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Sayed Ismail, Sharifah Noor Masidayu, Nor Azlina Ab. Aziz, Siti Zainab Ibrahim, Sophan Wahyudi Nawawi, Salem Alelyani, Mohamed Mohana, and Lee Chia Chun. "Evaluation of electrocardiogram: numerical vs. image data for emotion recognition system." F1000Research 10 (May 30, 2022): 1114. http://dx.doi.org/10.12688/f1000research.73255.2.
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Background: The electrocardiogram (ECG) is a physiological signal used to diagnose and monitor cardiovascular disease, usually using 2- D ECG. Numerous studies have proven that ECG can be used to detect human emotions using 1-D ECG; however, ECG is typically captured as 2-D images rather than as 1-D data. There is still no consensus on the effect of the ECG input format on the accuracy of the emotion recognition system (ERS). The ERS using 2-D ECG is still inadequately studied. Therefore, this study compared ERS performance using 1-D and 2-D ECG data to investigate the effect of the ECG input format on the ERS. Methods: This study employed the DREAMER dataset, which contains 23 ECG recordings obtained during audio-visual emotional elicitation. Numerical data was converted to ECG images for the comparison. Numerous approaches were used to obtain ECG features. The Augsburg BioSignal Toolbox (AUBT) and the Toolbox for Emotional feature extraction from Physiological signals (TEAP) extracted features from numerical data. Meanwhile, features were extracted from image data using Oriented FAST and rotated BRIEF (ORB), Scale Invariant Feature Transform (SIFT), KAZE, Accelerated-KAZE (AKAZE), Binary Robust Invariant Scalable Keypoints (BRISK), and Histogram of Oriented Gradients (HOG). Dimension reduction was accomplished using linear discriminant analysis (LDA), and valence and arousal were classified using the Support Vector Machine (SVM). Results: The experimental results show 1-D ECG-based ERS achieved 65.06% of accuracy and 75.63% of F1 score for valence, and 57.83% of accuracy and 44.44% of F1-score for arousal. For 2-D ECG-based ERS, the highest accuracy and F1-score for valence were 62.35% and 49.57%; whereas, the arousal was 59.64% and 59.71%. Conclusions: The results indicate that both inputs work comparably well in classifying emotions, which demonstrates the potential of 1-D and 2-D as input modalities for the ERS.
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Zhang, Yin-Han, Jerry Bryant, Fan-Lin Kong, Dong-Fang Yu, Richard Mendez, E. Edmund Kim, and David J. Yang. "Molecular Imaging of Mesothelioma withT99mc-ECG andG68a-ECG." Journal of Biomedicine and Biotechnology 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/232863.
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We have developed ethylenedicysteine-glucosamine (ECG) as an alternative to18F-fluoro-2-deoxy-D-glucose (18F-FDG) for cancer imaging. ECG localizes in the nuclear components of cells via the hexosamine biosynthetic pathway. This study was to evaluate the feasibility of imaging mesothelioma withT99mc-ECG andG68a-ECG. ECG was synthesized from thiazolidine-4-carboxylic acid and 1,3,4,6-tetra-O-acetyl-2-amino-D-glucopyranose, followed by reduction in sodium and liquid ammonia to yield ECG (52%). ECG was chelated withT99mc/tin (II) andG68a/69Ga chloride forin vitroandin vivostudies in mesothelioma. The highest tumor uptake ofT99mc-ECG is 0.47 at 30 min post injection, and declined to 0.08 at 240 min post injection. Tumor uptake (%ID/g), tumor/lung, tumor/blood, and tumor/muscle count density ratios forT99mc-ECG (30–240 min) were0.47±0.06to0.08±0.01;0.71±0.07to0.85±0.04;0.47±0.03to0.51±0.01, and3.49±0.24to5.06±0.25; forG68a-ECG (15–60 min) were0.70±0.06to0.92±0.08;0.64±0.05to1.15±0.08;0.42±0.03to0.67±0.07, and3.84±0.52to7.00±1.42; for18F-FDG (30–180 min) were1.86±0.22to1.38±0.35;3.18±0.44to2.92±0.34,4.19±0.44to19.41±2.05and5.75±2.55to3.33±0.65, respectively. Tumor could be clearly visualized withT99mc-ECG andG68a-ECG in mesothelioma-bearing rats.T99mc-ECG andG68a-ECG showed increased uptake in mesothelioma, suggesting they may be useful in diagnosing mesothelioma and also monitoring therapeutic response.
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Tanoh, Ian-Christopher, and Paolo Napoletano. "A Novel 1-D CCANet for ECG Classification." Applied Sciences 11, no. 6 (March 19, 2021): 2758. http://dx.doi.org/10.3390/app11062758.
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This paper puts forward a 1-D convolutional neural network (CNN) that exploits a novel analysis of the correlation between the two leads of the noisy electrocardiogram (ECG) to classify heartbeats. The proposed method is one-dimensional, enabling complex structures while maintaining a reasonable computational complexity. It is based on the combination of elementary handcrafted time domain features, frequency domain features through spectrograms and the use of autoregressive modeling. On the MIT-BIH database, a 95.52% overall accuracy is obtained by classifying 15 types, whereas a 95.70% overall accuracy is reached when classifying 7 types from the INCART database.
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McClean, Gavin, Nathan R. Riding, Guido Pieles, Victoria Watt, Carmen Adamuz, Sanjay Sharma, Keith P. George, David Oxborough, and Mathew G. Wilson. "Diagnostic accuracy and Bayesian analysis of new international ECG recommendations in paediatric athletes." Heart 105, no. 2 (September 18, 2018): 152–59. http://dx.doi.org/10.1136/heartjnl-2018-313466.
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ObjectiveHistorically, electrocardiographic (ECG) interpretation criteria for athletes were only applicable to adults. New international recommendations now account for athletes ≤16 years, but their clinical appropriateness is unknown. We sought to establish the diagnostic accuracy of new international ECG recommendations against the Seattle criteria and 2010 European Society of Cardiology (ESC) recommendations in paediatric athletes using receiver operator curve analysis. Clinical context was calculated using Bayesian analysis.Methods876 Arab and 428 black male paediatric athletes (11–18 years) were evaluated by medical questionnaire, physical examination, ECG and echocardiographic assessment. ECGs were retrospectively analysed according to the three criteria.ResultsThirteen (1.0%) athletes were diagnosed with cardiac pathology that may predispose to sudden cardiac arrest/death (SCA/D) (8 (0.9%) Arab and (5 (1.2%) black)). Diagnostic accuracy was poor (0.68, 95% CI 0.54 to 0.82) for 2010 ESC recommendations, fair (0.70, 95% CI 0.54 to 0.85) for Seattle criteria and fair (0.77, 95% CI 0.61 to 0.93) for international recommendations. False-positive rates were 41.0% for 2010 ESC recommendations, 21.8% for Seattle criteria and 6.8% for international recommendations. International recommendations provided a positive (+LR) and negative (−LR) post-test likelihood ratio of 9.0 (95% CI 5.1 to 13.1) and 0.4 (95% CI 0.2 to 0.7), respectively.ConclusionIn Arab and black male paediatric athletes, new international recommendations outperform both the Seattle criteria and 2010 ESC recommendations, reducing false positive rates, while yielding a ‘fair’ diagnostic accuracy for cardiac pathology that may predispose to SCA/D. In clinical context, the ‘chance’ of detecting cardiac pathology within a paediatric male athlete with a positive ECG (+LR=9.0) was 8.3%, whereas a negative ECG (−LR=0.4) was 0.4%.
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Herraiz, Álvaro Huerta, Arturo Martínez-Rodrigo, Vicente Bertomeu-González, Aurelio Quesada, José J. Rieta, and Raúl Alcaraz. "A Deep Learning Approach for Featureless Robust Quality Assessment of Intermittent Atrial Fibrillation Recordings from Portable and Wearable Devices." Entropy 22, no. 7 (July 1, 2020): 733. http://dx.doi.org/10.3390/e22070733.
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Atrial fibrillation (AF) is the most common heart rhythm disturbance in clinical practice. It often starts with asymptomatic and very short episodes, which are extremely difficult to detect without long-term monitoring of the patient’s electrocardiogram (ECG). Although recent portable and wearable devices may become very useful in this context, they often record ECG signals strongly corrupted with noise and artifacts. This impairs automatized ulterior analyses that could only be conducted reliably through a previous stage of automatic identification of high-quality ECG intervals. So far, a variety of techniques for ECG quality assessment have been proposed, but poor performances have been reported on recordings from patients with AF. This work introduces a novel deep learning-based algorithm to robustly identify high-quality ECG segments within the challenging environment of single-lead recordings alternating sinus rhythm, AF episodes and other rhythms. The method is based on the high learning capability of a convolutional neural network, which has been trained with 2-D images obtained when turning ECG signals into wavelet scalograms. For its validation, almost 100,000 ECG segments from three different databases have been analyzed during 500 learning-testing iterations, thus involving more than 320,000 ECGs analyzed in total. The obtained results have revealed a discriminant ability to detect high-quality and discard low-quality ECG excerpts of about 93%, only misclassifying around 5% of clean AF segments as noisy ones. In addition, the method has also been able to deal with raw ECG recordings, without requiring signal preprocessing or feature extraction as previous stages. Consequently, it is particularly suitable for portable and wearable devices embedding, facilitating early detection of AF as well as other automatized diagnostic facilities by reliably providing high-quality ECG excerpts to further processing stages.
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Ullah, Amin, Syed Muhammad Anwar, Muhammad Bilal, and Raja Majid Mehmood. "Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image Representation." Remote Sensing 12, no. 10 (May 25, 2020): 1685. http://dx.doi.org/10.3390/rs12101685.
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The electrocardiogram (ECG) is one of the most extensively employed signals used in the diagnosis and prediction of cardiovascular diseases (CVDs). The ECG signals can capture the heart’s rhythmic irregularities, commonly known as arrhythmias. A careful study of ECG signals is crucial for precise diagnoses of patients’ acute and chronic heart conditions. In this study, we propose a two-dimensional (2-D) convolutional neural network (CNN) model for the classification of ECG signals into eight classes; namely, normal beat, premature ventricular contraction beat, paced beat, right bundle branch block beat, left bundle branch block beat, atrial premature contraction beat, ventricular flutter wave beat, and ventricular escape beat. The one-dimensional ECG time series signals are transformed into 2-D spectrograms through short-time Fourier transform. The 2-D CNN model consisting of four convolutional layers and four pooling layers is designed for extracting robust features from the input spectrograms. Our proposed methodology is evaluated on a publicly available MIT-BIH arrhythmia dataset. We achieved a state-of-the-art average classification accuracy of 99.11%, which is better than those of recently reported results in classifying similar types of arrhythmias. The performance is significant in other indices as well, including sensitivity and specificity, which indicates the success of the proposed method.
