Title :
Soft computing technique based on ANFIS for the early detection of sleep disorders
Author :
Garg, Vijay Kumar ; Bansal, R.K.
Author_Institution :
Talwandi Sabo, Guru Kashi Univ., Talwandi Sabo, India
Abstract :
Sleep is a great natural occurring state in which everything is forgotten for a while, become fresh and ready for next coming daily routine exercises. Any person can lag in these exercises, if their sleep is not well taken. But, sometime it is observed that the sleep gets disturbed due to some awkward behaviors known as sleep disorders. The various intelligent techniques/methods are proposed for the diagnosis, detection and classification of sleep disorders, sleep spindles and other sleep related events. In this paper, a system is proposed based on physio-psycho symptoms by using an adaptive neuro-fuzzy inference system (ANFIS). The major concern is taken towards the early detection of only four sleep disorders that are Sleep Apnea, Insomnia, Parasomnia and Snoring. The prior detection of all these disorders are having a prime importance, as it can help a person to safe itself from the further effects that can arise from these sleep disorders. To implement the system, the data set is collected from various physicians comprising the record of 96 patients.
Keywords :
fuzzy neural nets; fuzzy reasoning; medical diagnostic computing; pattern classification; ANFIS; adaptive neuro-fuzzy inference system; insomnia; intelligent techniques; parasomnia; physio-psycho symptoms; sleep apnea; sleep disorder classification; sleep disorder diagnosis; sleep disorder early detection; snoring; soft computing technique; Adaptive systems; Diseases; Fuzzy logic; Neural networks; Psychology; Sleep apnea; Early Detection; Sleep Disorders; Soft Computing;
Conference_Titel :
Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in
Conference_Location :
Ghaziabad
DOI :
10.1109/ICACEA.2015.7164649