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.

Summary:In view of the high anti-oxidative potential of tocotrienol, the role of the tocotrienol-rich fraction (TRF) of palm oil in preventing pregnancy induced hypertension (PIH) was explored in a randomized double-blind placebo-controlled clinical trial in an urban teaching hospital. Healthy primigravidae were randomized to receive either oral TRF 100mg daily or placebo, from early second trimester until delivery. Out of 299 women, 151 were randomized into the TRF arm and 148 into the placebo arm. A total of 15 (5.0%) developed PIH. Although there was no statistically significant difference in the incidence of PIH (4/151 or 2.6% in the TRF arm vs 11/148 or 7.4% in the placebo arm, p = 0.058) between the two arms, there was a tendency towards a lower incidence of PIH in the TRF arm compared to the placebo arm. With TRF supplementation, the relative risk (RR) of PIH was 0.36 (95% CI 0.12-1.09). In conclusion, although TRF from palm oil does not statistically significantly reduce the risk of development of PIH in the population studied, the 64% reduction in incidence of PIH is substantial. The findings warrant further clinical trials, particularly in high risk populations.

Heart disease remains the main leading cause of death globally and around 50% of the patients died due to sudden cardiac death (SCD). Early detection and prediction of SCD have become an important topic of research and it is crucial for cardiac patient’s survival. Electrocardiography (ECG) has always been the first screening method for patient with cardiac complaints and it is proven as an important predictor of SCD. ECG parameters such as RR interval, QT duration, QRS complex curve, J-point elevation and T-wave alternan are found effective in differentiating normal and SCD subjects. The objectives of this paper are to give an overview of SCD and to analyze multiple important ECG-based SCD detection and prediction models in terms of processing techniques and performance wise. Detail discussions are made in four major stages of the models developed including ECG data, signal pre-processing and processing techniques as well as classification methods. Heart rate variability (HRV) is found as an important SCD predictor as it is widely used in detecting or predicting SCD. Studies showed the possibility of SCD to be detected as early as one hour prior to the event using linear and non-linear features of HRV. Currently, up to 3 hours of analysis has been carried out. However, the best prediction models are only able to detect SCD at 6 minutes before the event with acceptable accuracy of 92.77%. A few arguments and recommendation in terms of data preparation, processing and classification techniques, as well as utilizing photoplethysmography with ECG are pointed out in this paper so that future analysis can be done with better accuracy of SCD detection accuracy.

Fiducial points of photoplethysmogram (PPG), first derivative PPG (VPG), and second derivative PPG (APG) are essential in extracting numerous parameters to diagnose cardiovascular disease. However, the fiducial points were usually detected using complex mathematical algorithms. Inflection points from derivatives waveforms are not thoroughly studied, whereas they can significantly assist in peak detection. This study is performed to investigate the derivative waveforms of PPG and use them to detect the important peaks of PPG, VPG, and APG. PPGs with different morphologies from 43 ischemic heart disease subjects are analyzed. Inflection points of the derivative waveforms up to the fourth level are observed, and consistent information (derivative markers) is used to detect the fiducial points of PPG, VPG, and APG with proper sequence. Moving average filter and simple thresholding techniques are applied to detect the primary points in VPG and the third derivative waveform. A total of twelve out of twenty derivative markers are found reliable in detecting fiducial points of two common types of PPG. Systolic peaks are accurately detected with 99.64% sensitivity and 99.38% positive predictivity using the 43 IHD dataset and Complex System Laboratory (CSL) Pulse Oximetry Artifact Labels database. The study has introduced the fourth derivative PPG waveform with four main points, which are significantly valuable for detecting the fiducial points of PPG, VPG, and APG.

