Development of a Hierarchical Fuzzy System-Based Tool for the Rapid and Precise Detection of ADHD

Abstract

Attention-deficit/hyperactivity disorder (ADHD) disorder is quite common in India. It is related to neuro development with common symptoms of impulsiveness, insensitivity, and hyperactivity. ADHD diagnosis is quite challenging because of its heterogenous symptoms and its occurrence with some disorders like autism as well. The paper suggests a fuzzy system capable of rapid and precise detection of ADHD. The suggested process is: i) Feeding of symptoms of the patient (emotional, hyperactivity, inattention) into Fuzzy Rule-based system; ii) Its triangular membership function; iii) Centroid defuzzification; iv) Considering option intersections, commodities, and output ADHD severity levels; and v) Doctor’s estimation of extremity and commodities. The fuzzy approach is based on modelling intense variations in substitution of the collected data. This system shows higher accuracy. It also performs better than the existing tools by detecting ADHD and commodities by i) Reducing manual operations; and ii) Working on a single platform. Another plus point of ADHD is its focus on precision diagnosis of neuro developmental disorders.