| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10322406 | Expert Systems with Applications | 2012 | 11 Pages |
Abstract
⺠This study presents a methodology for OSA detection based on HRV time series. ⺠The HRV is characterized by dynamic banked features extracted from its spectrogram. ⺠The spectral splitting scheme to search frequency boundaries is introduced. ⺠Attained results show similar performance compared with another outcomes. ⺠An easier clinical interpretation of HRV-derived parameters is obtained.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
J.D. MartÃnez-Vargas, L.M. Sepulveda-Cano, C. Travieso-Gonzalez, G. Castellanos-Dominguez,