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Hamad alhussainy, Aqeel M., and Ammar D. Jasim. "ECG signal classification based on Deep Learning by using Convolutional Neural Network (CNN)." Iraqi Journal of Information & Communications Technology 3, no. 3 (December 31, 2020): 12–23. http://dx.doi.org/10.31987/ijict.3.3.106.
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Cardiovascular diseases (CVDs) are consider the main cause of death today According to World Health Organization (WHO),and because that ECG signal is very important tool in monitoring and diagnosis of these disease , different automatic methods were proposed based on this signal. [1]. The manual analysis of ECG signals is suffered different challenges such as differeculty of detecting and classify waveform of this signal, So, many machine learning methods are explored to describe the anomalies ECG signal accurately . Deep learning (DL) can be used in ECG classification, it can improve the quality of the automatic classification system. In this paper , we have proposed a deep learning classification system by using different layers of convolution, rectifier and pooling operations that can be used to increase feature extraction of ECG signal.
We have proposed two models, one is used for input signal of 1-D, in which we designed model for classification csv type of data for ECG signal, while in the second proposed system, we used model for 2-D signal after convert it from its csv type . 2-D signal (ECG image) is used in order to augment the two dimensional signal with different methods to increase the accuracy of the model by training it with geometric transformation of the original input images such as rotation, shearing etc.The results are compared with AlexNet and other models based on the metrics, which are used to measure the performance of the proposed work, the result show that, the proposed models improve the efficiency of the classification in the two systems.
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Alvarez, R. H., B. E. Almeida, M. T. C. P. Ribela, F. L. N. Natal, A. J. F. Melo, and P. Bartolini. "211 REVERSED-PHASE HIGH-PERFORMANCE LIQUID CHROMATOGRAPHY AS A TOOL TO ELUCIDATE THE BIOLOGICAL ACTIVITY OF COMMERCIAL EQUINE CHORIONIC GONADOTROPIN (eCG)." Reproduction, Fertility and Development 26, no. 1 (2014): 219. http://dx.doi.org/10.1071/rdv26n1ab211.
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Superovulation in ruminants can be induced with a single injection of equine chorionic gonadotropin (eCG). However, ovarian response is sometimes lower than expected because of, among other factors, the source of eCG used. This study aimed at establishing the physical-chemical profile of commercial eCG, in order to find differences which can be related to their biological activity. Four different commercial eCG products for veterinary use (A, B, C, D) and one eCG chemical reagent from Sigma (St. Louis, MO, USA), here used as reference preparation, were analysed by reversed-phase high-performance liquid chromatography (RP-HPLC) using a C4-Grace Vydac 214 TP 54-column (25 cm × 4.6 mm I.D.), with UV detection at 220 nm. All eCG preparations presented at least three peaks with retention times (tR) of ~27(I), 34(II), and 36(III) minutes, with a peak at tR = 27 min common to A, C, D, and Sigma eCG, whereas preparation B did not present this peak. A bioassay test was carried with all of these preparations. Immature 21- to 25-day-old Wistar female rats received the equivalent to 10 IU of eCG of each one of these preparations. Autopsy was performed 48 h later and ovaries were removed and weighed. The average ovarian weight for preparations A, C, D, and Sigma were ~0.0795 ± 0.0107 g, whereas preparation B was 0.035 ± 0.007 g (P < 0.01). Preparation B was not different from saline (0.034 ± 0.002 g). In order to establish which one of these three peaks presented the highest biological activity, a mass equivalent to 10 IU of eCG from peaks I, II, and III of Sigma and of product A were studied. The average ovarian weight of animals injected with material from peak II and III (~0.0285 ± 0.003 g) were similar to that of the control whereas peak I produced ovarian weights of 0.059 ± 0.007 g and 0.075 ± 0.010 g for Sigma and product A, respectively (P < 0.01). These results suggest that the lack of ovarian response to eCG treatments can be related to differences in the physical-chemical profile of commercial eCG products and that RP-HPLC is a fast and reliable tool for detecting these differences. Supported by FAPESP (Grant 11/13096-0).
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Jamil, Sonain, and MuhibUr Rahman. "A Novel Deep-Learning-Based Framework for the Classification of Cardiac Arrhythmia." Journal of Imaging 8, no. 3 (March 10, 2022): 70. http://dx.doi.org/10.3390/jimaging8030070.
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Cardiovascular diseases (CVDs) are the primary cause of death. Every year, many people die due to heart attacks. The electrocardiogram (ECG) signal plays a vital role in diagnosing CVDs. ECG signals provide us with information about the heartbeat. ECGs can detect cardiac arrhythmia. In this article, a novel deep-learning-based approach is proposed to classify ECG signals as normal and into sixteen arrhythmia classes. The ECG signal is preprocessed and converted into a 2D signal using continuous wavelet transform (CWT). The time–frequency domain representation of the CWT is given to the deep convolutional neural network (D-CNN) with an attention block to extract the spatial features vector (SFV). The attention block is proposed to capture global features. For dimensionality reduction in SFV, a novel clump of features (CoF) framework is proposed. The k-fold cross-validation is applied to obtain the reduced feature vector (RFV), and the RFV is given to the classifier to classify the arrhythmia class. The proposed framework achieves 99.84% accuracy with 100% sensitivity and 99.6% specificity. The proposed algorithm outperforms the state-of-the-art accuracy, F1-score, and sensitivity techniques.
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deNicolo, G., S. T. Morris, P. R. Kenyon, P. C. H. Morel, and T. J. Parkinson. "Out-of-season breeding of Romney sheep using artificially induced long days." Australian Journal of Experimental Agriculture 48, no. 7 (2008): 961. http://dx.doi.org/10.1071/ea07406.
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This experiment investigated the effects of subjecting Romney ewes to artificially induced long days (24 L : 0 D) in spring for 30 days, then abruptly applying 8 hours of darkness (16 L : 8 D) to induce the onset of reproductive activity. The treatment groups were: light + progesterone; light + progesterone + eCG; and progesterone + eCG (ambient photoperiod; control). Blood samples were collected over a 24-h period for analysis of serum melatonin concentrations. Ewes’ ovaries were examined laparoscopically 9 days after progesterone removal. Duration of secretion and maximal concentrations of melatonin were lower in ewes treated with light + progesterone (±eCG) compared with the control ewes. Fewer light + progesterone treated ewes displayed oestrus (66%) and were subsequently identified as being pregnant (28%) compared with ewes treated with light + progesterone + eCG (98% and 53%) and control ewes (97% and 65%, respectively). Conception rates were lower in light + progesterone treated ewes (43%) compared with light + progesterone + eCG (55%) and control ewes (67%). Results obtained indicate that artificially induced long days did not improve the results of out-of-season breeding program beyond that achieved with the use of eCG.
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Byeon, Yeong-Hyeon, Sung-Bum Pan, and Keun-Chang Kwak. "Intelligent Deep Models Based on Scalograms of Electrocardiogram Signals for Biometrics." Sensors 19, no. 4 (February 22, 2019): 935. http://dx.doi.org/10.3390/s19040935.
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This paper conducts a comparative analysis of deep models in biometrics using scalogram of electrocardiogram (ECG). A scalogram is the absolute value of the continuous wavelet transform coefficients of a signal. Since biometrics using ECG signals are sensitive to noise, studies have been conducted by transforming signals into a frequency domain that is efficient for analyzing noisy signals. By transforming the signal from the time domain to the frequency domain using the wavelet, the 1-D signal becomes a 2-D matrix, and it could be analyzed at multiresolution. However, this process makes signal analysis morphologically complex. This means that existing simple classifiers could perform poorly. We investigate the possibility of using the scalogram of ECG as input to deep convolutional neural networks of deep learning, which exhibit optimal performance for the classification of morphological imagery. When training data is small or hardware is insufficient for training, transfer learning can be used with pretrained deep models to reduce learning time, and classify it well enough. In this paper, AlexNet, GoogLeNet, and ResNet are considered as deep models of convolutional neural network. The experiments are performed on two databases for performance evaluation. Physikalisch-Technische Bundesanstalt (PTB)-ECG is a well-known database, while Chosun University (CU)-ECG is directly built for this study using the developed ECG sensor. The ResNet was 0.73%—0.27% higher than AlexNet or GoogLeNet on PTB-ECG—and the ResNet was 0.94%—0.12% higher than AlexNet or GoogLeNet on CU-ECG.
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Shugushev, Kh Kh, and A. A. Gaeva. "Diuretic therapy effects on the signal-averaged ECG parameters of atrial complex and supraventricular arrhythmias in patients with coronary heart disease and chronic heart failure." Cardiovascular Therapy and Prevention 10, no. 6 (December 20, 2011): 55–58. http://dx.doi.org/10.15829/1728-8800-2011-6-55-58.
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Aim. To study the signal-averaged ECG (SA-ECG) parameters of atrial complex and supraventricular arrhythmias (SVA) in patients with coronary heart disease (CHD) and chronic heart failure (CHF), treated with diuretics (D) torasemide and furosemide. Material and methods. The study included 107 patients with CHD and CHF. All participants underwent 24-hour ECG monitoring and the registration of SA-ECG atrial complex parameters. In total, 52 patients received furosemide, and 55 were administered torasemide. Results. In both groups, D therapy was associated with some increase in the duration of filtered P and LAS5, as well as a decrease in RMS20. These changes were more pronounced in the furosemide-treated patients. Torasemide demonstrated better effects on the SVA dynamics, which manifested in the decreased numbers of single, paired, and grouped SV extrasystoles. Conclusion. In CHD and CHF patients, the disturbed atrial depolarisation was manifested in negative dynamics of SA-ECG atrial complex parameters. Torasemide therapy did not affect the atrial complex parameters and also reduced SVA incidence, which made torasemide a medication of choice for patients with CHD and CHF.
