Automated Digitization of the Cardiotocography Signals from Real Scene Image of Binary Clinic Report

ObjectiveCardiotocography (CTG) is a popular clinical tool to assess foetal health status. Automatic CTG analysis can remove the judgement differences of inter- and intra- doctors. However, absence of CTG database has hindered the development of automatic CTG analysis based on deep learning. Therefore, digitization of CTG signal from clinic report is an important way to enrich CTG database, and in turn promote the automatic CTG analysis.MethodThe proposed digitization method extracts digital signal from the commonly used binary CTG paper reports. An adaptive region positioning algorithm based on statistical calculation is used to locate signal regions. Then, by deducing the dynamic minimal weight sum in theory, methods based on statistical calculation and on the weight sum are designed to remove grid lines. Next, according to different breakpoint types and signal line trends, different signal reconstruction methods are formulated. This realize extracting the signal line from binary background grid lines. Finally, a calibration method based on segmented sampling is designed to reduce calibration error due to smartphone lens distortion.ResultsThe experimental results show that the correlation coefficients of FHR and UC of proposed method both reached 0.98. After three expert gynaecologists's evaluations, there are no clinically relevant differences were identified between the extracted signals and the reference ones.     

Antepartum fetal heart rate feature extraction and classification using empirical mode decomposition and support vector machine

Background  

Cardiotocography (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'.     

Comparison of a Novel Computerized Analysis Program and Visual Interpretation of Cardiotocography

Objective

To compare a novel computerized analysis program with visual cardiotocography (CTG) interpretation results.

Methods

Sixty-two intrapartum CTG tracings with 20- to 30-minute sections were independently interpreted using a novel computerized analysis program, as well as the visual interpretations of eight obstetricians, to evaluate the baseline fetal heart rate (FHR), baseline FHR variability, number of accelerations, number/type of decelerations, uterine contraction (UC) frequency, and the National Institute of Child Health and Human Development (NICHD) 3-Tier FHR classification system.

Results

There was no significant difference in interobserver variation after adding the components of computerized analysis to results from the obstetricians'' visual interpretations, with excellent agreement for the baseline FHR (ICC 0.91), the number of accelerations (ICC 0.85), UC frequency (ICC 0.97), and NICHD category I (kappa statistic 0.91); good agreement for baseline variability (kappa statistic 0.68), the numbers of early decelerations (ICC 0.78) and late decelerations (ICC 0.67), category II (kappa statistic 0.78), and overall categories (kappa statistic 0.80); and moderate agreement for the number of variable decelerations (ICC 0.60), and category III (kappa statistic 0.50).

Conclusions

This computerized analysis program is not inferior to visual interpretation, may improve interobserver variations, and could play a vital role in prenatal telemedicine.     

Archaeal Nucleosome Positioning by CTG Repeats

DNA shape recognition determines the preferred binding sites for sequence-independent DNA binding proteins, and here we document that archaeal histones assemble archaeal nucleosomes in vitro centered preferentially within (CTG)₆ and (CTG)₈ repeats, close to junctions with flanking mixed-sequence DNA. Archaeal nucleosomes were not positioned by (CTG)₄-, (CTG)₅-, or (CTG)₃AA(CTG)₃-containing DNA sequences. The features of CTG repeat-containing sequences that direct eucaryal nucleosome positioning may also be similarly recognized by archaeal histones.     

A Comparison of ECG Signal Pre-processing Using FrFT,FrWT and IPCA for Improved Analysis

