A Sample Protocol for Using Tai Chi and Qigong to Treat Chronic Fatigue Syndrome: An Application of Artificial Intelligence to Traditional Chinese Medicine

Abstract Chronic Fatigue Syndrome (CFS), also known as myalgic encephalomyelitis (ME/CFS), affects 17–24 million people worldwide and is characterized by profound, unexplained fatigue, post-exertional malaise, unrefreshing sleep, and significant impairment in quality of life. Conventional treatments remain largely symptomatic and of limited efficacy. Traditional Chinese Medicine (TCM) views CFS as a disorder of Qi deficiency and stagnation, making gentle Qi-cultivating practices such as Tai Chi and Qigong theoretically well-suited interventions. Guo Lin Qigong, originally developed by Grandmaster Guo Lin for cancer recovery, employs slow walking combined with specific breathing patterns (“Wind Breathing”) and is noted for its extremely low intensity (1.5–2 METs), making it tolerable even for severely fatigued patients. Using Grok 4 artificial intelligence, a tailored, evidence-informed Guo Lin Qigong protocol was generated and refined for CFS. The resulting 15-minute program emphasizes the “Wind Breathing Walk” while omitting higher-effort postures to minimize risk of post-exertional malaise. An 8-week randomized controlled trial design is proposed to test the protocol’s effects on fatigue (MFI-20), vitality (VAS), functional capacity (6MWD), and quality of life (SF-36). This study illustrates a novel methodology for rapidly translating ancient TCM practices into modern, testable clinical protocols through artificial intelligence, offering a scalable model for other chronic illnesses.