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Souza, A. F., V. G. Pinheiro, R. L. Ereno, and C. M. Barros. "14 SYNCHRONIZATION OF OVULATION IN ANESTROUS NELORE COWS TREATED WITH HORMONAL PROTOCOL WITHOUT PROGESTERONE OR PROGESTAGENS." Reproduction, Fertility and Development 18, no. 2 (2006): 115. http://dx.doi.org/10.1071/rdv18n2ab14.
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Postpartum anestrous cows are usually treated with progesterone/progestagen protocols in order to induce ovulation and sustain pregnancy. In the present work, the efficiency of a protocol (modified GPE), in which temporary calf removal (TCR) and/or administration of eCG, replaced the use of progesterone/progestagens, was evaluated in anestrous animals. Anestrous Nelore cows (40 to 60 days postpartum, n = 22) were randomly allocated to two groups: GPE/eCG and TCR/GPE/eCG. At a random stage of the estrous cycle (D0), animals from Group GPE/eCG were treated with GnRH (50 �g, licereline, i.m., Gestran Plus�; Tecnopec, Sao Paulo, Brazil) and seven days later (D7) they received PGF2� (150 mcg, d-cloprostenol, i.m., Prolise�) and eCG (300 UI, i.m., Novormon�). On D8, estradiol benzoate (EB, 1 mg, Estrogin�; Tecnopec) was administered, and 30 to 36 h afterwards all cows were inseminated at fixed-time (FTAI), without estrus detection. The animals from group TCR/GPE/eCG received the same treatment described above, but with temporary calf removal (during 48 h) before beginning hormonal treatments. The ovaries were examined by ultrasonography (Aloka SSD 500, 7.5 MHz probe) before (D-12, D-2), during (D0, D7, D8), and after (D9, D10, D11, D17, D60) hormonal treatments. The absence of CL, during the ultrasonography performed before starting the treatments, was the criterion used to classify the cows as in postpartum anestrus. Administration of GnRH (D0) induced ovulation (determined by the presence of CL on D7) in 6 of 11 cows (54.5%) from Group GPE/eCG and TCR/GPE/eCG. In relation to synchronization of ovulation after EB administration, in Group GPE/eCG, two cows (18.1%) ovulated until 12 h after FTAI, and four (36.3%) 12 h afterwards (24 h after FTAI). In Group TCR/GPE/eCG, one cow (9%) ovulated approximately 6 h before FTAI, two (18.1%) 12 h after FTAI, and two (18.1%) 12 h afterwards. Preovulatory follicles had a diameter of 11.0 � 1.3 and 11.5 � 2.6 mm in Groups GPE/eCG and TCR/GPE/eCG, respectively. Pregnancy rates, determined by ultrasonograpy 40 to 46 days after FTAI, were 27.2% (3/11) and 45.4% (5/11), respectively. The results indicate that association of TCR with protocol GPE/eCG did not improve synchronization of ovulation or pregnancy rates (P > 0.005). However, increase in pregnancy rates was observed in another experiment with a large number of animals (Pinheiro et al. 2005 Reprod. Fert. Dev. 17, 161, abstr), in which cows from Group TCR/GPE/eCG had higher pregnancy rates (51.5%; 34/66) when compared to animals from Group GPE/eCG (28.3%, 21/74; P < 0.05). This work was supported by FAPESP and by fellowships for A. F. Souza and V. G. Pinheiro from CNPq, Brazil.
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Maraña, D., L. Cutaia, L. Peres, D. Pincinato, L. F. K. Borges, and G. A. Bo. "16 OVULATION AND PREGNANCY RATES IN POSTPARTUM BOS INDICUS COWS TREATED WITH PROGESTERONE VAGINAL DEVICES AND ESTRADIOL BENZOATE, WITH OR WITHOUT eCG AND TEMPORARY WEANING." Reproduction, Fertility and Development 18, no. 2 (2006): 116. http://dx.doi.org/10.1071/rdv18n2ab16.
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Two experiments were designed to compare the effects of eCG treatment and temporary weaning on ovulation and pregnancy rates in postpartum cows. In Experiment 1, 39 lactating multiparous crossbred Bos indicus cows, 60 to 80 d postpartum with a body condition score (BCS) between 2.0 to 2.5 out of 5 were randomly allocated to one of four treatment groups in a 2 � 2 factorial design. On Day 0, all cows received a progesterone (P4) intravaginal device (DIB; Syntex, Argentina) and 2 mg estradiol benzoate (EB) i.m. (Syntex). On Day 8, DIB devices were removed and all cows received 150 �g D(+)cloprostenol i.m. (Ciclase; Syntex) and were randomly divided to receive 400 IU eCG i.m. (Novormon 5000; Syntex) at the same time or no treatment. In addition, half of the cows in each group had their calves weaned temporarily (TW) for 56 h at the time of DIB removal; the other half remained with their calves. All cows received 1 mg EB i.m. on Day 9 and were examined every 8 h by ultrasonography from the time of DIB removal until ovulation. Data were analyzed by ANOVA and chi-square test. The diameter of the dominant follicle on Day 8 (eCG: 7.8 � 0.5 mm vs. no eCG: 8.2 � 0.4 mm, and TW: 7.6 � 0.4 mm vs. no TW 8.4 � 0.5 mm), the proportion of cows that ovulated (eCG: 12/20, 60% vs. no eCG: 9/19, 47%; and TW: 13/20, 65% vs. no TW: 8/19, 42%, and the interval to ovulation (eCG: 72.0 � 1.4 h vs. no eCG: 75.6 � 2.0 h, and TW: 73.8 � 1.6 h vs. no TW: 73.0 � 1.8 h) did not differ among groups (P > 0.05). Although there was no effect of eCG treatment or eCG by TW interaction (P > 0.3) on the size of the preovulatory follicle (eCG: 11.1 � 0.4 mm vs. no eCG: 10.1 � 0.6 mm), it was smaller in cows TW (9.9 � 04 mm), compared to those not TW (11.8 � 0.3 mm; P < 0.05). Nevertheless, the growth rate of the ovulatory follicle was greater (P < 0.02) in cows treated with eCG (1.1 � 0.1 mm/day) than in those not treated with eCG (0.6 � 0.1 mm/day). In Experiment 2 769 lactating multiparous crossbred Bos indicus cows received the same treatments as those in Experiment 1 and were fixed-time inseminated (FTAI) 52 to 56 h after DIB removal. Cows were examined by ultrasonography on Day 0 (22.5% with corpora lutea (CL), 30.0% with follicles >8 mm, and 47.5% with follicles <8 mm) and 42 d after FTAI to determine pregnancy. Data were analyzed by logistic regression. Pregnancy rates were not affected (P > 0.7) by TW (TW: 141/397, 37.2% vs. no TW: 141/390, 36.1%) or the TW by eCG interaction (P > 0.7). However, pregnancy rates were higher (P < 0.05) in cows treated with eCG (154/377, 40.8%) than in those not treated with eCG (128/392, 32.6%). The use of eCG but not TW improved pregnancy rates following FTAI in postpartum Bos indicus cows. Results also suggest that the eCG-related increase in pregnancy rates may be due to the final growth rate of the ovulatory follicle.
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Fu’adah, Yunendah Nur, and Ki Moo Lim. "Classification of Atrial Fibrillation and Congestive Heart Failure Using Convolutional Neural Network with Electrocardiogram." Electronics 11, no. 15 (August 7, 2022): 2456. http://dx.doi.org/10.3390/electronics11152456.
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Atrial fibrillation (AF) and congestive heart failure (CHF) are the most prevalent types of cardiovascular disorders as the leading cause of death due to delayed diagnosis. Early diagnosis of these cardiac conditions is possible by manually analyzing electrocardiogram (ECG) signals. However, manual diagnosis is complex, owing to the various characteristics of ECG signals. An accurate classification system for AF and CHF has the potential to save patient lives. Therefore, this study proposed an ECG signal classification system for AF and CHF using a one-dimensional convolutional neural network (1-D CNN) to provide a robust classification system performance. This study used ECG signal recording of AF, CHF, and NSR, which can be accessed on the Physionet website. A total of 5600 ECG signal segments were obtained from 56 subjects, divided into train sets from 42 subjects (N = 4200 ECG segments), and test sets from 14 subjects (N = 1400). We applied for leave-one-out cross-validation in training to select the best model. The proposed 1-D CNN algorithm successfully classified raw data of ECG signals into normal sinus rhythm (NSR), AF, and CHF by providing the highest classification accuracy of 99.643%, f1-score, recall, and precision of 0.996, respectively, with an AUC score of 0.999. The results showed that the proposed method extracted the ECG signal information directly without needing several preprocessing steps and feature extraction methods that potentially reduce the information contained in the ECG signals. Furthermore, the proposed method outperformed previous studies in classifying AF, CHF, and NSR. Therefore, this approach can be considered as an adjunct for medical personnel to diagnose AF, CHF, and NSR.
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Gugale, Piyush, Vihita Kulkarni, Arun Bahulikar, and Deepak Phalgune. "Study of cardiac function in adults with dengue." International Journal of Advances in Medicine 9, no. 4 (March 24, 2022): 463. http://dx.doi.org/10.18203/2349-3933.ijam20220785.
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Background: Medical literature has reports of isolated cases of atrioventricular conduction disorders, supraventricular arrhythmias, and myocarditis in dengue fever (DF). There is a paucity of data available in the published literature on the cardiac manifestations of DF from India. The aim of the present study was to assess the cardiac manifestations of DF. Methods: The 140 patients aged ≥18 years with DF confirmed with a serology-dengue non-structural protein 1 antigen-positive were included for this prospective observational study. Three serial ECGs were taken on day one, day three and day seven or day of discharge. All the patients were evaluated using 2D echo on day one, day seven or day of discharge. The primary outcome measures were to find the incidence and type of echocardiographic abnormalities and electrocardiographic changes in dengue.Results: The incidence of cardiac abnormalities on ECG and 2D echo was 30 (21.4%), and 5 (7.0%) respectively. On ECG, 14 (10%) 9 (6.4%) 3 (2.1%) 3 (2.1%) and 1 (0.7%) patients had sinus bradycardia, sinus tachycardia, non-specific ST-T changes, right bundle branch block and atrio-ventricular block on ECG respectively. On 2D echo, 7 (5.0%), 5 (3.6%) and 1 (0.7%) patient had systolic dysfunction, ejection fraction (<45.0%) and diastolic dysfunction respectively.Conclusions: The incidence of cardiac abnormalities on ECG and 2D ECHO in dengue patients was considerable. ECG and 2 D echo should be undertaken in patients with DF.