ObjectiveElectrocardiogram (ECG) is a diagnostic tool for recording electrical activities of the human heart non-invasively. It is detected by electrodes placed on the surface of the skin in a conductive medium. In medical applications, ECG is used by cardiologists to observe heart anomalies (cardiovascular diseases) such as abnormal heart rhythms, heart attacks, effects of drug dosage on subject's heart and knowledge of previous heart attacks. Recorded ECG signal is generally corrupted by various types of noise/distortion such as cardiac (isoelectric interval, prolonged depolarization and atrial flutter) or extra cardiac (respiration, changes in electrode position, muscle contraction and power line noise). These factors hide the useful information and alter the signal characteristic due to low Signal-to-Noise Ratio (SNR). In such situations, any failure to judge the ECG signal correctly may result in a delay in the treatment and harm a subject (patient) health. Therefore, appropriate pre-processing technique is necessary to improve SNR to facilitate better treatment to the subject. Effects of different pre-processing techniques on ECG signal analysis (based on R-peaks detection) are compared using various Figures of Merit (FoM) such as sensitivity (Se), accuracy (Acc) and detection error rate (DER) along with SNR.MethodsIn this research article, a new fractional wavelet transform (FrWT) has been proposed as a pre-processing technique in order to overcome the disadvantages of other existing commonly used techniques viz. wavelet transform (WT) and the fractional Fourier transform (FrFT). The proposed FrWT technique possesses the properties of multiresolution analysis and represents signal in the fractional domain which consists of representation in terms of rotation of signals in the time–frequency plane. In the literature, ECG signal analysis has been improvised using statistical pre-processing techniques such as principal component analysis (PCA), and independent component analysis (ICA). However, both PCA and ICA are prone to suffer from slight alterations in either signal or noise, unless the basis functions are prepared with a worldwide set of ECG. Independent Principal Component Analysis (IPCA) has been used to overcome this shortcoming of PCA and ICA. Therefore, in this paper three techniques viz. FrFT, FrWT and IPCA are selected for comparison in pre-processing of ECG signals.ResultsThe selected methods have been evaluated on the basis of SNR, Se, Acc and DER of the detected ECG beats. FrWT yields the best results among all the methods considered in this paper; 34.37dB output SNR, 99.98% Se, 99.96% Acc, and 0.036% DER. These results indicate the quality of biology-related information retained from the pre-processed ECG signals for identifying different heart abnormalities.ConclusionCorrect analysis of the acquired ECG signal is the main challenge for cardiologist due to involvement of various types of noises (high and low frequency). Twenty two real time ECG records have been evaluated based on various FoM such as SNR, Se, Acc and DER for the proposed FrWT and existing FrFT and IPCA preprocessing techniques. Acquired real-time ECG database in normal and disease situations is used for the purpose. The values of FoMs indicate high SNR and better detection of R-peaks in a ECG signal which is important for the diagnosis of cardiovascular disease. The proposed FrWT outperforms all other techniques and holds both analytical attributes of the actual ECG signal and alterations in the amplitudes of various ECG waveforms adequately. It also provides signal portrayals in the time-fractional-frequency plane with low computational complexity enabling their use practically for versatile applications.     

Flexible Analytic Wavelet Transform Based Features for Physical Action Identification Using sEMG Signals

ObjectivesElectromyography (EMG) is recording of the electrical activity produced by skeletal muscles. The classification of the EMG signals for different physical actions can be useful in restoring some or all of the lost motor functionalities in these individuals. Accuracy in classifying the EMG signal indicates efficient control of prosthesis.Material and methodsThe flexible analytic wavelet transform (FAWT) is used for classification of surface electromyography (sEMG) signals for identification of physical actions. FAWT is an efficient method for decomposition of sEMG signal into eight sub-bands, features namely neg-entropy, mean absolute value (MAV), variance (VAR), modified mean absolute value type 1 (MAV1), waveform length (WL), simple square integral (SSI), Tsallis entropy, integrated EMG (IEMG) are extracted from the sub-bands. Extracted features are fed into an extreme learning machine (ELM) classifier with sigmoid activation function.ResultsComprehensive experiments are conducted on the input sEMG signals and the accuracy, sensitivity and specificity scores are used for performance measurement. Experiments showed that among all sub-bands, the seventh sub-band provided the best performance where the recorded accuracy, sensitivity and specificity values were 99.36%, 99.36% and 99.93%, respectively. The comparison results showed best efficiency of proposed method as compared to other methods on the same dataset.ConclusionThis paper investigates the usage of the FAWT and ELM on sEMG signal classification. The results show that the proposed method is quite efficient in classification of the sEMG signals. It is also observed that the seventh sub-band of the FAWT provides the best discrimination property. In the future works, recent wavelet transform methods will be used for improving the classification performance.     

