TY - JOUR
T1 - Investigation of the high frequency band of heart rate variability
T2 - Identification of preeclamptic pregnancy from normal pregnancy in Oman
AU - Hossen, Abdulnasir
AU - Jaju, Deepali
AU - Barhoum, Alaa
AU - Gowri, Vaidyanathan
AU - Hamdi, Ilham
AU - Hassan, Mohammed Othman
AU - Al-Kharusi, Lamya
PY - 2013/6
Y1 - 2013/6
N2 - Background: The spectral analysis of heart rate variability (HRV) shows a decrease in the power of the high frequency (HF) component in preeclamptic pregnancy compared with normal pregnancy; such a decrease is associated with an increase in the low frequency (LF/HF) ratio of the HRV. The physiological interpretation is that preclamptic pregnancy and normal pregnancy is associated with a facilitation of sympathetic regulation and an attenuation of parasympathetic influence of HR compared with nonpregnancy. Objective: We used a spectral analysis of HRV to identify preeclamptic pregnancy in Oman. Methods: Fast Fourier transform (FFT) spectral analysis was used to show whether patients with preeclamptic pregnancy have a reduction in the power of the HF band of HRV compared with subjects with normal pregnancy. The soft-decision wavelet-based technique is then implemented to scan the HF band to find which part of it is associated with preeclampsia. Data was obtained from eight preeclamptic pregnant subjects and nine normal pregnant controls of the same pregnancy duration. Results: The classical FFT approach to the LF/HF power ratio of HRV is a possible classification factor. The identification accuracy obtained was 76.47%, while the sensitivity (identification of patients) and the specificity (identification of normal subjects) were found to be 75% and 77.77%, respectively. The soft-decision wavelet-based technique with five decomposition stages of Coif5 wavelets, finds that B10 and B11 (out of 32 bands) covering the frequency range of (0.1406-0.1563) Hz, and (0.1563-0.1719) Hz, respectively, are the most dominant parts of the HF band affected by preeclampsia. The identification accuracy, sensitivity, and specificity using this range are found to be 94.11%, 100%, and 88.88%, respectively. Conclusion: Soft-decision wavelet decomposition is shown to be a successful tool for identification of preeclampsia.
AB - Background: The spectral analysis of heart rate variability (HRV) shows a decrease in the power of the high frequency (HF) component in preeclamptic pregnancy compared with normal pregnancy; such a decrease is associated with an increase in the low frequency (LF/HF) ratio of the HRV. The physiological interpretation is that preclamptic pregnancy and normal pregnancy is associated with a facilitation of sympathetic regulation and an attenuation of parasympathetic influence of HR compared with nonpregnancy. Objective: We used a spectral analysis of HRV to identify preeclamptic pregnancy in Oman. Methods: Fast Fourier transform (FFT) spectral analysis was used to show whether patients with preeclamptic pregnancy have a reduction in the power of the HF band of HRV compared with subjects with normal pregnancy. The soft-decision wavelet-based technique is then implemented to scan the HF band to find which part of it is associated with preeclampsia. Data was obtained from eight preeclamptic pregnant subjects and nine normal pregnant controls of the same pregnancy duration. Results: The classical FFT approach to the LF/HF power ratio of HRV is a possible classification factor. The identification accuracy obtained was 76.47%, while the sensitivity (identification of patients) and the specificity (identification of normal subjects) were found to be 75% and 77.77%, respectively. The soft-decision wavelet-based technique with five decomposition stages of Coif5 wavelets, finds that B10 and B11 (out of 32 bands) covering the frequency range of (0.1406-0.1563) Hz, and (0.1563-0.1719) Hz, respectively, are the most dominant parts of the HF band affected by preeclampsia. The identification accuracy, sensitivity, and specificity using this range are found to be 94.11%, 100%, and 88.88%, respectively. Conclusion: Soft-decision wavelet decomposition is shown to be a successful tool for identification of preeclampsia.
KW - FFT
KW - HRV
KW - LF/HF
KW - Preeclampsia
KW - Soft-decision wavelet-decomposition
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U2 - 10.5372/1905-7415.0703.185
DO - 10.5372/1905-7415.0703.185
M3 - Article
AN - SCOPUS:84880667051
SN - 1905-7415
VL - 7
SP - 339
EP - 346
JO - Asian Biomedicine
JF - Asian Biomedicine
IS - 3
ER -