Intelligent scheduling of execution for customized physical fitness and healthcare system

Huang, Chung-Chi; Liu, Hsiao-Man; Huang, Chung-Lin

doi:10.3233/thc-151096

Cited by 5 publications

(1 citation statement)

References 4 publications

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“…The testing information will be recorded and managed through wireless sensor networks in order to better understand the health status of users. Huang et al [10] developed an intelligent execution scheduling system for specific fitness and health care systems. Using fuzzy logic reasoning, test results of health care systems are automatically generated, and scheduling schemes are generated by genetic algorithm, which effectively improves people's system health management system.…”

Section: Introductionmentioning

confidence: 99%

Research on Intelligent Monitoring and Analysis of Physical Fitness Based on the Internet of Things

Huang

Chen

Zhang³

et al. 2019

IEEE Access

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In the process of physical fitness training, it is an important subject of scientific physical fitness training to adjust and control the physical load intensity in real-time, accurately and effectively according to the physiological load inside the human body so as to make it consistent with the predetermined goal of the training plan. Aiming at the current demand of smartphone popularization and athlete training monitoring, this paper designs an intelligent monitoring system of physical fitness based on the Internet of Things technology. By selecting such factors as vertical jump, fast leg raising, sitting forward, height, chest circumference, percentage of body constitution, YOYO intermittent endurance running and so on, using RFID technology to mark different athletes, and after using the particle swarm optimization method of BP network to establish the evaluation model of the athletes' physical condition. Through simulation, the physical condition of athletes is accurately predicted, which provides a new scientific and technological means to improve the efficiency of physical training and make physical training scientific. INDEX TERMS Physical fitness, intelligent monitoring, The Internet of Things, BP neural network, particle swarm.

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Section: Introductionmentioning

confidence: 99%