BackgroundCardiotocography (CTG) is the most widely used tool for fetal surveillance. The visual analysis of fetal heart rate (FHR) traces largely depends on the expertise and experience of the clinician involved. Several approaches have been proposed for the effective interpretation of FHR. In this paper, a new approach for FHR feature extraction based on empirical mode decomposition (EMD) is proposed, which was used along with support vector machine (SVM) for the classification of FHR recordings as 'normal' or 'at risk'.MethodsThe FHR were recorded from 15 subjects at a sampling rate of 4 Hz and a dataset consisting of 90 randomly selected records of 20 minutes duration was formed from these. All records were labelled as 'normal' or 'at risk' by two experienced obstetricians. A training set was formed by 60 records, the remaining 30 left as the testing set. The standard deviations of the EMD components are input as features to a support vector machine (SVM) to classify FHR samples.ResultsFor the training set, a five-fold cross validation test resulted in an accuracy of 86% whereas the overall geometric mean of sensitivity and specificity was 94.8%. The Kappa value for the training set was .923. Application of the proposed method to the testing set (30 records) resulted in a geometric mean of 81.5%. The Kappa value for the testing set was .684.ConclusionsBased on the overall performance of the system it can be stated that the proposed methodology is a promising new approach for the feature extraction and classification of FHR signals.

Ageing is one of the main contributing factors towards increasing arterial stiffness, leading to changes in peripheral pulses propagation. Therefore the characteristics of the photoplethysmogram (PPG) pulse, especially the rising edge and peak position, are greatly affected. In this study, the PPG pulse rising edge and corresponding peak position have been investigated non-invasively in human subjects as a function of age. Fifteen healthy subjects were selected and grouped in five age intervals, from 20 to 59 years, based on their comparable systolic-diastolic blood pressure and PPG amplitude. As expected, the peripheral pulse shows a steep rise and early peak in younger subjects. With age, the slope becomes blunted and in older subjects, the rise is very gradual and the pulse peak appears much later. Qualitative results were further verified by a modified 10-element Windkessel model to quantify the lumped parameter changes with ageing. This verification highlighted some specific changes in vascular parameters with aging. The rising edge could be considered as one parameter in determining the age-dependent vascular state.

This study was conducted to investigate the utility and efficacy of finger photoplethysmogram pulse amplitude (PPG-AC) in comparison with the standard Doppler ultrasound in assessing an endothelial function via flow-mediated dilation (FMD). High-resolution B-mode scanning of the right brachial artery (BA) of 31 healthy subjects aged 39.7 +/- 11.3 (range 22-64) years and 52 risk subjects aged 47.7 +/- 10.8 (range 30-65) years were performed before and after 4 min of upper arm occlusion. Concurrent with the ultrasound measurement (where color Doppler imaging was used to enhance arterial boundary detection), PPG signals were recorded from both index fingers for cross evaluation and comparison. Our results show that the finger PPG-AC exhibits a similar response to that of the well-known BA dilation: following the release of pressure (cuff around the BA), the PPG-AC increases abruptly before slowly decreasing toward the baseline. The peak PPG-AC is reached significantly faster than the peak FMD measured by ultrasound among healthy and risk groups (P < 0.001). The proposed technique using a finger photoplethysmogram can be applied in a rapid and non-invasive assessment of peripheral vascular functions as an alternative low-cost and less operator-dependent tool compared to ultrasound.

An algorithm based on digital filtering, adaptive thresholding, statistical properties in the time domain, and differencing of local maxima and minima has been developed for the simultaneous measurement of the fetal and maternal heart rates from the maternal abdominal electrocardiogram during pregnancy and labor for ambulatory monitoring. A microcontroller-based system has been used to implement the algorithm in real-time. A Doppler ultrasound fetal monitor was used for statistical comparison on five volunteers with low risk pregnancies, between 35 and 40 weeks of gestation. Results showed an average percent root mean square difference of 5.32% and linear correlation coefficient from 0.84 to 0.93. The fetal heart rate curves remained inside a +/- 5-beats-per-minute limit relative to the reference ultrasound method for 84.1% of the time.

Cardiotocograph (CTG) is widely used in everyday clinical practice for fetal surveillance, where it is used to record fetal heart rate (FHR) and uterine activity (UA). These two biosignals can be used for antepartum and intrapartum fetal monitoring and are, in fact, nonlinear and non-stationary. CTG recordings are often corrupted by artifacts such as missing beats in FHR, high-frequency noise in FHR and UA signals. In this paper, an empirical mode decomposition (EMD) method is applied on CTG signals. A recursive algorithm is first utilized to eliminate missing beats. High-frequency noise is reduced using EMD followed by the partial reconstruction (PAR) method, where the noise order is identified by a statistical method. The obtained signal enhancement from the proposed method is validated by comparing the resulting traces with the output obtained by applying classical signal processing methods such as Butterworth low-pass filtering, linear interpolation and a moving average filter on 12 CTG signals. Three obstetricians evaluated all 12 sets of traces and rated the proposed method, on average, 3.8 out of 5 on a scale of 1(lowest) to 5 (highest).