Why the study?
Measuring cardiorespiratory endurance via laboratory VO2max is not practical for real-life use, warranting heart rate-based estimation methods.
Does a fuzzy algorithm-based training program improve resting heart rate, heart rate recovery, and cardiorespiratory endurance?
Does a fuzzy algorithm-based training program improve resting heart rate, heart rate recovery, and cardiorespiratory endurance?
A fuzzy algorithm utilizing resting heart rate and heart rate recovery can effectively guide personalized treadmill training to improve cardiorespiratory endurance.
May support fuzzy algorithm personalization in small cohorts; leaves open validation versus standard training in randomized trials.
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 (VO2max) 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.
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Cheng et al. (2019) studied this question.
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