Selection of the Best Thermal Massage Treatment for Diabetes by using Fuzzy Analytical Hierarchy Process
Keywords:
Fuzzy Analytical Hierarchy Process, Diabetes, Thermal massageAbstract
Diabetes is a condition in which the human blood glucose (sugar) level is abnormally high due to the lack of insulin produced by the pancreas. As diabetes has been claimed to be a disease that is incurable, researchers have come out with numerous alternati ves in making it curable and one of them is thermal massage treatment. This treatment refers to the application of chiropractic where it focuses on realigning the spine where diabetes is claimed to be related to the misalignment of thoracic 7 (T7). The obj ective of this study is to identify and select the best and most effective thermal massage treatment session(s) required for both T1D and T2D patients of different high glucose level in the blood to be reduced to the normal glucose level by using thermal m assager. This study is conducted for the diabetic patients who receive treatments from Ceragem Healthcare Centre on how to optimise their thermal massage treatments to normalise their glucose level. Fuzzy Analytical Hierarchy Process (AHP) is utilised in t his type of selection problem mainly due to the reliable results produced for the imprecise and uncertain preferences of the users in which able to be expressed as a fuzzy set (triangular fuzzy number). The findings indicated that the most significant crit eria for effective thermal massage is determined by the “number of treatment session (per day)†where the best thermal massage treatment is derived from the normalised fuzzy weight of both criteria and sub - criteria.Downloads
Download data is not yet available.
Downloads
Published
2017-03-30
How to Cite
Mahat, N., & Ahmad, S. (2017). Selection of the Best Thermal Massage Treatment for Diabetes by using Fuzzy Analytical Hierarchy Process. Journal of Computing Research and Innovation, 2(1), 23–28. Retrieved from https://jcrinn.com/index.php/jcrinn/article/view/25
Issue
Section
General Computing
License
Copyright (c) 2018 Journal of Computing Research and Innovation
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.