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Melnikova, I. Yu, and Yu A. Tokarevа. "The index of “electrical quality of the heart” allows predicting the degree of risk of fatal cardiogenic conditions in children and adolescents." Experimental and Clinical Gastroenterology 1, no. 1 (March 17, 2021): 150–54. http://dx.doi.org/10.31146/1682-8658-ecg-185-1-150-154.
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The purpose of the research. The optimization of the method electrocardiogram’s interpretation (ECG) for diagnosis and prognosis of fatal cardiogenic situations among children and teenagers depending on the severity of myocardial electrical instability.Materials and methods. The authors propose to use a modified method for assessing the “electrical quality of the heart”, proposed by A. N. Volobuev and co-authors in order to assess the electrical instability of the myocardium among children and teenagers. There is a formula which helps to estimate the index of “electrical quality factor of the heart” among children and teenagers: D=(aR/aT):(QT/QRS), where D is the index of “electrical quality factor of the heart”, aT and aR is the amplitude of R wave and T, QT — QT interval, QRS — interval, QRS. ECG was recorded in 12 leads, ECG assessment was carried out according to generally accepted rules.Results. Based on the analysis of 234 ECG of children and teenagers from the neonatal period to 18 years, the criteria of the average value of the index of “electrical quality factor of the heart” (D) were defined, D =1,09 +/- 0,03. It is proved that the value of the index “electrical quality factor of the heart” does not depend on the sex and age of the child. There was a decrease in the index of “electrical quality factor of the heart” was revealed among children with the lengthening of the QT interval.Conclusion. The index of “electrical quality factor of the heart” in pediatric practice allows to predict the risk of fatal cardiogenic conditions, to develop tactics of dynamic monitoring of patients, to evaluate the efficiency of treatment. When D<0.55 it is possible to predict high risk, at a value of 0.55≤D<0.80 — average risk, and at D≥0.80 — low risk of fatal cardiogenic conditions among children and teenagers.
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Anghelescu, MD, Doralina L., Rakesh M. Patel, MD, Daniel P. Mahoney, MD, Luis Trujillo, MD, Lane G. Faughnan, BSN, Brenda D. Steen, MSN, Justin N. Baker, MD, and Deqing Pei, MS. "Methadone prolongs cardiac conduction in young patients with cancer-related pain." Journal of Opioid Management 12, no. 2 (March 1, 2016): 131. http://dx.doi.org/10.5055/jom.2016.0325.
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Objective: Methadone prolongs cardiac conduction, from mild corrected QT (QTc) prolongation to torsades de pointes and ventricular fibrillation, in adults. However, methadone use for pain and its effects on cardiac conduction have not been investigated in pediatric populations.Methods: A retrospective review of QTc intervals in patients receiving methadone analgesia was conducted. Medical records from a 4-year period (September 2006 to October 2010) at a pediatric oncology institution were reviewed, and correlations were tested between cardiac conduction and methadone dosage and duration of therapy, electrolyte levels, renal and hepatic dysfunction, and concurrent medications.Results: Of the 61 patients who received methadone, 37 met our inclusion criteria and underwent 137 electrocardiograms (ECGs). During methadone treatment, the mean QTc was longer than that at baseline (446.5 vs 437.55 ms). The mean methadone dose was 27.0 ± 24.3 mg/d (range, 5-125 mg/d; median, 20 mg/d) or 0.47 ± 0.45 mg/kg per day (range, 0.05-2.25 mg/kg per day; median, 0.37 mg/kg per day), and the mean duration of therapy was 49 days. The authors identified a correlation between automated and manual ECG readings by two cardiologists (Pearson r = 0.649; p < 0.0001), but the authors found no correlations between methadone dose or duration and concurrent QTc-prolonging medications, sex, age, electrolyte abnormalities, or renal or hepatic dysfunction.Conclusion: At a clinically effective analgesic dose, methadone dosage and duration were not correlated with QTc prolongation, even in the presence of other risk factors, suggesting that methadone use may be safe in pediatric populations. The correlation between automated and manual ECG readings suggests that automated ECG readings are reliable for monitoring cardiac conductivity during the reported methadone-dosage regimens.
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Giriprasad Gaddam, P., A. Sanjeeva reddy, and R. V. Sreehari. "Automatic Classification of Cardiac Arrhythmias based on ECG Signals Using Transferred Deep Learning Convolution Neural Network." Journal of Physics: Conference Series 2089, no. 1 (November 1, 2021): 012058. http://dx.doi.org/10.1088/1742-6596/2089/1/012058.
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Abstract In the current article, an automatic classification of cardiac arrhythmias is presented using a transfer deep learning approach with the help of electrocardiography (ECG) signal analysis. Now a days, an ECG waveform serves as a powerful tool used for the analysis of cardiac arrhythmias (irregularities). The goal of the present work is to implement an algorithm based on deep learning for classification of different cardiac arrhythmias. Initially, the one dimensional (1-D) ECG signals are transformed to two dimensional (2-D) scalogram images with the help of Continuous Wavelet(CWT). Four different categories of ECG waveform were selected from four PhysioNet MIT-BIH databases, namely arrhythmia database, Normal Sinus Rhythm database, Malignant Ventricular Ectopy database and BIDMC Congestive heart failure database to examine the proposed technique. The major interest of the present study is to develop a transferred deep learning algorithm for automatic categorization of the mentioned four different heart diseases. Final results proved that the 2-D scalogram images trained with a deep convolutional neural network CNN with transfer learning technique (AlexNet) pepped up with a prominent accuracy of 95.67%. Hence, it is worthwhile to say the above stated algorithm demonstrates as an effective automated heart disease detection tool
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Garzon, Sérgio A. C., Adalberto M. Lorga, and José Carlos Nicolau. "Electrocardiography in Chagas' heart disease." Sao Paulo Medical Journal 113, no. 2 (April 1995): 802–13. http://dx.doi.org/10.1590/s1516-31801995000200011.
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Conventional ECG still plays an important role in the overall knowledge of Chagas' cardiopathy, because of its importance in longitudinal and epidemiological studies, its diagnostic value, and its utility in prognostic evaluation. The authors discuss these aspects, as well as the use of ECG in the acute phase and the significance of a normal ECG in Chagas' disease. Correlations were made between ECG and hemodynamic/angiographic variables among 1010 patients with positive laboratory tests for Chagas' disease: a) in the group with normal ECG there were no significant differences between symptomatic and non-symptomatic patients with regard to ejection fraction and angiographic abnormalities; b) slight abnormalities on the ECG corresponded to an intermediate level of severity of the disease, that is, between normal ECG and ECG with significant abnormalities; c) fibrosis on the ECG was not predictive of akinesia in the related area on the angiography; d) combined ECG abnormalities generally correlated with greater myocardial compromise compared to isolated abnormalities; e) under multiple regression analysis the ECG abnormalities that independently correlated with depressed ejection fraction were: premature ventricular beats, ventricular tachycardia, left bundle branch block, atrial fibrillation, complete AV block, and anterior and inferior fibrosis. Male sex, cardiac insufficiency and cardiomegaly on the thorax radiography were also significantly related.
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Chiang, H. K., Chao-Wei Chu, Gau-Yang Chen, and Cheng-Deng Kuo. "A new 3-D display method for 12-lead ECG." IEEE Transactions on Biomedical Engineering 48, no. 10 (2001): 1195–202. http://dx.doi.org/10.1109/10.951523.
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Moumene, A., F. Khammar, K. Miroud, R. Seboussi, S. Guedaoura, and J. L. Bister. "Traitements à base de progestagènes ou de mélatonine combinés à l’effet bélier chez la brebis Ouled-Djellal au printemps." Revue d’élevage et de médecine vétérinaire des pays tropicaux 67, no. 1 (July 1, 2014): 41. http://dx.doi.org/10.19182/remvt.10158.
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Pour comparer l’effet de traitements hormonaux à base de mélatonine à ceux à base de progestatifs et d’hormone chorionique gonadotrope équine (eCG) sur l’amélioration des performances reproductives de la race ovine Ouled- Djellal, 829 brebis réparties sur quatre exploitations (A, B, C et D ; respectivement n = 248, 351, 100 et 80) ont été suivies de mars à octobre 2008. Dans l’exploitation B, les progestagènes ont eu un effet améliorateur, avec une fertilité de 92,3 p. 100 pour le traitement avec les éponges vaginales à l’acétate de médroxyprogestérone (MAP) + eCG 400 UI, et de 84,1 p. 100 pour le traitement avec les éponges vaginales à l’acétate de fluorogestone (FGA) + eCG 500 UI, au lieu de 23,2 p. 100 chez les témoins. Les taux de fertilité obtenus dans les exploitations A et C avec les implants de mélatonine après la première saillie ont été significativement moins importants que ceux des lots traités avec les progestagènes et eCG (A : 40,9 vs 79,9 p. 100 ; C : 24 vs 70 p. 100). Le taux de fertilité obtenu avec les implants de mélatonine dans l’exploitation A après la première saillie a été plus élevé (40,9 p. 100) que celui obtenu dans les exploitations C (24 p. 100) et D (17,5 p. 100). Dans l’exploitation D les implants de mélatonine ont amélioré la fertilité totale par rapport au lot témoin (55,0 vs 17,5 p. 100). La prolificité à la première saillie a été améliorée par le traitement MAP + eCG 400 UI dans les exploitations A (1,30) et B (1,70), alors que les traitements FGA + eCG 500 UI et avec implant de mélatonine n’ont pas eu d’effet sur la prolificité. La mélatonine associée à l’effet bélier et utilisée précocement a donné de bons résultats, de l’ordre de ceux obtenus avec les progestagènes.
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Wang, Zhongmin, Zhigao Liu, Chenxi Wu, Songlin Liu, Dianhui Wang, Chaohao Hu, Tao Chen, Zhaojin Ran, Weijiang Gan, and Guiyin Li. "Computational Analysis on Antioxidant Activity of Four Characteristic Structural Units from Persimmon Tannin." Materials 16, no. 1 (December 29, 2022): 320. http://dx.doi.org/10.3390/ma16010320.
