Abstract
Ayurveda is a well-established form of alternative medicine. The terms Prakriti, Vikriti, Agni, and Koshta are well-known and their associations have been articulated in both the traditional literature of Ayurveda and by practicing Ayurvedic clinicians. These associations, while well understood and applied clinically, have not until recently been explored empirically. Correlational analysis has shown that these principles and processes of Ayurveda can be statistically observed in a large sample of patients. For example, Prakriti (the constitution of the body) and Vikriti (the current state of the body) are correlated to Agni (digestion) and Koshta (gut responsiveness), and results uniformly indicate that Vikriti is also associated to weight, body mass index, and diet, each an established cardiovascular disease risk factor. The present proof-of-concept case study takes these topics to the next stage of empirical investigation aimed at formulating an approach to bring Ayurvedic research into mainstream Life Sciences and complementary medicine. The principal challenge here is in a gap between the paradigms of modern Life Sciences and Ayurveda. We propose bridging this gap by formulating a minimal phenomenological nonlinear dynamics model to account for the critical role Agni plays in the health of Vikriti and for a threshold-type improvement in both Agni and Vikriti during the process of a six-month Ayurvedic treatment.
Reference33 articles.
1. Zgurovsky MZ, Kasyanov PO. Qualitative and quantitative analysis of nonlinear systems. Springer. 2018.
2. Alon U. An introduction to systems biology. In: Lin X, Singh M, Britton NF, et al editors. 2nd ed. Chapman & Hall/CRC Computational Biology Series. Taylor and Francis;2019.
3. Nonlinear dynamics of COVID-19 pandemic: Modelling, control, and future perspectives;Machado JA;Nonlinear Dynamics,2020
4. Tulchynska S, Popelo O, Garafonova O, et al. Modelling the influence of innovative factors on sustainable development of regions in the context of digitalization. Journal of Management Information and Decision Sciences. 2021;24:1-8.
5. Disentangling climatic and anthropogenic contributions to nonlinear dynamics of alpine grassland productivity on the Qinghai-Tibetan Plateau;Wu;J Environ Manag,2021