This study found that an obese person exhibits lower fitness level and weaker cardiovascular function than a normal person. The muscular strength, muscular endurance, flexibility, power, agility, and balance were evaluated by grip strength (kg), sit-ups (reps/min), sit and reach (cm), vertical jump (cm), side steps (reps/30 s), and standing on one leg with eyes closed (s), respectively. In the investigation of the associations between cardiovascular function and both BMI and PF in Korean men, the VO 2max was obtained from YMCA submaximal test using a cycle erogometer. The results showed that periodical customization of the fuzzy system for individuals was important because of changes in the muscular fatigue properties and the differences between the objective and subjective representations of fatigue. For the basic data collection, the respiratory gas exchange and the blood lactate every minute were simultaneously measured to determine the anaerobic threshold (AT) and the lactate threshold (LT). To remain healthy by exercising, and to provide appropriate exercise levels for elderly people, a fuzzy system is designed for adjusting the cycle ergometer workload to each individual’s physical work capacity. The appropriate exercise level varies for each elderly person because there are great individual differences. Data collected included five parameters required for the PF passport: subject’s age, body mass index (BMI), performance in the sit-and-reach test, 1-min bent-leg curl-ups, and cardiorespiratory endurance. To eliminate the need to refer to a chart of the modular standard to decide the fitness category, A back-propagation neural network (BPNN) was adopted to accesses the subject’s physical fitness (PF). Improving cardiorespiratory endurance is an important issue for maintaining good health. From a health perspective, people who have good heart and lung endurance can exercise longer, not get tired as quickly, and avoid all kinds of cardiorespiratory diseases. About 60–85% of adults in the world live a static life, and two-thirds of children have insufficient physical activity, which will affect their health and cause public health problems in the future. The World Health Organization points out that inadequate physical activity has become the fourth most important risk factor for global mortality, more than 2 million deaths can be attributed to physical inactivity. With the rapid development of the economy, manual labor work has been replaced by a large number of machines, resulting in an inactive state of life. The proposed system can be combined with other methods for fitness instructors to design a training program that is more suitable for individuals. 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 computer-based fuzzy program takes RHR and heart rate recovery (HRR) after exercise as inputs to calculate the cardiorespiratory endurance level. 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. 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. 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. Given the relative difficulty in measuring oxygen consumption directly, we can estimate cardiorespiratory endurance on the basis of heart beat. Cardiorespiratory endurance is typically measured in the laboratory by maximum oxygen uptake (VO 2max) which is not a practical method for real-life use. 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.
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