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Antioxidants are molecules that can prevent the harmful effects of oxygen, help capture and neutralize free radicals, and thus eliminate the damage of free radicals to the human body. Persimmon tannin (PT) has excellent antioxidant activity, which is closely related to its molecular structure. We report here a comparative study of four characteristic structural units from PT (epicatechin gallate (ECG), epigallocatechin gallate (EGCG), A−type linked ECG dimer (A−ECG dimer), A−type linked EGCG dimer (A−EGCG dimer)) to explore the structure–activity relationship by using the density functional theory. Based on the antioxidation mechanism of hydrogen atom transfer, the most favorable active site for each molecule exerts antioxidant activity is determined. The structural parameters, molecular electrostatic potential, and frontier molecular orbital indicate that the key active sites are located on the phenolic hydroxyl group of the B ring for ECG and EGCG monomers, and the key active sites of the two dimers are located on the phenolic hydroxyl groups of the A and D’ rings. The natural bond orbital and bond dissociation energy of the phenolic hydroxyl hydrogen atom show that the C11−OH in the ECG monomer and the C12−OH in the EGCG monomer are the most preferential sites, respectively. The most active site of the two A−linked dimers is likely located on the D’ ring C20′ phenolic hydroxyl group. Based on computational analysis of quantum chemical parameters, the A−ECG dimer is a more potent antioxidant than the A−EGCG dimer, ECG, and EGCG. This computational analysis provides the structure–activity relationship of the four characteristic units which will contribute to the development of the application of PT antioxidants in the future.
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Spinicci, Michele, Carlo Fumagalli, Niccolò Maurizi, Enrico Guglielmi, Mimmo Roselli, Herlan Gamboa, Marianne Strohmeyer, et al. "Feasibility of a Combined Mobile-Health Electrocardiographic and Rapid Diagnostic Test Screening for Chagas-Related Cardiac Alterations." Microorganisms 9, no. 9 (September 6, 2021): 1889. http://dx.doi.org/10.3390/microorganisms9091889.
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Background: Chronic Chagas cardiomyopathy (CChC) is the most common cause of death related to Chagas disease (CD). The aim of this study was to assess the feasibility of a combined rapid diagnostic test (RDT) and electrocardiographic (ECG) screening in a remote rural village of the Bolivian Chaco, with a high prevalence of CChC. Methods: Consecutive healthy volunteers > 15 years were enrolled in the community of Palmarito (municipality of Gutierrez, Santa Cruz Department, Bolivia) in February 2019. All patients performed an RDT with Chagas Stat-Pak® (CSP, Chembio Diagnostic System, Medford, NY, USA) and an ECG by D-Heart® technology, a low-cost, user-friendly smartphone-based 8-lead Bluetooth ECG. RDTs were read locally while ECGs were sent to a cardiology clinic which transmitted reports within 24 h from recording. Results: Among 140 people (54 men, median age 38(interquartile range 23–54) years), 98 (70%) were positive for Trypanosoma cruzi infection, with a linear, age-dependent, increasing trend (p < 0.001). Twenty-five (18%) individuals showed ECG abnormalities compatible with CD. Prevalence of ECG abnormalities was higher in infected individuals and was associated with higher systolic blood pressure and smoking. Following screening, 22 (16%) individuals underwent clinical evaluation and chest X-ray and two were referred for further evaluation. At multivariate analysis, positive CSP results (OR = 4.75, 95%CI 1.08–20.96, p = 0.039) and smoking (OR = 4.20, 95%CI 1.18–14.92, p = 0.027) were independent predictors of ECG abnormalities. Overall cost for screening implementation was <10 $. Conclusions: Combined mobile-Health and RDTs was a reliable and effective low-cost strategy to identify patients at high risk of disease needing cardiologic assessment suggesting potential future applications.
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Pinheiro, V., A. Souza, R. Ereno, and C. Barros. "23 PREGNANCY RATE IN NELORE COWS AFTER TEMPORARY CALF REMOVAL, AND USE OF HORMONAL PROTOCOLS WITH eCG." Reproduction, Fertility and Development 17, no. 2 (2005): 161. http://dx.doi.org/10.1071/rdv17n2ab23.
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Both temporary calf removal (TCR) and administration of eCG are potentially useful to improve pregnancy rates in animals treated with fixed-time artificial insemination (FTAI) protocols. In the present work, two experiments were performed to compare the efficiency of eCG and/or TCR in FTAI protocols, with or without exogenous progesterone. In experiment 1, lactating Nelore cows (40 to 70 days post-partum, n = 220) were allocated to two Groups. At a random stage of the estrous cycle (Day 0), animals from Group GPE (GnRH/PGF2α/Estradiol)/eCG were treated with GnRH (50 mg lecireline, i.m.; Gestran Plus®; Tecnopec, Sao Paulo, Brazil). Seven days later (Day 7) they received PGF2α (150 mg D-cloprostenol, i.m.; Prolise®, Tecnopec) and eCG (300 UI, i.m.; Novormon®, Syntex). On Day 8 estradiol benzoate (EB, 1 mg, Estrogin®, Tecnopec) was administered, and 30–36 h later the animals were inseminated (FTAI). In Group DIB (bovine intravaginal device)/eCG an intravaginal progesterone-releasing device (1.0 g, DIB®, Syntex, Buenos Aires, Agrentina; Day 0) was inserted into the vagina of cows and EB (2.5 mg, i.m.) was given in parallel. Eight days later (Day 8), eGC (300 UI, i.m.) and D-cloprostenol (150 mg) were administered. Then the DIB was removed. Twenty-four hour after DIB removal, cows were treated with EB (1.0 mg, i.m.), and 30–36 h later the animals were inseminated (FTAI). Ultrasonographic evaluation of ovaries was performed in all experiments 10 days before and at the beginning of the treatments or TCR, in order to detect the presence of CL. Cows from Group DIB/eCG showed higher pregnancy rates than those from Group GPE/eCG (58%, 72/124 vs. 39.5%, 38/96, respectively, P < 0.01). Furthermore, only in Group GPE/eCG were pregnancy rates higher in animals with CL (47.6%, 20/42) when compared to those without CL (33%, 18/54, P < 0.05). In a second experiment, a possibly beneficial effect of TCR on GPE/eCG protocol was tested in lactating Nelore cows (40 to 70 days postpartum, n = 140). Animals of Group GPE/eCG (control) were treated as described above, whereas calves were removed for 48 h from cows in Group RTB/GPE/eCG prior to hormonal treatments. Lactating Nelore cows having their calves removed showed a significant increase in pregnancy rates compared to those without TCR (51.2%, 34/66 v. 28.4%, 21/74, respectively, P < 0.01), in both situations: animals with CL (54.8%, 17/31 v. 33.3%, 11/33, respectively, RTB/GPE/eCG v. GPE/eCG) or without CL (48.5%, 17/35 v. 24.3%, 10/41, respectively, RTB/GPE/eCG v. GPE/eCG). In conclusion, these results indicate that addition of eCG to the GPE protocol was not efficient enough to produce comparable results to those obtained with DIB/eCG protocol. However, calf removal before the GPE/eCG treatment increased pregnancy rates in cycling or anestrous (without CL) lactating Nelore cows.
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Kuru, Mushap, Buket Boga Kuru, Cihan Kacar, Murat Can Demir, and Nebi Cetin. "Effect of oestrus synchronization with different lengths of progesterone-impregnated sponges and equine chorionic gonadotropin on reproductive efficiency in Romanov ewes during the non-breeding season." Acta Veterinaria Brno 91, no. 3 (2022): 243–50. http://dx.doi.org/10.2754/avb202291030243.
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This study aimed to determine the effects of different lengths of progesterone and equine chorionic gonadotropin (eCG) treatment on reproductive performance during the non-breeding season in ewes. Progesterone-impregnated sponges were inserted intravaginally for 7 d in Group 1 (G1, n = 24), 9 d in Group 2 (G2, n = 25), and 11 d in Group 3 (G3, n = 24). On the day of sponge removal, eCG (350 IU) was injected and 24 h later the ewes were exposed to rams. Pregnancy was diagnosed by transrectal ultrasonography 30 ± 3 d after mating. Oestrus symptoms of G2 and G3 started earlier than G1, but there was only a significant difference between G1 and G3 (P = 0.013). In G1, G2, and G3, the oestrus responses were 100%, 100%, and 95.8%, pregnancy rates were 79.2%, 72%, and 75%, lambing rates were 79.8%, 72%, and 75%, litter sizes were 2.5, 2.2, and 2.4, and multiple birth rates were 86.7%, 80%, and 85.7%, respectively (P > 0.05). In conclusion, the short-term progesterone-impregnated sponge and eCG treatment provided excellent oestrus induction. The effects of different days (7, 9, or 11) of progesterone treatment on reproductive indicators were similar; therefore, the stress caused by the inserted sponge can be reduced by short-term use.
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Abo-Zahhad, Mohammed, Sabah M. Ahmed, and Ahmed Zakaria. "An Efficient Technique for Compressing ECG Signals Using QRS Detection, Estimation, and 2D DWT Coefficients Thresholding." Modelling and Simulation in Engineering 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/742786.
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This paper presents an efficient electrocardiogram (ECG) signals compression technique based on QRS detection, estimation, and 2D DWT coefficients thresholding. Firstly, the original ECG signal is preprocessed by detecting QRS complex, then the difference between the preprocessed ECG signal and the estimated QRS-complex waveform is estimated. 2D approaches utilize the fact that ECG signals generally show redundancy between adjacent beats and between adjacent samples. The error signal is cut and aligned to form a 2-D matrix, then the 2-D matrix is wavelet transformed and the resulting wavelet coefficients are segmented into groups and thresholded. There are two grouping techniques proposed to segment the DWT coefficients. The threshold level of each group of coefficients is calculated based on entropy of coefficients. The resulted thresholded DWT coefficients are coded using the coding technique given in the work by (Abo-Zahhad and Rajoub, 2002). The compression algorithm is tested for 24 different records selected from the MIT-BIH Arrhythmia Database (MIT-BIH Arrhythmia Database). The experimental results show that the proposed method achieves high compression ratio with relatively low distortion and low computational complexity in comparison with other methods.
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Erbiti, F., C. Lissarrague, J. Cabodevila, and S. S. Callejas. "Efecto de algunas variables sobre la preñez de vaquillonas post-inseminación artificial a tiempo fijo." Revista Veterinaria 29, no. 1 (June 22, 2018): 35. http://dx.doi.org/10.30972/vet.2912788.