58 Packaging trinucleotide repeats: the effect of CAG/CTG repeats on nucleosome formation

In neurological diseases such as fragile X syndrome, spinal and bulbar muscular atrophy, myotonic dystrophy, and Huntington’s disease, the molecular basis of pathogenicity is the presence of an expanded trinucleotide repeat (TNR) tract (Ashley & Warren, 1995). TNRs implicated in many of these diseases are composed of CAG/CTG repeats. For example, in healthy individuals 5–35, CAG/CTG TNR repeats are present in the huntingtin gene. However, individuals with 40 or greater repeats will develop Huntington’s disease (Andrew et al., 1993). We are particularly interested in how these TNR sequences are packaged in chromatin. Recent evaluations of CAG/CTG TNR sequences in our laboratory have demonstrated that the repeats increase the propensity for the DNA sequences to incorporate into nucleosomes, where nucleosomes represent the minimal unit of packaging in chromatin (Volle & Delaney, 2012). In this work, we are interested in determining the minimum number of CAG/CTG repeats required to confer a significant increase in nucleosome incorporation relative to sequences that lack the TNR sequence. By defining the changes imposed on these fundamental interactions by the presence of a CAG/CTG repeat tract, we will gain insight into the possible interactions that allow for the expansion of these TNR tracts.     

Mate searching in Ennya maculicornis (Membracidae: Polyglyptini) initiated by females: behavioural and acoustic descriptions

1. In treehoppers in which courtship has been studied, males initiate the search for females by periodically emitting a vibrational signal. The responses by the female are used by males as a beacon and give rise to a duet. 2. Courtship and mating of the treehopper Ennya maculicornis were characterised through the simultaneous recording of vibrational signals and the behaviour of males and females in an arena. 3. In E. maculicornis, female initiated mate searching. Females produced two types of signals during the this process: (i) a signal that preceded the approach by the male and (ii) a signal that preceded mating. Males emitted two signals associated with two stereotyped body movements: (i) a signal produced as a response to the first signal emitted by the female, involving a change in the male's locomotory mode and the approach to the female, and (ii) a signal produced after finding and holding on to the female, involving simultaneous abdomen raising and wing fluttering. These signals were repeated several times before the female emitted the second signal. The four signalling patterns were observed in all recordings in which mating was observed. When any of the signals was missing, mating did not occur. 4. Female‐biased sex ratios in E. maculicornis, along with iteroparity, are suggested to explain the initiation of mate searching behaviour by females. A comparison of data with that from other treehoppers indicates that vibrational signals and their associated behaviour are more diverse among treehoppers than has been appreciated previously.     

First automatic passive acoustic tool for monitoring two species of procellarides (Pterodroma baraui and Puffinus bailloni) on Reunion Island,Indian Ocean

Here are proposed two automatic detectors of Barau's petrel (Pterodroma baraui) and tropical shearwater (Puffinus bailloni) vocalisations in noisy audio recordings (1) trained with a low number of positive training instances, and (2) whose performances would be the highest possible. To do so, acoustic recordings were performed in one Barau's petrel colony between February and May 2014 (85 h) and in two tropical shearwater colonies in March and April (21 h). Manual and automatic methods of segmentation were combined. Manual segmentation allowed (1) to miss a very few number of positive segments and (2) to avoid introducing false positive instances. Automatic segmentation provided quickly a diversified set of negative instances. Manual labelling must be regarded as an investment, for current and future works. A random forest classifier and classical methods of acoustic signal characterisation (cepstral coefficients, spectral moments, etc.) were tested. Best models were able to discriminate each target species calls from other sounds of its colony with F1 scores of 88% (Barau's petrel, 1015 samples) and 85% (tropical shearwater, 1217 samples). The acoustic monitoring of nocturnal burrow-nesting seabirds based on (1) data collected by autonomous recording units in harsh, windy and wet environments and (2) automatic analysis tools is feasible. The size of our database was limited. Consequently further works will be necessary to study robustness of models on long time-series data.     

