基于模糊算法的人体心肺耐力训练与评估。
Training and Evaluation of Human Cardiorespiratory Endurance Based on a Fuzzy Algorithm.
机构信息
Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 80782, Taiwan.
Department of Biomedical Engineering, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
出版信息
Int J Environ Res Public Health. 2019 Jul 5;16(13):2390. doi: 10.3390/ijerph16132390.
Cardiorespiratory endurance refers to the ability of the heart and lungs to deliver oxygen to working muscles during continuous physical activity, which is an important indicator of physical health. Cardiorespiratory endurance is typically measured in the laboratory by maximum oxygen uptake (VO) which is not a practical method for real-life use. Given the relative difficulty in measuring oxygen consumption directly, we can estimate cardiorespiratory endurance on the basis of heart beat. In this paper, we proposed a fuzzy system based on the human heart rate to provide an effective cardiorespiratory endurance training program and the evaluation of cardiorespiratory endurance levels. Trainers can respond correctly with the help of a smart fitness app to obtain the desired training results and prevent undesirable events such as under-training or over-training. The fuzzy algorithm, which is built for the Android mobile phone operating system receives the resting heart rate (RHR) of the participants via Bluetooth before exercise to determine the suitable training speed mode of a treadmill for the individual. The computer-based fuzzy program takes RHR and heart rate recovery (HRR) after exercise as inputs to calculate the cardiorespiratory endurance level. The experimental results show that after 8 weeks of exercise training, the RHR decreased by an average of 11%, the HRR increased by 51.5%, and the cardiorespiratory endurance evaluation level was also improved. The proposed system can be combined with other methods for fitness instructors to design a training program that is more suitable for individuals.
心肺耐力是指心脏和肺部在持续体力活动中向工作肌肉输送氧气的能力，是身体健康的重要指标。心肺耐力通常在实验室中通过最大摄氧量（VO）来测量，但这种方法在实际生活中并不实用。由于直接测量耗氧量相对困难，我们可以根据心跳来估计心肺耐力。在本文中，我们提出了一种基于人体心率的模糊系统，为心肺耐力训练计划和心肺耐力水平评估提供了一种有效的方法。借助智能健身应用程序，教练可以正确响应，获得所需的训练效果，并防止训练不足或过度等不良事件发生。该模糊算法是为 Android 手机操作系统构建的，在运动前通过蓝牙接收参与者的静息心率（RHR），以确定个人跑步机的合适训练速度模式。基于计算机的模糊程序将 RHR 和运动后的心率恢复（HRR）作为输入，计算心肺耐力水平。实验结果表明，经过 8 周的运动训练，RHR 平均下降 11%，HRR 增加 51.5%，心肺耐力评估水平也得到了提高。该系统可以与其他方法结合使用，为健身教练设计更适合个人的训练计划。
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