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<p>El objetivo del presente trabajo fue evaluar el efecto del tratamiento de control del ciclo estral (Co-Synch: 5 días; J-Synch o Dispositivos 7 días), del estado reproductivo (cíclico o anestro superficial) y de la gonadotrofina coriónica equina (eCG) sobre el porcentaje de preñez post-inseminación artificial a tiempo fijo (IATF). Se utilizaron vaquillonas Angus de 20-22 meses (n=336), que fueron distribuidas a: Co-Synch 5 días (el día 0 se colocó un dispositivo intravaginal DISP (0,558 g progesterona más 10,5 µg de acetato de buserelina). El día 5 se retiró el DISP y se inyectó 0,150 mg de D-Cloprostenol y aleatoriamente recibieron o no 300 UI de eCG. A las 56 h post DISP se realizó IATF más administración de 10,5 mg de acetato de buserelina. J-Synch: el día 0 se colocó DISP más 2 mg de benzoato de estradiol. El día 6 se retiró el DISP y se inyectó 0,150 mg de D-Cloprostenol; y aleatoriamente recibieron o no 300 UI de eCG. A las 72 h post DISP se realizó IATF más 10,5 mg de acetato de buserelina. Dispositivo 7 días: el día 0 se colocó DISP más 2 mg de benzoato de estradiol. El día 7 se retiró el DISP y se inyectaron 0,150 mg de D-Cloprostenol y 1 mg de cipionato de estradiol; aleatoriamente recibieron o no 300 UI de eCG. El diagnóstico de gestación se realizó a los 30 días post IATF. Se observaron efectos significativos (p<0,01) del tratamiento de control del ciclo estral sobre el porcentaje de preñez (Co-Synch 5 días: 38,1a , J-Synch: 55,5b y Dispositivo 7 días: 61,1b ), del estado reproductivo (cíclico: 58,7; anestro superficial: 42,2) y de la administración de eCG (Si: 59,2 y No: 43,7). Se concluye que el tratamiento hormonal, el estado reproductivo y la administración de eCG afectan el porcentaje de preñez post IATF></p>
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Zhang, Jixiang, Chengqin Wu, Chenzhao Ruan, Rongxia Zhang, Zengshun Zhao, and Xiangqian Cheng. "ECG Signal Classification Based on Fusion of Hybrid CNN and Wavelet Features by D-S Evidence Theory." Journal of Healthcare Engineering 2021 (September 7, 2021): 1–13. http://dx.doi.org/10.1155/2021/4222881.
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At present, cardiovascular disease is regarded as one of the dangerous diseases that threaten human life. The morbidity and lethality caused by cardiovascular disease are constantly increasing every year. In this paper, we propose a two-stream style operation to handle the electrocardiogram (ECG) classification: one for time-domain features and another for frequency-domain features. For the time-domain features, convolutional neural networks (CNN) are constructed for feature learning and classification of ECG signals. For the frequency-domain features, support vector regression (SVR) machines are designed to perform the regression prediction on each signal. Finally, the D-S evidence theory is adopted to perform the decision fusion strategy on the time-domain and frequency-domain classification results. We confirm a recognition performance of 99.64% from the experiment result for the D-S evidence theory recognition system upon the MIT-BIH arrhythmia database. The analysis of various methods of ECG classification shows that the model delivers superior performance promotion across all these scenarios.
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Sung, Wen Tsai, Jui Ho Chen, and Yen Chun Chiang. "ECG Application to Remote Care System via Web-Based and Graphics Interface." Advanced Materials Research 217-218 (March 2011): 1330–35. http://dx.doi.org/10.4028/www.scientific.net/amr.217-218.1330.
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This system was composed of independently developed ECG Signal Acquisition Model, DAQ Signal Acquisition Card, and the LabVIEW Graphics System. Regarding the ECG Signal Acquisition Model, this system uses the TL082 Operational Amplifier to realize the amplification, and uses the Filter Circuits along with the ISO122 to isolate IC. Regarding the ECG oscillogram display and ECG Signal Acquisition, the LabVIEW Graphics System developed by the American company “National Instruments” (NI) was adopted. Also, the LabVIEW system and the DAQ signal acquisition card of the Data Acquisition Package developed by the NI Company was adopted as well.The DAQ signal acquisition card can engage in A/D, DI/O, number counting and time counting applications. At last, it can use the TCP/IP Protocol to send the ECG waveform data by the internet to the computers with remote surveillance monitors. The remote surveillance computers can be installed in the hospital. Professional doctors in the hospital can observe the patient’s ECG waveform data and statistics, and engage in the job of remote care.
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McCarthy, Lucas. "Ambulatory ECG monitoring for 30 d increased AF detection more than 24 h of ECG monitoring after cryptogenic stroke." Annals of Internal Medicine 161, no. 10 (November 18, 2014): JC2. http://dx.doi.org/10.7326/0003-4819-161-10-201411180-02002.
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Alexandre, E., A. Pena, and M. Sobreira. "On the Use of 2-D Coding Techniques for ECG Signals." IEEE Transactions on Information Technology in Biomedicine 10, no. 4 (October 2006): 809–11. http://dx.doi.org/10.1109/titb.2006.874926.
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Joshi, Shruti S., Mardi Hamra, and David E. Newby. "Diagnostic computed tomography in acute interscapular pain." Heart 106, no. 2 (December 24, 2019): 126–63. http://dx.doi.org/10.1136/heartjnl-2019-315821.
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Clinical introductionA man in his 60s with no medical history presented with sudden-onset, severe interscapular pain. He was in circulatory shock with a blood pressure of 65/30 mm Hg, heart rate of 115 beats per minute, respiratory rate of 32 breaths per minute and a room air oxygen saturation of 89%. Examination demonstrated weak peripheral pulses, an elevated jugular venous pressure, faint dual heart sounds, no cardiac murmurs and bilateral lung crepitations. An ECG was recorded which showed a broad QRS (figure 1A). There were no previous ECGs to compare this with. In view of his presentation with acute-onset interscapular pain, CT of the aorta was organised by the emergency department clinicians (figure 1B–D). After the CT result was obtained, the on-call cardiologist was contacted and a bedside echocardiogram performed. This demonstrated severe left ventricular systolic dysfunction with akinesia of the apex and lateral walls. The patient was then transferred to the catheter laboratory for an emergency invasive coronary angiogram.Figure 1ECG and CT images at presentation (A) 12 lead ECG. (B) Contrast enhanced CT aorta - coronal view. (C) Contrast enhanced CT aorta - axial view. (D) CT aorta showing 4 chamber view of the heart.What is the most likely diagnosis?Pulmonary embolism.Aortic dissection.Acute myocardial infarction.Cardiac tamponade.
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Hadiyoso, Sugondo, Suci Aulia, Indrarini Dyah Irawati, and Mohamad Ramdhani. "Multi-Distance Dispersion Entropy for ECG Signal Classification." International Journal of Online and Biomedical Engineering (iJOE) 18, no. 07 (June 14, 2022): 151–60. http://dx.doi.org/10.3991/ijoe.v18i07.30055.
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Automatic detection of heartbeat is critical for early cardiovascular disease prevention and diagnosis. Traditional feature methodologies based on expert knowledge cannot abstract and represent multidimensional and multi-view information. Hence traditional research on heartbeat detection pattern recognition cannot produce adequate results. The proposed method in this research used Dispersion Entropy (DisEn) on Multidistance Signal Level Difference (MSLD) for feature extraction and Support Vector Machine (SVM) method for classifying the ECG signals. DisEn generates 20 DE values as feature vectors for each MSLD signal with a distance D of 1 to 20. The datasets used in this research were obtained from the MIT-BIH Arrhythmia database of ECG signals that consist of forty-five patients was captured using 200 [adu/mV] amplification and a sampling frequency of 360 Hz. The experiments result using 5-fold cross-validation revealed that at distance D= 1-15 had the highest accuracy of 91% to classify the ECG data into Normal Sinus Rhythm (NSR), Left Bundle Branch Block (LBBB), and Atrial Fibrillation (AFIB) from the MIT-BIH Arrhythmias database.
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Chang, Lijun. "Research on Prediction Algorithm of Employees’ Psychological Stress Based on Multifeature Fusion." Security and Communication Networks 2021 (October 14, 2021): 1–9. http://dx.doi.org/10.1155/2021/6917191.
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A multifeature fusion-based enterprise employee psychological stress prediction algorithm is suggested to address the concerns of low prediction accuracy, long duration, and poor results in current psychological stress prediction approaches. Examine ECG signal generation and properties, as well as the notion and causes of heart rate variability. The ECG signal is gathered according to the psychological stress reaction mechanism, and the digital filter is utilized to filter and preprocess the noise interference of the ECG signal. The linear discriminant analysis algorithm extracts the time domain linear features, frequency domain linear features, and nonlinear features of the ECG signal and then selects the ECG signal characteristics. D-S evidence theory is used to fuse the time domain linear characteristics, frequency domain linear characteristics, and nonlinear characteristics of the ECG signal, construct the psychological stress prediction model, obtain the final result of psychological stress state prediction, and realize the psychological stress prediction of enterprise employees, all based on multifeature fusion technology. The results of the experiments reveal that the suggested algorithm has a greater predictive effect on employee psychological stress, allowing it to enhance forecast accuracy and reduce prediction time.
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Tortorella, R. D., M. R. Modesto, J. P. Neves, and A. F. Ramos. "Development of fixed-time artificial insemination protocols for locally adapted Curraleiro Pé-Duro cows." Arquivo Brasileiro de Medicina Veterinária e Zootecnia 68, no. 5 (October 2016): 1159–67. http://dx.doi.org/10.1590/1678-4162-8555.
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ABSTRACT Two experiments were conducted aiming to evaluate the effects of two ovulatory inducers (Exp.1) and equine chorionic gonadotropin (eCG; Exp.2) on follicular and luteal dynamics in a fixed-time AI (FTAI) protocol in locally adapted Curraleiro Pé-Duro cows. In Exp. 1 multiparous cows (n=12) received an intravaginal device containing 1g of progesterone (P4) for 8 days and 2mg of estradiol benzoate (EB) intramuscularly (IM) at device insertion (Day 0). At device removal (Day 8) 0.150mg of Sodium D-Cloprostenol was administered IM and the cows were randomly assigned to receive 1mg of EB (EB8) or 1mg of estradiol cypionate (EC8) IM, or to not receive any ovulatory inducer (Control). All the animals participated in all treatments (crossover). The interval from P4 removal to ovulation was shorter and less variable in the EB8 treatment group (P≤0.05). In Exp. 2 (crossover), multiparous cows (n=12) received the same hormonal treatment as the EB8 group in Exp.1. At device removal (Day 8) cows were randomly assigned to receive 300UI of eCG IM or to not receive eCG (Control). No difference was ascertained on follicular and luteal parameters in Exp. 2 (P>0.05). We concluded that EB can be used as the ovulatory inducer (Exp. 1) in a FTAI protocol in Curraleiro Pé-Duro cows. However, eCG (Exp. 2) was not able to stimulate follicular and luteal development. This result is probably due to the adaptive capacity of Curraleiro Pé-Duro cows that maintained a satisfactory body condition score even in dry and hot environments.