Effects of liquid stimuli on dual-axis swallowing accelerometry signals in a healthy population

Background  

Dual-axis swallowing accelerometry has recently been proposed as a tool for non-invasive analysis of swallowing function. Although swallowing is known to be physiologically modifiable by the type of food or liquid (i.e., stimuli), the effects of stimuli on dual-axis accelerometry signals have never been thoroughly investigated. Thus, the objective of this study was to investigate stimulus effects on dual-axis accelerometry signal characteristics. Signals were acquired from 17 healthy participants while swallowing 4 different stimuli: water, nectar-thick and honey-thick apple juices, and a thin-liquid barium suspension. Two swallowing tasks were examined: discrete and sequential. A variety of features were extracted in the time and time-frequency domains after swallow segmentation and pre-processing. A separate Friedman test was conducted for each feature and for each swallowing task.     

Multi-Atlas Based Adaptive Active Contour Model with Application to Organs at Risk Segmentation in Brain MR Images

BackgroundAccurate delineation of organs at risk (OARs) is critical in radiotherapy. Manual delineation is tedious and suffers from both interobserver and intraobserver variability. Automatic segmentation of brain MR images has a wide range of applications in brain tumor radiotherapy. In this paper, we propose a multi-atlas based adaptive active contour model for OAR automatic segmentation in brain MR images.MethodsThe proposed method consists of two parts: multi-atlas based OAR contour initiation and an adaptive edge and local region based active contour evolution. In the adaptive active contour model, we define an energy functional with an adaptive edge intensity fitting force which is responsible for evaluating contour inwards or outwards, and a local region intensity fitting force which guides the evolution of the contour.ResultsExperimental results show that the proposed method achieved more accurate segmentation results in brainstem, eyes and lens automatic segmentation with the Dice Similar Coefficient (DSC) value of 87.19%, 91.96%, 77.11% respectively. Besides, the dosimetric parameters also demonstrate the high consistency of the manual OAR delineations and the auto segmentation results of the proposed method in brain tumor radiotherapy.ConclusionsThe geometric and dosimetric evaluations show the desirable performance of the proposed method on the application of OARs segmentations in brain tumor radiotherapy.     

Continuous fetal heart rate monitoring during late gestation in cattle by means of Doppler ultrasonography: reference values obtained by computer-assisted analysis

Continuous fetal heart rate (FHR) monitoring using transabdominal Doppler ultrasonography can be assumed to provide information about the viability of the bovine fetus during late gestation, as has been found in humans. To be able to recognize unfavourable fetal conditions, first the normal ranges of FHR parameters in cattle should be established. Therefore, in this study we aimed to determine the normal ranges of computerized FHR parameters, like basal fetal heart rate (BHR), number of accelerations and decelerations per hour and short and long term variation (STV and LTV) during the last 3 weeks before calving (n = 21 cows). Each cow had one recording in each of three episodes of 7 days before parturition. As recording time in the cow is limited, we also studied whether these FHR parameters differ between recordings of 30 and 60 min duration (n = 31 pairs of recordings). The outcomes of FHR recordings with a duration of 30 or 60 min did not differ significantly, except for a higher percentage of signal loss in the 60 min recordings. Therefore, determination of normal ranges was performed in 30 min recordings. BHR decreased from 3 to 2 weeks (114 to 109 bpm; P < 0.0001) before parturition and then remained constant until 2 days before calving. The mean number of accelerations per hour ranged between 4.4 and 5.0 h(-1) and did not change significantly with time. Compared to 3 weeks before parturition, STV was significantly higher at 2 weeks (P < 0.05), but not at 1 week before parturition (8.1, 10.0, and 9.2 ms, respectively). Changes in LTV showed a time course comparable to that of STV, but significance was not reached (51.4, 58.6, and 58.4 ms for respectively 3, 2 and 1 weeks before parturition). No decelerations were found during the period understudy. In conclusion, this study has provided normal ranges of bovine computerized FHR parameters during the last 3 weeks of gestation, allowing a comparison with data from cows with compromised gestations in future.     

