Volatile components from Exocarpium Citri Grandis (ECG) were, respectively, extracted by three methods, that is, steam distillation (SD), headspace solid-phase microextraction (HS-SPME), and solvent extraction (SE). A total of 81 compounds were identified by gas chromatography-mass spectrometry including 77 (SD), 56 (HS-SPME), and 48 (SE) compounds, respectively. Despite of the extraction metho...

A new method based on least square support vector machine (LSSVM) combined with FastICA is proposed to extract the fetal electrocardiogram (FECG) from the abdominal signals of a pregnant woman. Firstly, the LSSVM is applied to estimate the maternal electrocardiogram (MECG) component in the multiplex abdominal signals. Then the optimal estimation of multiplex noise-added FECG is obtained by remo...

Unsupervised mining of electrocardiography (ECG) time series is a crucial task in biomedical applications. To have efficiency of the clustering results, the prominent features extracted from preprocessing analysis on multiple ECG time series need to be investigated. In this paper, a Harmonic Linear Dynamical System is applied to discover vital prominent features via mining the evolving hidden d...

ST-analysis of the fetal electrocardiogram (ECG) (STAN(®)) combined with cardiotocography (CTG) for intrapartum fetal monitoring has been developed following many years of animal research. Changes in the ST-segment of the fetal ECG correlated with fetal hypoxia occurring during labor. In 1993 the first randomized controlled trial (RCT), comparing CTG with CTG + ST-analysis was published. STAN(®...

Wearable ECG sensors are growing in their popularity day by day. These ECG sensors run on batteries, hence carry a limited battery life. The ECG sensors are also used to monitor the fetal health, which are called FECG sensors. These sensors are used with the pregnant women for the fetal ECG monitoring to avoid the critical health hazards. In this research, the signal optimized for its easy tran...

Consider a set of multiple, multimodal sensors capturing a complex system or a physical phenomenon of interest. Our primary goal is to distinguish the underlying sources of variability manifested in the measured data. The first step in our analysis is to find the common source of variability present in all sensor measurements. We base our work on a recent paper, which tackles this problem with ...

This paper illustrates the use of a combined neural network model for classification of electrocardiogram (ECG) beats. We present a trainable neural network ensemble approach to develop customized electrocardiogram beat classifier in an effort to further improve the performance of ECG processing and to offer individualized health care. We process a three stage technique for detection of prematu...

Different methods have been projected and used for ECG feature extraction with a substantial percentage of precise detection. However, the problem remains exposed especially regarding higher detection precision in noisy ECG. In this work, we have developed an algorithm based using LabVIEW 8.5. LabVIEW (Laboratory Virtual Instrument Engineering Workbench) is a graphical user interface design lan...

The effects of ethanol concentration (0%-100%, v/v), solid-to-solvent ratio (1:10-1:60, w/v) and extraction time (30-180 min) on the extraction of polyphenols from agarwood (Aquilaria crassna) were examined. Total phenolic content (TPC), total flavonoid content (TFC) and total flavanol (TF) assays and HPLC-DAD were used for the determination and quantification of polyphenols, flavanol gallates ...

The study of electrocardiogram (ECG) waveform amplitudes, timings and patterns has been the subject of intense research, for it provides a deep insight into the diagnostic features of the heart's functionality. In some recent works, a Bayesian filtering paradigm has been proposed for denoising and compression of ECG signals. In this paper, it is shown that this framework may be effectively used...