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Yang, Peixin, Jinrong Wang, Yulei Shen, and Shyamal K. Roy. "Developmental Expression of Estrogen Receptor (ER) α and ERβ in the Hamster Ovary: Regulation by Follicle-Stimulating Hormone." Endocrinology 145, no. 12 (December 1, 2004): 5757–66. http://dx.doi.org/10.1210/en.2004-0779.
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Abstract Perinatal expression of estrogen receptor (ER) protein and mRNA and the influence of FSH on this process were examined by immunofluorescence and RT-PCR using ovaries from fetal (d 13–15 of gestation) and postnatal [postnatal d 1–15 (P1–P15)] hamsters and from 8-d-old hamsters exposed in utero to an anti-FSH serum on d 12 of gestation and saline or equine chorionic gonadotropin (eCG) on P1. A few somatic cells expressing ERα immunoreactivity appeared first on d 14 of gestation and increased markedly by P8–P15 in the interstitial cells and granulosa cells of primordial follicles. In contrast, appreciable ERβ immunoreactivity was localized on d 13 of gestation, and more cells expressed ERβ immunoreactivity by P1–P8. By P7, ERβ immunoreactivity was present in cells adjacent to the oocytes, and by P8, ERβ was preferentially localized in the granulosa cells. Receptor immunoreactivities decreased markedly in P8 ovaries exposed in utero to the FSH antiserum but were reversed with postnatal eCG replacement. Oocytes and somatic cells expressed ERα and ERβ mRNA, and levels of ER mRNA in the ovary increased by P7–P8, corresponding to the appearance of primordial follicles. Thereafter, only ERβ mRNA levels increased progressively with postnatal ovary development. Similar to ER protein, mRNA levels decreased significantly in FSH antiserum-treated ovaries but were restored by eCG. These results indicate that both ER subtypes are expressed in undifferentiated somatic cells and the oocytes during perinatal ovary development in the hamster; however, ERβ expression segregates with the differentiation of granulosa cells. Furthermore, ER expression and differentiation of somatic cells to granulosa cells depend on perinatal FSH action.
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Atanasov, Branko, Ljupco Mickov, Igor Esmerov, Ksenija Ilievska, Martin Nikolovski, and Toni Dovenski. "Two Possibile Hormonal Treatment Methods for Inducing Follicular Growth in Dairy Cows With Inactive-Static Ovaries." Macedonian Veterinary Review 37, no. 2 (October 1, 2014): 171–77. http://dx.doi.org/10.14432/j.macvetrev.2014.09.023.
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AbstractPostpartum anestrus is a physiological phenomenon in high-producing dairy cows. Static ovaries have been related as major contributors for its occurrence causing a significant reproductive problem to the dairy industry. Different treatment methods have been employed with inconsistent rate of success in initiation of cyclicity, requiring further investigations in order to achieve satisfactory results. The aim of the present study was to compare the ovarian response in cows diagnosed with static ovaries, more than 60 days postpartum using two different hormonal treatment (GnRH and eCG) methods. A total of 58 acyclic cows (no CL, follicles<8mm, P4<0.5ng/mL) were randomly divided into three groups: GnRH (Group 1, n=23), eCG (Group 2, n=23) and Controls (n=12), and allocated thereafter, into subgroups according to the applied doses of GnRH (100μg or 250μg); eCG (750 IU or 1000 IU) whilst control group cows were left untreated. Daily follicular growth rate and treatment respond interval were estimated based on repeated ultrasound examinations. Blood serum P4 sampling was done on d -7, d-0 (start of the experiment) and on d 7 after ovulation. Resumption of cyclic activity occurred in 55.17% (32/58) of the treated cows, 56.52% in Group 1; 60.86% in Group 2 and 41.66% in the control group. Overall, the follicular growth rate was similar between the trials group and significant with regard to the cows in the control group (p<0.05). eCG or GnRH treated cows responded significantly faster 6.85±0.2 and 7.84±0.2 days, respectively, in comparison to the control group cows (17±0.7 days, p<0.001). Treatment with a single dose of GnRH or eCG caused resumption of follicular growth and ovulation following luteogenesis (forming CL) without significant changes in P4 concentrations on day 7 after ovulation (p>0.05). Cows in Group 2 had significantly higher incidence of multiple ovulations than cows in Group 1 (p<0.05). The eCG treatment resulted in a faster response and higher ovulation rate compared to GnRH treatment. In conclusion, both treatments have shown acceptable results in resumption of cyclicity in dairy cows with static ovaries.
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Bao, Zhe, Dong Li, Shoufen Jiang, Liting Zhang, and Yatao Zhang. "Atrial Fibrillation Detection with Low Signal-to-Noise Ratio Data Using Artificial Features and Abstract Features." Journal of Healthcare Engineering 2023 (January 21, 2023): 1–11. http://dx.doi.org/10.1155/2023/3269144.
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Detecting atrial fibrillation (AF) of short single-lead electrocardiogram (ECG) with low signal-to-noise ratio (SNR) is a key of the wearable heart monitoring system. This study proposed an AF detection method based on feature fusion to identify AF rhythm (A) from other three categories of ECG recordings, that is, normal rhythm (N), other rhythm (O), and noisy (∼) ECG recordings. So, the four categories, that is, N, A, O, and ∼ were identified from the database provided by PhysioNet/CinC Challenge 2017. The proposed method first unified the 9 to 60 seconds unbalanced ECG recordings into 30 s segments by copying, cutting, and symmetry. Then, 24 artificial features including waveform features, interval features, frequency-domain features, and nonlinear feature were extracted relying on prior knowledge. Meanwhile, a 13-layer one-dimensional convolutional neural network (1-D CNN) was constructed to yield 38 abstract features. Finally, 24 artificial features and 38 abstract features were fused to yield the feature matrix. Random forest was employed to classify the ECG recordings. In this study, the mean accuracy (Acc) of the four categories reached 0.857. The F1 of N, A, and O reached 0.837. The results exhibited the proposed method had relatively satisfactory performance for identifying AF from short single-lead ECG recordings with low SNR.
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Yang, Fang, He Ping Hang, Jin Hui Shen, and Ming Gang Shao. "Design and Realization of Portable ECG Monitor with Dual CPU." Advanced Materials Research 340 (September 2011): 451–55. http://dx.doi.org/10.4028/www.scientific.net/amr.340.451.
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In order to meet data acquisition mobility and convenient requirements of the portable ECG monitor, the data acquisition system of ECG with dual CPU is designed in this paper. The system, in which C8051F005 is master CPU, meanwhile ATmega168 is slave CPU, consists of analogical circuit for detecting of ECG, amplifier-filter circuit, A/D converter and SD memory card communication interface mainly. Experimental data shows that the system has such advantages such as good repeatability, high accuracy, quick response and excellent anti-interference. It can effectively detect and obtain electrical activity of the heart and cope with continuous large memory with SD memory card in embedded system. Strong background noises are eliminated effectively by multi-level amplifier and filter; Un-anamorphic ECG can be acquired and recorded synchronously in memory cards. Moreover, this paper also proposes a preprocessing algorithm for noise reduction so that it can reject the interference by respiration and surface EMG signal.
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Hallfors, N. G., D. Maksimovski, I. A. H. Farhat, M. Abi Jaoude, A. R. Devarajan, K. Liao, M. Ismail, H. Pade, R. Y. Adhikari, and A. F. Isakovic. "Layered, tunable graphene oxide-nylon composite heterostructures for wearable electrocardiogram sensors." Applied Physics Letters 122, no. 1 (January 2, 2023): 013701. http://dx.doi.org/10.1063/5.0120774.
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Nanoscale engineered materials combined with wearable wireless technologies can deliver a new level of health monitoring. A reduced graphene oxide-nylon composite material is developed and tested, demonstrating its usefulness as a material for sensors in wearable, long-term electrocardiogram (ECG) monitoring via a comparison to one of the widely used ECG sensors. The structural analysis by scanning electron microscopy and atomic force microscopy shows a limited number of defects on a macroscopic scale. Fourier transform infrared and Raman spectroscopy confirm the presence of rGOx, and the ratio of D- and G-features as a function of thickness correlates with the resistivity analysis. The negligible effect of the defects and the tunability of electrical and optical properties, together with live ECG data, demonstrate its signal transduction capability. Other potential electronic and optical sensor uses beyond ECG are possible, given the controllable nature of the heterostructures and the correlation of transport and optical properties.
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Wasimuddin, Muhammad, Khaled Elleithy, Abdelshakour Abuzneid, Miad Faezipour, and Omar Abuzaghleh. "Multiclass ECG Signal Analysis Using Global Average-Based 2-D Convolutional Neural Network Modeling." Electronics 10, no. 2 (January 14, 2021): 170. http://dx.doi.org/10.3390/electronics10020170.
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Cardiovascular diseases have been reported to be the leading cause of mortality across the globe. Among such diseases, Myocardial Infarction (MI), also known as “heart attack”, is of main interest among researchers, as its early diagnosis can prevent life threatening cardiac conditions and potentially save human lives. Analyzing the Electrocardiogram (ECG) can provide valuable diagnostic information to detect different types of cardiac arrhythmia. Real-time ECG monitoring systems with advanced machine learning methods provide information about the health status in real-time and have improved user’s experience. However, advanced machine learning methods have put a burden on portable and wearable devices due to their high computing requirements. We present an improved, less complex Convolutional Neural Network (CNN)-based classifier model that identifies multiple arrhythmia types using the two-dimensional image of the ECG wave in real-time. The proposed model is presented as a three-layer ECG signal analysis model that can potentially be adopted in real-time portable and wearable monitoring devices. We have designed, implemented, and simulated the proposed CNN network using Matlab. We also present the hardware implementation of the proposed method to validate its adaptability in real-time wearable systems. The European ST-T database recorded with single lead L3 is used to validate the CNN classifier and achieved an accuracy of 99.23%, outperforming most existing solutions.
