Cognitive Neuro-Fuzzy Expert System for Hypotension Control

Abstract

Hypotension; also known as low blood sugar affect gender of all sort; hypotension is a relative term because the blood pressure normally varies greatly with activity, age, medications, and underlying medical conditions.  Low blood pressure can result from conditions of the nervous system, conditions that do not begin in the nervous system and drugs. Neurologic conditions (condition affecting the brain neurons) that can lead to low blood pressure include changing position from lying to more vertical (postural hypotension), stroke, shock, lightheadedness after urinating or defecating, Parkinson's disease, neuropathy and simply fright. Clinical symptoms of hypotension include low blood pressure, dizziness, Fainting, clammy skin, visual impairment and cold sweat. Neuro-Fuzzy Logic explores approximation techniques from neural networks to find the parameter of a fuzzy system. In this paper, the traditional procedure of the medical diagnosis of hypotension employed by physician is analyzed using neuro-fuzzy inference procedure. The proposed system which is self-learning and adaptive is able to handle the uncertainties often associated with the diagnosis and analysis of hypotension.

Keywords: Neural Network, Fuzzy logic, Neuro Fuzzy System, Expert System, Hypotension