Detection of perinatal hypoxia using time-frequency analysis of heart rate variability signals
Author | Dong S. |
Author | Boashash B. |
Author | Azemi G. |
Author | Lingwood B.E. |
Author | Colditz P.B. |
Available date | 2022-05-31T19:01:37Z |
Publication Date | 2013 |
Publication Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
Resource | Scopus |
Identifier | http://dx.doi.org/10.1109/ICASSP.2013.6637787 |
Abstract | This paper presents a time-frequency approach to detect perinatal hypoxia by characterizing the nonstationary nature of heart rate variability (HRV) signals. Quadratic time-frequency distributions (TFDs) are used to represent the HRV signals. Six features based on the instantaneous frequency (IF) of the lower frequency components of HRV signals are selected to establish a classifier using support vector machine. The classifier is trained and tested using the signals recorded from a neonatal piglet model under a controlled hypoxic condition, which provides reliable annotations on the data. The method shows superior performance in the detection of hypoxic epochs with sensitivity (89.8%), specificity (100%) and total accuracy (94.9%) compared with that based on frequency domain features, indicating that nonstationarity should be taken into account for a more accurate assessment of the newborn status with possible hypoxia when analyzing HRV signals. |
Language | en |
Subject | Heart rate variability Heart rate variability signals Lower frequency components Non-stationarities perinatal hypoxia Quadratic time-frequency Time-frequency approach Time-frequency distributions Heart Robustness (control systems) Signal detection |
Type | Conference Paper |
Pagination | 939-943 |
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Electrical Engineering [2616 items ]