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Vu, Tran Anh, Hoang Quang Huy, Pham Duy Khanh, Nguyen Thi Minh Huyen, Trinh Thi Thu Uyen, and Pham Thi Viet Huong. "Classify arrhythmia by using 2D spectral images and deep neural network." Indonesian Journal of Electrical Engineering and Computer Science 25, no. 2 (February 1, 2022): 931. http://dx.doi.org/10.11591/ijeecs.v25.i2.pp931-940.
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Electrocardiogram (ECG) is the most common method for monitoring the working of the heart. ECG signal is the basis to determine normal or abnormal rhythm, thereby helping to accurately diagnose cardiovascular diseases. Therefore, an automatic algorithm to detect and diagnose abnormal heart rhythms is essential. There are many methods of classifying arrhythmias using machine learning algorithms such as k-nearest neighbors (KNN), support vector machines (SVM), based on the features extracted from the record of ECG signal. Actually, deep learning algorithms are evolving and highly effective in image analysis and processing. In this research, a dense neural network model is proposed to classify normal and abnormal beats. Input ECG signal presenting a time series is converted into 2-D spectral image by applying wavelet transform. Our research is evaluated based on using the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database. The accuracy of the classification algorithm we employ is 99.8%, demonstrating the model's validity when compared to other reports' findings. This is the foundation for our algorithm to prove it can be utilized as an efficient model for categorizing arrhythmia using ECG signals.
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Ayari, E., and R. Tielert. "Front End Schaltung zur Online Auswertung von EKG-Signalen." Advances in Radio Science 5 (June 13, 2007): 197–204. http://dx.doi.org/10.5194/ars-5-197-2007.
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Abstract. Ein mobiles EKG-System zur Online Auswertung von EKG-Signalen wird dargestellt. Die Auswertung beruht auf ein energiesparendes Verfahren, das den Vorteil einer zulässigen Unterabtastung des Signals bietet und eine Interaktion zwischen der messenden Elektronik und dem funkgebundenen Auswertungsrechner ermöglicht. Diese Interaktion besteht darin, sowohl die Front End Schaltung im EKG-Sensor als auch den im ATmega8L eingebetteten A/D-Wandler vom Auswertungsrechner zu steuern und den Datenbedarf des Rechners dynamisch an die Erfordernisse des Analyseprogramms anzupassen. Das entwickelte EKG-System liefert erfolgreiche Charakterisierungen erfasster Elektrokardiogramme. A mobile ecg-system for an online analysis of electrocardiogram signals is presented. The analysis is based on an energy-saving procedure, which offers the advantage of an acceptable undersampling of the signal, and which allows an interaction between the measuring electronic and the radio-bound analysis-computer. In this interaction both the front-end circuit in the ecg-sensor and the A/D converter, which is embedded in the ATmega8L, are steered by the analysis computer. The data requirement of the computer is also dynamically adapted to the requirements of the analysis-program. The developed ecg-system supplies successful characterisations of measured electrocardiograms.
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HANILCI, Ayca, and Hakan GÜRKAN. "ECG Biometric Identification Method based on Parallel 2-D Convolutional Neural Networks." Journal of Innovative Science and Engineering (JISE) 3, no. 1 (June 24, 2019): 11–22. http://dx.doi.org/10.38088/jise.559236.
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Kiranyaz, Serkan, Turker Ince, and Moncef Gabbouj. "Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks." IEEE Transactions on Biomedical Engineering 63, no. 3 (March 2016): 664–75. http://dx.doi.org/10.1109/tbme.2015.2468589.
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Tuliani, Tushar A., Maithili Shenoy, Abhishek Deshmukh, Muhammad Janjua, Levine Diane, and Luis Afonso. "MAJOR RESTING ECG ABNORMALITIES AND VITAMIN D DEFICIENCY: IMPACT ON CARDIOVASCULAR MORTALITY." Journal of the American College of Cardiology 61, no. 10 (March 2013): E1450. http://dx.doi.org/10.1016/s0735-1097(13)61450-3.
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Ruram, Jacob Abraham, Rami Reddy Ganta, and P. Arunachalam. "Role of electrocardiogram in identifying the infarct related artery in acute myocardial infarction and to correlate it with 2D echo and coronary angiogram." International Journal of Advances in Medicine 7, no. 3 (February 24, 2020): 451. http://dx.doi.org/10.18203/2349-3933.ijam20200657.
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Background: The Electrocardiogram remains a crucial tool in the identification and management of acute myocardial infarction. A detailed analysis of patterns of ST segment elevation may influence decisions regarding the perfusion therapy. This study was undertaken to study the role of ECG in identifying the infarct related artery in acute ST elevation MI and to correlate its findings with 2 D ECHO and Coronary angiogram.Methods: A total of 100 patients who presented with acute ST elevation MI were randomly selected for the study. After admission all the patients underwent ECG, CPK, CK-MB levels, 2D ECHO and CAG. Patients with ST segment elevation from ECG was evaluated to identify culprit vessel and the ECG findings were then correlated with 2D ECHO and CAG to identify the Sensitivity, Specificity, Positive predictive value and Negative predictive value of ECG in identifying the infarct related artery.Results: Fifty-two (52%) patients had an Anterior wall MI, forty-two patients (42%) had an evidence of Inferior wall MI and Six patients (6%) were found to have Antero inferior wall MI in the study group. Thirty-eight (38%) had evidence of SVD, forty-six patients (46%) had DVD and Sixteen patients (16%) had TVD. Sensitivity, Specificity, PPV and NPV of the ECG in identifying the LAD artery occlusion were 60.5%, 100%, 100% and 44.4% respectively. Sensitivity, Specificity, PPV and NPV of ECG in identifying the RCA artery occlusion were 78.5%, 100%, 100% and 78.5% respectively. Sensitivity, Specificity, PPV and NPV of the ECG in identifying the LCx artery occlusion were 26%, 96%, 86% and 60% respectively.Conclusions: ECG was found to be a sensitive and specific tool in identifying the infarct related Coronary artery in acute ST elevation MI.
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Brouillard, Charly, Pascal Carrive, Françoise Camus, Jean-Jacques Bénoliel, Thomas Similowski, and Caroline Sévoz-Couche. "Long-lasting bradypnea induced by repeated social defeat." American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 311, no. 2 (August 1, 2016): R352—R364. http://dx.doi.org/10.1152/ajpregu.00021.2016.
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Repeated social defeat in the rat induces long-lasting cardiovascular changes associated with anxiety. In this study, we investigated the effects of repeated social defeat on breathing. Respiratory rate was extracted from the respiratory sinus arrhythmia (RSA) peak frequency of the ECG in rats subjected to social defeat for 4 consecutive days. Respiratory rate was recorded under anesthesia 6 days (D+10) or 26 days (D+30) after social defeat. At D+10, defeated (D) rats spent less time in the open arms of the elevated plus maze test, had heavier adrenal glands, and displayed bradypnea, unlike nondefeated animals. At D+30, all signs of anxiety had disappeared. However, one-half of the rats still displayed bradypnea (DL rats, for low respiratory rate indicated by a lower RSA frequency), whereas those with higher respiratory rate (DH rats) had recovered. Acute blockade of the dorsomedial hypothalamus (DMH) or nucleus tractus solitarii (NTS) 5-HT3 receptors reversed bradypnea in all D rats at D+10 and in DL rats at D+30. Respiratory rate was also recorded in conscious animals implanted with radiotelemetric ECG probes. DH rats recovered between D+10 and D+18, whereas DL rats remained bradypneic until D+30. In conclusion, social stress induces sustained chronic bradypnea mediated by DMH neurons and NTS 5-HT3 receptors. These changes are associated with an anxiety-like state that persists until D+10, followed by recovery. However, bradypnea may persist in one-half of the population up until D+30, despite apparent recovery of the anxiety-like state.
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Burke, John M., Ian Flinn, Michael Craig, Richard H. C. Van Der Jagt, David MacDonald, Doreen M. Hallman, and Mihaela C. Munteanu. "Lack of effect of bendamustine on Fridericia corrected QT interval (QTcF) in a phase III study of bendamustine-rituximab in advanced indolent non-Hodgkin’s lymphoma (NHL) or mantle cell lymphoma (MCL)." Journal of Clinical Oncology 31, no. 15_suppl (May 20, 2013): e19518-e19518. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.e19518.
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e19518 Background: Clinical data on the arrhythmogenic potential of bendamustine are limited. Bendamustine and rituximab (BR) are commonly combined, and rituximab concentrations are essentially constant ≥1.5 hours due to its long half-life. This BR single-arm study assessed the effects of bendamustine on QTcF over 1.5 hours in previously untreated adults with advanced indolent NHL or MCL. Methods: Patients in this open-label study were aged ≥18 years with QTc on screening electrocardiogram (ECG) ≤450 ms. Exclusion criteria included low serum potassium or magnesium and history of cardiac conditions with QT prolongation risk. Bendamustine 90 mg/m2 was given on days 1 and 2 and rituximab 375 mg/m2 on day 1 of each 28-day cycle. On day 2 of cycle 1, ECGs and blood sampling were performed ~15 min prior to bendamustine infusion (baseline), at the end of infusion (EOI)/Cmax, and 1 h post-EOI. The primary measure was change in QTcF at EOI. Secondary measures included outlier analyses of QTcF intervals, pharmacokinetic/pharmacodynamic (PK/PD) analysis, and changes in ECG morphology. The ECG analysis included patients with ≥1 ECG at baseline and on treatment. Results: There were 53 enrolled patients (92% white; 60% male; mean age 63.0 y, range 37-84 y; mean body surface area 2.0 m2, range 1.4-2.6 m2). No clinically relevant signal of any bendamustine effect on cardiac repolarization was detected based on the mean change in QTcF from baseline and outlier analyses (Table). In the PK/PD analyses, predicted change in QTcF for bendamustine and its metabolites, M3 and M4, were not significant: 5.4 ms (upper CI 7.6 ms), 6.0 ms (8.8 ms), and 7.1 ms (10.1 ms), respectively, but there were few data. No new ECG morphologic changes were seen. Conclusions: In this small population with previously untreated advanced NHL or MCL, bendamustine was associated with a small increase in mean QTcF that was not clinically meaningful. Support: Teva BPP R&D, Inc. Clinical trial information: NCT01073163. [Table: see text]