Objective: To determine the trend in incidence of preterm birth over five years and its predictors in a single centre.Design: A cross sectional study using electronic data from a Total Hospital Information System (THIS) and computerized birth registry system.Setting: A single teaching and referral hospital in the Greater Kuala Lumpur, Malaysia.Population or Sample: All livebirths delivered in the centre from January 2011 to December 2015 weighing ≥500g.Methods: Logistic regressions with backward likelihood ratio were used. Main outcome measures: Preterm live birth and live term babies.Results: 31,405 live births were included. There was almost 20% increment in the incidence of preterm births between 2011 and 2012 which then gradually decreased until 2015. Maternal age of 20-34 years (OR 0.7, 95% CI 0.7-0.8) was noted as a protective factor. The highest risk level of the pregnancy (OR 2.83, 95% CI 2.3-3.4), multiple pregnancy (OR 2.2, 95% CI 1.8-2.6), low birth weight (OR 18.7,) and male infant (OR 1.3, 95% CI 1.2-1.5) were noted as risk factors. Conclusions:The incidence showed an upward trend between 2011 and 2012 then a gradual decrease until 2015 with a similar pattern reported by national data. The predictors of preterm birth in the study centre were birth weight, risk level of the pregnancy, multiplicity of pregnancy, maternal age and infant gender. Continuum of care using the risk level coding assessment must be enhanced at the primary care level especially for appropriate referral and co-management at a referral centre (secondary or tertiary hospital).

Results indicate that the proposed hardware and algorithm could replace the manual counting method, uncomfortable nasal airflow sensor, chest band, and impedance pneumotachography often used in hospitals. The system also takes advantage of the prevalence of smartphone usage and increase the monitoring frequency of the current ECG of patients with critical illnesses.

Abnormal vital signs often predict a serious condition of acutely ill hospital patients in 24 hours. The notable fluctuations of respiratory rate (RR) are highly predictive of deteriorations among the vital signs measured. Traditional methods of detecting RR are performed by directly measuring the air flow in or out of the lungs or indirectly measuring the changes of the chest volume. These methods require the use of cumbersome devices, which may interfere with natural breathing, are uncomfortable, have frequently moving artifacts, and are extremely expensive. This study aims to estimate the RR from electrocardiogram (ECG) and photoplethysmogram (PPG) signals, which consist of passive and non-invasive acquisition modules. Algorithms have been validated by using PhysioNet’s Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II)’s patient datasets. RR estimation provides the value of mean absolute error (MAE) for ECG as 1.25 bpm (MIMIC-II) and 1.05 bpm for the acquired data. MAE for PPG is 1.15 bpm (MIMIC-II) and 0.90 bpm for the acquired data. By using 1-minute windows, this method reveals that the filtering method efficiently extracted respiratory information from the ECG and PPG signals. Smaller MAE for PPG signals results from fewer artifacts due to easy sensor attachment for the PPG because PPG recording requires only one-finger pulse oximeter sensor placement. However, ECG recording requires at least three electrode placements at three positions on the subject’s body surface for a single lead (lead II), thereby increasing the artifacts. A reliable technique has been proposed for RR estimation.

Blood pressure (BP) monitoring can be performed either invasively via arterial catheterization or non-invasively through a cuff sphygmomanometer. However, for conscious individuals, traditional cuff-based BP monitoring devices are often uncomfortable, intermittent, and impractical for frequent measurements. Continuous and non-invasive BP (NIBP) monitoring is currently gaining attention in the human health monitoring area due to its promising potentials in assessing the health status of an individual, enabled by machine learning (ML), for various purposes such as early prediction of disease and intervention treatment. This review presents the development of a non-invasive BP measuring tool called sphygmomanometer in brief, summarizes state-of-the-art NIBP sensors, and identifies extended works on continuous NIBP monitoring using commercial devices. Moreover, the NIBP predictive techniques including pulse arrival time, pulse transit time, pulse wave velocity, and ML are elaborated on the basis of bio-signals acquisition from these sensors. Additionally, the different BP values (systolic BP, diastolic BP, mean arterial pressure) of the various ML models adopted in several reported studies are compared in terms of the international validation standards developed by the Advancement of Medical Instrumentation (AAMI) and the British Hypertension Society (BHS) for clinically-approved BP monitors. Finally, several challenges and possible solutions for the implementation and realization of continuous NIBP technology are addressed.