morbidity and mortality. The purpose of this study was to explore advancements in Artificial Intelligence, and wearable technologies for the prevention and management of diabetic foot ulcers. Key findings indicate that Artificial Intelligence-driven predictive analytics can identify early signs of diabetic foot ulcers, enabling timely interventions.
View Article and Find Full Text PDFCureus
August 2024
Incubation Center, Shriram institute for Industrial Research, Gurugram, IND.
Background Gait analysis has evolved through many years of research. Many methods are used to analyze the gait of a subject. Recent times have shown a high demand for wearable sensor-based insoles integrated with smartphone-based devices used for gait analysis due to ease of use.
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