Previously submitted to: JMIR mHealth and uHealth (no longer under consideration since Mar 12, 2021)
Date Submitted: Aug 15, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Wearable Monitoring and Predicting System for Knee Joint Fatigue Based on Curvature and Pressure Sensing
ABSTRACT
Background:
Knee injury is always a trouble for people in daily life. It not only threatens the career of an athlete but also affects a normal engineer through morning running. The injury of the knee joint is found to be directly related to the fatigue caused by excessive exercise.
Objective:
The aim of the study was to explore the use of wearable embedded devices to monitor and predict the fatigue degree of the knee joint during exercise, so as to prevent the knee joint from being injured.
Methods:
An economical embedded system with a designed acceleration-weighted curve fitting method was developed to estimate and predict the knee fatigue state. Then the warning message and recommended lasting time were sent to users to avoid excessive exercise. 24 healthy volunteers were involved in the experiments to verify the effectiveness of the system compared to human perception.
Results:
Only using human perception to prevent knee joint fatigue had a risk of failure while the designed wearable system could protect knee successfully. It was also found that the knee of female was more likely to be injured than the one of male in intense exercises and a high BMI value could influence the risk of knee injuries during sports. However, a short break in sports could significantly extend the healthy time for knee.
Conclusions:
Early warning from the specially designed embedded system can successfully help people avoid knee joint fatigue and injuries during exercises, such as running, badminton, table tennis and basketball.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.