A Mechanoluminescent Elastic Resistance Band for Quantitative Resistance Training
收藏DataCite Commons2024-10-10 更新2025-04-16 收录
下载链接:
https://ieee-dataport.org/documents/mechanoluminescent-elastic-resistance-band-quantitative-resistance-training
下载链接
链接失效反馈官方服务:
资源简介:
Resistance training with elastic bands has been proven to effectively enhance muscle performance, making it an important component of strength and fitness training. However, assessing the intensity of resistance training typically requires large equipment such as isokinetic dynamometers or complex methods like muscle electromyography. These approaches are highly dependent on professional assistance and cannot be conducted synchronously during training. To solve these problems, we propose a mechanoluminescent elastic resistance band, which just utilizes one monocular vision system to record the deformation of mechanoluminescent elastic resistance, and calculate the force and work people do during training. We first selected a cubic fitting method for the stress-strain mapping relationship taking fitting performance and computing complexity into consideration. The coefficient of determination (R2) and root mean square error (RMSE) of fitting performances were more than 0.999 and about 0.05, respectively. Second, we designed one monocular vision system to detect the dimensions of elastic resistance band which acquired improvements (from 3.66% to 13.92%) to binocular vision system. Third, the mechanoluminescent elastic resistance could generate light when in dynamic stretching or releasing, which could compensate the band detection in different light intensity environment with more than 86.67% detection accuracy. Finally, this quantitative resistance training evaluation system was applied to evaluate different movements, and it could output the force and work trainers did to the band during training. Our study has provided a convenient and effective method for evaluating trainers' resistance training, which is a new way of quantitative resistance training evaluation
提供机构:
IEEE DataPort
创建时间:
2024-10-10