RECENT BIOACOUSTIC PUBLICATIONS (mainly 1993)

ABSTRACT

Some acoustic signals produced by small insects are very low in amplitude and attenuate rapidly with distance. To achieve high quality recordings with such signals, the use of specialised microphones or of sound insulation chambers is necessary. This paper presents a simple and efficient method for the recording of acoustic signals emitted by small sources. Its principle is based upon the use of two simultaneous digital recordings from two microphones: one records the ambient noise while the other records the ambient noise plus the signal to analyse. Both these recordings are converted into digital files and then a simple subtraction between the two isolates the signal with a good signal-to-noise ratio. With this method of background noise removal, the recording of low amplitude sounds in an uninsulated room with common microphones becomes possible. We have applied this method to the study of 12 complete courtships of Drosophila melanogaster and particularly to the analysis of pulse sounds produced by the male in presence of a female. The study focuses mainly on the rhythm of production of pulse trains over the course of the courtship.     

The Role of XPG in Processing (CAG)n/(CTG)n DNA Hairpins

Background

During DNA replication or repair, disease-associated (CAG)_n/(CTG)_n expansion can result from formation of hairpin structures in the repeat tract of the newly synthesized or nicked DNA strand. Recent studies identified a nick-directed (CAG)_n/(CTG)_n hairpin repair (HPR) system that removes (CAG)_n/(CTG)_n hairpins from human cells via endonucleolytic incisions. Because the process is highly similar to the mechanism by which XPG and XPF endonucleases remove bulky DNA lesions during nucleotide excision repair, we assessed the potential role of XPG in conducting (CAG)_n/(CTG)_n HPR.

Results

To determine if the XPG endonuclease is involved in (CAG)_n/(CTG)_n hairpin removal, two XPG-deficient cell lines (GM16024 and AG08802) were examined for their ability to process (CAG)_n/(CTG)_n hairpins in vitro. We demonstrated that the GM16024 cell line processes all hairpin substrates as efficiently as HeLa cells, and that the AG08802 cell line is partially defective in HPR. Analysis of repair intermediates revealed that nuclear extracts from both XPG-deficient lines remove CAG/CTG hairpins via incisions, but the incision products are distinct from those generated in HeLa extracts. We also show that purified recombinant XPG protein greatly stimulates HPR in XPG-deficient extracts by promoting an incision 5' to the hairpin.

Conclusions

Our results strongly suggest that 1) human cells possess multiple pathways to remove (CAG)_n/(CTG)_n hairpins located in newly synthesized (or nicked) DNA strand; and 2) XPG, although not essential for (CAG)_n/(CTG)_n hairpin removal, stimulates HPR by facilitating a 5' incision to the hairpin. This study reveals a novel role for XPG in genome-maintenance and implicates XPG in diseases caused by trinucleotide repeat expansion.     

1D-CADCapsNet: One dimensional deep capsule networks for coronary artery disease detection using ECG signals

PurposeCardiovascular disease (CVD) is a leading cause of death globally. Electrocardiogram (ECG), which records the electrical activity of the heart, has been used for the diagnosis of CVD. The automated and robust detection of CVD from ECG signals plays a significant role for early and accurate clinical diagnosis. The purpose of this study is to provide automated detection of coronary artery disease (CAD) from ECG signals using capsule networks (CapsNet).MethodsDeep learning-based approaches have become increasingly popular in computer aided diagnosis systems. Capsule networks are one of the new promising approaches in the field of deep learning. In this study, we used 1D version of CapsNet for the automated detection of coronary artery disease (CAD) on two second (95,300) and five second-long (38,120) ECG segments. These segments are obtained from 40 normal and 7 CAD subjects. In the experimental studies, 5-fold cross validation technique is employed to evaluate performance of the model.ResultsThe proposed model, which is named as 1D-CADCapsNet, yielded a promising 5-fold diagnosis accuracy of 99.44% and 98.62% for two- and five-second ECG signal groups, respectively. We have obtained the highest performance results using 2 s ECG segment than the state-of-art studies reported in the literature.Conclusions1D-CADCapsNet model automatically learns the pertinent representations from raw ECG data without using any hand-crafted technique and can be used as a fast and accurate diagnostic tool to help cardiologists.     

