Wavelet analysis for early identification of HRV changes in offspring with genetic predisposition to hypertension in Oman.

Background: Offspring with a genetic predisposition to hypertension may have higher blood pressure (BP) at rest compared with those without a genetic predisposition to hypertension. They are also expected to have a higher sympathetic component in the heart rate variability (HRV) which could be computed with signal processing algorithms.

Objective: The purpose of this study is to design a wavelet-based system to estimate the heart rate variability that can be used to detect early cardiovascular changes in offspring with a genetic predisposition to hypertension.

Classification of sleep apnea using wavelet-based spectral analysis of heart rate variability.

Background: Obstructive Sleep Apnea (OSA) is the cessation of breathing during sleep due to the collapse of upper airway. Polysomnographic recording is a conventional method for detection of OSA. Although it provides reliable results, it is expensive and cumbersome.

Statistical signal characterization for congestive heart failure patient's classification.

This paper aims at investigating a new technique of time-domain analysis of heart variability (R-R interval (RRI)) for the screening of patients with Congestive Heart Failure (CHF). This method is based on the Statistical Signal Characterization (SSC) of the analytical signal that is generated using Hilbert transformation of the RRI data. The four SSC parameters are: amplitude mean, period mean, amplitude deviation and period deviation.

Screening of obstructive sleep apnea based on statistical signal characterization of Hilbert transform of RRI data.

A new technique of time-domain analysis for screening of Obstructive Sleep Apnea (OSA) using R-R interval (RRI) data is investigated. This method is based on the Statistical Signal Characterization (SSC) of the analytical signal that is generated using Hilbert transformation of the RRI data. The four SSC parameters: amplitude mean, period mean, amplitude deviation and period deviation, and their maximum and minimum values are found over a 5-minutes sliding window for both the instantaneous amplitudes and the instantaneous frequencies derived from the analytical signal of the RRI data.