A different sleep apnea classification system with neural network based on the acceleration signals

Yuzer, Ahmet; Sümbül, Harun; Nour, Majid; POLAT, KEMAL

doi:10.1016/j.apacoust.2020.107225

A different sleep apnea classification system with neural network based on the acceleration signals

Yuzer A. H., Sümbül H., Nour M., POLAT K.

APPLIED ACOUSTICS, vol.163, 2020 (SCI-Expanded, Scopus)

Publication Type: Article / Article
Volume: 163
Publication Date: 2020
Doi Number: 10.1016/j.apacoust.2020.107225
Journal Name: APPLIED ACOUSTICS
Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Communication & Mass Media Index, Compendex, ICONDA Bibliographic, INSPEC, DIALNET
Keywords: Sleep apnea, Acceleration sensor, Acceleration data, Artificial neural network, Medical decision making, ELECTROCARDIOGRAM, PREDICTION, DIAGNOSIS, EVENTS, DEVICE
Ondokuz Mayıs University Affiliated: Yes

Abstract

Background and objective: The apnea syndrome is characterized by an abnormal breath pause or reduction in the airflow during sleep. It is reported in the literature that it affects 2% of middle-aged women and 4% of middle-aged men, approximately. This study has vital importance, especially for the elderly, the disabled, and pediatric sleep apnea patients.