A pipeline to quantify spinal cord atrophy with deep learning: Application to differentiation of MS and NMOSD patients

PurposeQuantitative measurement of various anatomical regions of the brain and spinal cord (SC) in MRI images are used as unique biomarkers to consider progress and effects of demyelinating diseases of the central nervous system. This paper presents a fully-automated image processing pipeline which quantifies the SC volume of MRI images.MethodsIn the proposed pipeline, after conducting some pre-processing tasks, a deep convolutional network is utilized to segment the spinal cord cross-sectional area (SCCSA) of each slice. After full segmentation, certain extra slices interpolate between each two adjacent slices using the shape-based interpolation method. Then, a 3D model of the SC is reconstructed, and, by counting the voxels of it, the SC volume is calculated. The performance of the proposed method for the SCCSA segmentation is evaluated on 140 MRI images. Subsequently, to demonstrate the application of the proposed pipeline, we study the differentiations of SC atrophy between 38 Multiple Sclerosis (MS) and 25 Neuromyelitis Optica Spectrum Disorder (NMOSD) patients.ResultsThe experimental results of the SCCSA segmentation indicate that the proposed method, adapted by Mask R-CNN, presented the most satisfactory result with the average Dice coefficient of 0.96. For this method, statistical metrics including sensitivity, specificity, accuracy, and precision are 97.51%, 99.98%, 99.92%, and 98.04% respectively. Moreover, the t-test result (p-value = 0.00089) verified a significant difference between the SC atrophy of MS and NMOSD patients.ConclusionThe pipeline efficiently quantifies the SC volume of MRI images and can be utilized as an affordable computer-aided tool for diagnostic purposes.     

Msh3 is a limiting factor in the formation of intergenerational CTG expansions in DM1 transgenic mice

The CTG repeat involved in myotonic dystrophy is one of the most unstable trinucleotide repeats. However, the molecular mechanisms underlying this particular form of genetic instability—biased towards expansions—have not yet been completely elucidated. We previously showed, with highly unstable CTG repeat arrays in DM1 transgenic mice, that Msh2 is required for the formation of intergenerational and somatic expansions. To identify the partners of Msh2 in the formation of intergenerational CTG repeat expansions, we investigated the involvement of Msh3 and Msh6, partners of Msh2 in mismatch repair. Transgenic mice with CTG expansions were crossed with Msh3- or Msh6-deficient mice and CTG repeats were analysed after maternal and paternal transmissions. We demonstrated that Msh3 but not Msh6 plays also a key role in the formation of expansions over successive generation. Furthermore, the absence of one Msh3 allele was sufficient to decrease the formation of expansions, indicating that Msh3 is rate-limiting in this process. In the absence of Msh6, the frequency of expansions decreased only in maternal transmissions. However, the significantly lower levels of Msh2 and Msh3 proteins in Msh6 -/- ovaries suggest that the absence of Msh6 may have an indirect effect.     

Myotonic dystrophy type 1-associated CTG repeats disturb the expression and subcellular distribution of microtubule-associated proteins MAP1A, MAP2, and MAP6/STOP in PC12 cells

To study the effect of DM1-associated CTG repeats on neuronal function, we developed a PC12 cell-based model that constitutively expresses the DMPK gene 3′-untranslated region with 90 CTG repeats (CTG90 cells). As CTG90 cells exhibit impaired neurite outgrowth and as microtubule-associated proteins (MAPs) are crucial for microtubule stability, we analyzed whether MAPs are a target of CTG repeats. NGF induces mRNA expression of Map2, Map1a and Map6 in control cells (PC12 cells transfected with the empty vector), but this induction is abolished for Map2 and Map1a in CTG90 cells. MAP2 and MAP6/STOP proteins decrease in NGF-treated CTG90 cells, whereas MAP1A increases. Data suggest that CTG repeats might alter somehow the expression of MAPs, which appears to be related with CTG90 cell-deficient neurite outgrowth. Decreased MAP2 levels found in the hippocampus of a DM1 mouse model indicates that targeting of MAPs expression by CTG repeats might be relevant to DM1.