| Title |
A Study for Snoring Detection Based Artificial Neural Network |
| Authors |
장원규(Jang, Won-Kyu) ; 조성필(Cho, Sung-Pil) ; 이경중(Lee , Kyung-Joung) |
| Keywords |
Snoring detection ; BPNN(Back-Propagation Netural Network) |
| Abstract |
In this study, we developed a snoring detection algorithm that detects snores automatically. It consists of preprocessing and snoring detection part. The preprocessing part is composed of a noise removal part using spectrum subtraction, and segmentation part, and computation part of temporal and spectral features. And the snoring detection part decides whether detected blocks are snores with BPNN(Back-Propagation Neural Network). BPNN with one hidden layer and one output layer, is trained with data of 7 subjects and tested with data of 11 subjects of total 18 subjects. The proposed algorithm showed a Sensitivity of 90.41% and a Predictive Positive Value of 84.95%. |