Total views : 246
Fuzzy Expert System to Calculate the Strength/ Immunity of a Human Body
Objectives: Determining the level of strength of patients’ body is essential for an Ayurvedic Physician to provide the appropriate dose of medicines to them. The proposed work is a stepping stone towards a vigilant and proper diagnosis that will surely leads to an efficacious treatment. Methods/Statistical Analysis: A fuzzy logic based expert system is designed to calculate the quality of the seven tissues (Lymph, Blood, Muscle, Fat tissue, Bone, Bone Marrow, Reproductive tissues) and mind of a human body. Based on that quality the overall body strength is computed. All the required parameters are finalized after consulting an Ayurvedic Expert during knowledge acquisition phase. Findings: The accuracy and veracity of the system is evaluated by ranking all results of different defuzzification methods. Data collection is performed by survey method and results were highlighted as false positives and false negatives after verifying from expert. Maximum results depict that the outputs produced by the proposed system matches with those of Ayurvedic Expert. Application/ Improvements: The proposed system will guide the physicians to plan the dose of medicines and treatment for the patients. This fuzzy based system will prove itself as a learning kit for Ayurveda and Vedic practitioner.
Defuzzification, Examination of Strength, Fuzzy Expert System, Fuzzy Logic, Fuzzification, Inference System.
- A statistical fuzzy inference system for classifying human constituents. 2010. Available from: http://ieeexplore.ieee.org/document/5715634/
- Shashirekha HK, Bargale SS. Importance of dasha vidha pareeksha in clinical practice. Journal of Ayurveda and Holistic Medicine. 2014 Apr; 2(3):25-34.
- An approach to develop Multi Techniques Integrated Expert System for Diagnosis of Human Constitutions. 2008. Available from: http://ieeexplore.ieee.org/document/4783970/
- Mandip RG. Applied aspects of dasha-vidha atura pariksha. Journal of Ayurveda Physicians Surgeons. 2015 Mar; 2(2):40-6.
- Agrawal P, Vishu, Kumar V. Fuzzy rule-based medical expert system to identify the disorders of eyes, ENT and liver. International Journal of Advanced Intelligence Paradigm. 2015 Dec; 7(3/4):352-67.
- Sivanandam SN, Sumathi S, Deepa SN. Introduction to Fuzzy Logic using MATLAB. 1st ed. Springer; 2006.
- Mehta AK, Gupta N, Sharma RN. Jain B. Health and Harmonythrough Ayurveda. 2002.
- Sharma R, Dash B. Charaka Samhita. Varanasi, India: Chowkhamba Sanskrit Series; 2009.
- Ross T. Fuzzy logic with engineering applications. 3rd ed. John Wiley and Sons; 2010.
- Fuzzy Rule based Students’ Performance Analysis Expert System. 2014. Available from: http://ieeexplore.ieee.org/document/6781259/ 11. Darlington K. The essence of expert system. 3rd ed. Prentice Hall; 1999.
- Jackson P. Introduction to Expert Systems. 3rd ed. USA: Addison-Wesley; 1993.
- A computer model for diagnosis of human constituents. 2006. Available from: http://ieeexplore.ieee.org/document/4250234/.
- Agrawal PV, Kumar S, Jain L. Fuzzy rule-based medical expert system to identify the disorders of eyes, ENT and liver. International Journal of Advanced Intelligent Paradigm. 2015 Dec; 7(3/4):352-67.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.