AN INTELLIGENT COMPUTING METHOD FOR THE DIAGNOSIS OF SLEEP DISORDERS

Abstract

In today s era, sleep disorders have become the common disorder faced by most of the population. Going by the statistics, 20% of people around the world are suffering from sleep disorders. It makes people to use sleeping pills for a sound sleep. The designing and building of an intelligent computing method for the diagnosis of sleep disorders can enhance the health of many patients suffering from sleep disorders. newlineIn this study, 3 different types of datasets have been considered: Physionet, Harvard database, UZ Leuven Database. In this, ECG signals recordings vary in length slightly less than 7 hours to nearly 10 hours each. Each recording includes a continuous digitized ECG signals. These signals were categorized into 2 sections, in which females were having age of 27-44 years, height of 158-183 cm and weight of 53-65 kg and males were having age of 27-63 years, height of 168-184 cm and weight of 64-135 kg. newlineIn proposed method ANFUS, ANN has been integrated with FCM, further it has been combined with SVM-OVA. The complete working of intelligent system has been described in this thesis. A comparison of the proposed system has been made with the other implemented intelligent techniques like ANN, FIS, ANFIS and SVM-OVA to check the performance measurements based on accuracy, sensitivity and specificity. newline