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.
The recent advancement of dielectrophoresis (DEP)-enabled microfluidic platforms is opening new opportunities for potential use in cancer disease diagnostics. DEP is advantageous because of its specificity, low cost, small sample volume requirement, and tuneable property for microfluidic platforms. These intrinsic advantages have made it especially suitable for developing microfluidic cancer diagnostic platforms. This review focuses on a comprehensive analysis of the recent developments of DEP enabled microfluidic platforms sorted according to the target cancer cell. Each study is critically analyzed, and the features of each platform, the performance, added functionality for clinical use, and the types of samples, used are discussed. We address the novelty of the techniques, strategies, and design configuration used in improving on existing technologies or previous studies. A summary of comparing the developmental extent of each study is made, and we conclude with a treatment of future trends and a brief summary.
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).
[1] The ionospheric and geomagnetic response to the total eclipse of the Sun on 1 August 2008 over Northern Hemisphere has been examined using 14 GPS, three ISR radar, and three magnetometer ground-based stations. Three different approaches were employed to examine the TEC depletion occurrence at the GPS stations: determination of the TEC depletion parameters during the solar eclipse with respect the quiet day TEC variations, comparison of the total TEC (STEC) during the solar eclipse period with respect to quiet day TEC measurements for the same period of time, and determination of the average daily TEC obtained from eight GPS stations and compares the values with the average quiet day TEC at these stations. The GPS observations indicate obvious TEC depression occurrence at all stations with the values was varying between 11% and 40%. The observations show that TEC depression at most GPS stations started on the neck of the first contact of the eclipse followed by deeper negative deviation while the area of optical disk obscured getting larger. Periods of TEC depletion were also observed before the first contact time of solar eclipse and after the fourth contact of solar eclipse due to earlier and later obscuration of the solar corona before and after the eclipse observation time. The incoherent scatter radar observations at Svalbard, Tromso, and Sondrestrom also show clear depletion occurrence in electron density, electron temperature, ion velocity, and plasma cutoff frequency during the solar eclipse passage at these stations. Radar measurements show obvious difference in the ionospheric response between the E and F layers of ionosphere and between ion and electron temperature in the F layer. The geomagnetic field response to the solar eclipse at CBB, RESO, and NUR stations was examined by using two different techniques, first by comparing the daily variations of geomagnetic field during the eclipse period with the variations on the day before and day after the eclipse, and second by determination the D magnetic field with respect to the average quiet geomagnetic field. The results show obvious decrease in the total field, X and Z components of geomagnetic field and obvious increase in the Y component at both CBB and RESO stations. The depletion in X, Z, and total field was in the range between 15 and 28 nT while the increase in the Y component was 18-22 nT.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.