Human prakriti and tridosha are important for human health and fitness according to Ayurveda. A person's prakriti can be identified in Ayurveda in several ways. According to Ayurveda, every person born has five elements: earth, air, water, fire and space.We own distinctive balance of these five elements in assorted degrees. The balance of these elements is known as Tridosha. There are three basic doshas: Vata, Pitta and Kapha, and good health is considered a balance of these three doshas. Doctors evaluate these characteristics through examination and palpation to determine Prakriti in patients. The physician decides on diagnosis, primary prevention, and therapy based on the Prakriti of each individual. Prakriti assessment involves clinical examination including questions about physiological and behavioural traits. There is requirement to develop models correctly for predicting prakriti classes that have been used for foretell various diseases. Ayurvedic doctors examine the prakriti of a person either by accessing the physical features and or by inspecting the nature of their pulsation. Based on this investigation, they identify, prevent and cure disease in patients by prescribing medicine.This article looks at a comprehensive literature review based on three aspects: prakriti and tridosha, the physiological characteristics. Research gaps were also found based on the literature survey.
Trivedi, Arpit & Patel, Dharmendra. (2021). Survey on Human Prakriti and Tridosha (Vata, Pitta and Kapha) Based on Physiological Features Using Machine Learning and Image Processing Techniques. 2394-2320.
Ammu Anna Mathew and Dr. S. Vivekanandan,” A Review on Ayurvedic Approach in Sphygmology: Characteristics, Traditional Parameters and Existing Sensors in Sphygmology”, International Journal Of Scientific & Technology Research Volume 9, Issue 03, March 2020.
Ramesh Duraisamy and Vijay Jeyakumar ”A systematic approach for pulse diagnosis based on siddha medical procedure: https://www.researchgate.net/publication/320743728 .
Sharma, Hari, and Robert Keith Wallace. 2020. "Ayurveda and Epigenetics" Medicina 56, no. 12: 687. https://doi.org/10.3390/medicina56120687
Joshi Manisha S , Umadevi V , Akshitha Raj B N (2020) Computerized pragmatic assessment of Prakriti Dosha using tongue images- Pilot study. Indian Journal of Science and Technology 13(48): 4679-4698. https://doi.org/10.17485/IJST/v13i48.1626
Wallace, Robert Keith. 2020. "Ayurgenomics and Modern Medicine" Medicina 56, no. 12: 661. https://doi.org/10.3390/medicina56120661
Bhat, Vedika & Borse, Swapnil & Chavan-Gautam, Preeti & Joshi, Kalpana. (2021). Exploring AyuGenomics approach for understanding COVID-19 predisposition and progression. Journal of Ayurveda and Integrative Medicine.13.10.1016/j.jaim.2021.06.003.
V. Madaan and A. Goyal, "Predicting Ayurveda-Based Constituent Balancing in Human Body Using Machine Learning Methods," in IEEE Access, vol. 8, pp. 65060-65070, 2020, doi: 10.1109/ACCESS.2020.2985717.
Yogita Ghodke, Kalpana Joshi, Bhushan Patwardhan, "Traditional Medicine to Modern Pharmacogenomics: Ayurveda Prakriti Type and CYP2C19 Gene Polymorphism Associated with the Metabolic Variability", Evidence-Based Complementary and Alternative Medicine, vol. 2011, Article ID 249528, 5 pages, 2011. https://doi.org/10.1093/ecam/nep206.
Huang Zoufang, Chavda Vivek P., Bezbaruah Rajashri, Uversky Vladimir N., P. Sucharitha, Patel Aayushi B., Chen Zhe-Sheng, An Ayurgenomics Approach: Prakriti-Based Drug Discovery and Development for Personalized Care Frontiers in Pharmacology, volume 13, 2022, doi:10.3389/fphar.2022.866827. https://www.frontiersin.org/articles/10.3389/fphar.2022.86682
Gadre, Gayatri, "Classification of Humans into Ayurvedic Prakriti Types using Computer Vision" (2019). Master's Projects.
Vishu Maddanet Predicting Ayurveda-Based Constituent Balancing in Human Body Using Machine Learning Methods. https://www.researchgate.net/publication/340487137.
Shilpa S, and Murthy CG, “Development and standardization of Mysore Tridosha scale,” Ayu., vol. 32, no. 3, pp. 308–314, Aug 2011.
P. Kallurkar, K. Patil, G. Sharma, S. Sharma, and N. Sharma, “Analysis of Tridosha in various physiological conditions,” in 2015 IEEE International Conference on Electronics, Computing and Communication Technologies(CONECCT), 2015, pp.1–5.
M. Osman, M. Maar of, and M. Rohani, “Towards Integrating Statistical Color Features for Human Skin Detection,”2016.
Sanyam Jain , Taruna chawala “Ayurvedic doshas identification using face and body image features “International Journal of Advanced Research in Computer Science, Volume 12, No. 4, July-August 2021.
M. Sharmila Begum, R. Duraiarasan, P. J. Dhivaakar, “Diagnosing Diseases through pulse using pressure sensor” https://www.researchgate.net.
U. R. Muhammad, M. Svanera, R. Leonardi, and S. Benini, “Hair detection, segmentation, and hairstyle classification in the wild,” Image Vis. Comput., vol. 71, pp. 25-37, Mar.2018.
Corina Dunlap, Douglas Hanes, Charles Elder, Carolyn Nygaard, and Heather Zwickeya, “Reliability of self-reported constitutional questionnaires in Ayurveda diagnosis,” J Ayurveda Integrative Medicine, vol. 8, no. 4, pp. 257–262, Dec 2017.
H. Zuo, H. Fan, E. Blasch, and H. Ling, “Combining Convolutional and Recurrent Neural Networks for Human Skin Detection,” IEEE Signal Process. Lett., vol. 24, no. 3, pp. 289-293, Mar.2017.
P. Mehta, Dataset of around 800k images consisting of 1100 Famous Celebrities and an Unknown class to classify unknown faces: prateekmehta59/Celebrity-Face-Recognition-Dataset.2019.
S. V. Manoj Kumar Singh, "Tridosha in Context of Living Organisms," International Journal of Ayurveda and Pharmaceutical Chemistry, Vol.1, no. 11, pp. 207-215, 2019.
Cite this article
Swati Dhole and S.E. Yedey, “A Review Paper on Identification of Ayurvedic Prakriti Types”, Advances in Computational Intelligence in Materials Science, pp. 169-172, May. 2023. doi:10.53759/acims/978-9914-9946-9-8_26