Abstract
Chronic diseases are the number one killer in the world today, and the most common cause of chronic diseases is lack of exercise. Research on the application of artificial intelligence technology in the medical field can shorten the distance between clinical best practice and practical application, and promote the standardized management of clinicians according to specifications. In this paper, three different exercise methods, continuous aerobic, anaerobic, and control, were used to conduct a 12-week study. This paper discussed the effects of three different forms of exercise on the body shape, body composition, and metabolism of patients with chronic diseases, and discussed the intervention effects of the same exercise mode in different periods (0–6 weeks, 6–12 weeks), to provide a theoretical basis for more effective and targeted choice of exercise intervention programs. Through training load, training frequency, training sequence, training interval, and other factors, a training plan can be designed. To avoid mistakes, experts often try to do some items that are prone to mistakes, especially lung function measurement. The scores of self-care, extraction, standing, occupation/housework, social activities, and total scores were significantly lower than those before intervention (P < 0.01). Advanced resistance kinetic energy can significantly improve the exercise and cardiopulmonary function of patients with various types of chronic diseases. Advanced resistance kinetic energy can significantly promote the strength and explosive force of the shoulder, waist, and back muscles in chronic patients, and can significantly promote the muscle adaptability of the shoulder, waist, and back muscles in chronic patients.
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