Search results for: heart rate variability

Authors: Fatema-Tuz-Zohra Khanam, Ali Al-Naji, Asanka G. Perera, Kim Gibson, Javaan Chahl

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Conventional contact-based vital signs monitoring sensors such as pulse oximeters or electrocardiogram (ECG) may cause discomfort, skin damage, and infections, particularly in neonates with fragile, sensitive skin. Therefore, remote monitoring of the vital sign is desired in both clinical and non-clinical settings to overcome these issues. Camera-based vital signs monitoring is a recent technology for these applications with many positive attributes. However, there are still limited camera-based studies on neonates in a clinical setting. In this study, the heart rate (HR) and respiratory rate (RR) of eight infants at the Neonatal Intensive Care Unit (NICU) in Flinders Medical Centre were remotely monitored using a digital camera applying color and motion-based computational methods. The region-of-interest (ROI) was efficiently selected by incorporating an image decomposition method. Furthermore, spatial averaging, spectral analysis, band-pass filtering, and peak detection were also used to extract both HR and RR. The experimental results were validated with the ground truth data obtained from an ECG monitor and showed a strong correlation using the Pearson correlation coefficient (PCC) 0.9794 and 0.9412 for HR and RR, respectively. The RMSE between camera-based data and ECG data for HR and RR were 2.84 beats/min and 2.91 breaths/min, respectively. A Bland Altman analysis of the data also showed a close correlation between both data sets with a mean bias of 0.60 beats/min and 1 breath/min, and the lower and upper limit of agreement -4.9 to + 6.1 beats/min and -4.4 to +6.4 breaths/min for both HR and RR, respectively. Therefore, video camera imaging may replace conventional contact-based monitoring in NICU and has potential applications in other contexts such as home health monitoring.

Keywords: neonates, NICU, digital camera, heart rate, respiratory rate, image decomposition

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Authors: Derya Karagöz

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A Shewhart chart based on normality assumption is not appropriate for skewed distributions since its Type-I error rate is inflated. This study presents X̄ and S control charts for monitoring the process variability for skewed distributions. We propose Weighted Standard Deviation (WSD) X̄ and S control charts. Standard deviation estimator is applied to monitor the process variability for estimating the process standard deviation, in the case of the W SD X̄ and S control charts as this estimator is simple and easy to compute. Unlike the Shewhart control chart, the proposed charts provide asymmetric limits in accordance with the direction and degree of skewness to construct the upper and lower limits. The performances of the proposed charts are compared with other heuristic charts for skewed distributions by using Simulation study. The Simulation studies show that the proposed control charts have good properties for skewed distributions and large sample sizes.

Keywords: weighted standard deviation, MAD, skewed distributions, S control charts

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Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

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Authors: Haoming Ma, Guo Yu, Peiru Zhou

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Background: Previous studies show that dysglycemia, mostly hyperglycemia, hypoglycemia and glycemic variability(GV), are associated with excess mortality in critically ill patients, especially those without diabetes. Glycemic variability is an increasingly important measure of glucose control in the intensive care unit (ICU) due to this association. However, there is limited data pertaining to the relationship between different clinical factors and glycemic variability and clinical outcomes categorized by their DM status. This retrospective study of 958 intensive care unit(ICU) patients was conducted to investigate the relationship between GV and outcome in critically ill patients and further to determine the significant factors that contribute to the glycemic variability. Aim: We hypothesize that the factors contributing to mortality and the glycemic variability are different from critically ill patients with or without diabetes. And the primary aim of this study was to determine which dysglycemia (hyperglycemia\hypoglycemia\glycemic variability) is independently associated with an increase in mortality among critically ill patients in different groups (DM/Non-DM). Secondary objectives were to further investigate any factors affecting the glycemic variability in two groups. Method: A total of 958 diabetic and non-diabetic patients with severe diseases in the ICU were selected for this retrospective analysis. The glycemic variability was defined as the coefficient of variation (CV) of blood glucose. The main outcome was death during hospitalization. The secondary outcome was GV. The logistic regression model was used to identify factors associated with mortality. The relationships between GV and other variables were investigated using linear regression analysis. Results: Information on age, APACHE II score, GV, gender, in-ICU treatment and nutrition was available for 958 subjects. Predictors remaining in the final logistic regression model for mortality were significantly different in DM/Non-DM groups. Glycemic variability was associated with an increase in mortality in both DM(odds ratio 1.05; 95%CI:1.03-1.08,p＜0.001) or Non-DM group(odds ratio 1.07; 95%CI:1.03-1.11,p=0.002). For critically ill patients without diabetes, factors associated with glycemic variability included APACHE II score(regression coefficient, 95%CI:0.29,0.22-0.36,p＜0.001), Mean BG(0.73,0.46-1.01,p＜0.001), total parenteral nutrition(2.87,1.57-4.17,p＜0.001), serum albumin(-0.18,-0.271 to -0.082,p＜0.001), insulin treatment(2.18,0.81-3.55,p=0.002) and duration of ventilation(0.006,0.002-1.010,p=0.003).However, for diabetes patients, APACHE II score(0.203,0.096-0.310,p＜0.001), mean BG(0.503,0.138-0.869,p=0.007) and duration of diabetes(0.167,0.033-0.301,p=0.015) remained as independent risk factors of GV. Conclusion: We found that the relation between dysglycemia and mortality is different in the diabetes and non-diabetes groups. And we confirm that GV was associated with excess mortality in DM or Non-DM patients. Furthermore, APACHE II score, Mean BG, total parenteral nutrition, serum albumin, insulin treatment and duration of ventilation were significantly associated with an increase in GV in Non-DM patients. While APACHE II score, mean BG and duration of diabetes (years) remained as independent risk factors of increased GV in DM patients. These findings provide important context for further prospective trials investigating the effect of different clinical factors in critically ill patients with or without diabetes.

Keywords: diabetes, glycemic variability, predictors, severe disease

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Authors: Aysan Esgandanian, Sabalan Daneshvar

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The study is done to determine the comparison between proportional-integral-derivative controller (PID controller) and tilt-integral-derivative (TID controller) for cardiac pacemaker systems, which can automatically control the heart rate to accurately track a desired preset profile. The controller offers good adaption of heart to the physiological needs of the patient. The parameters of the both controllers are tuned by particle swarm optimization (PSO) algorithm which uses the integral of time square error as a fitness function to be minimized. Simulation results are performed on the developed cardiovascular system of humans and results demonstrate that the TID controller produces superior control performance than PID controllers. In this paper, all simulations were performed in Matlab.

Keywords: integral of time square error, pacemaker systems, proportional-integral-derivative controller, PSO algorithm, tilt-integral-derivative controller

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Authors: İbrahi̇m Kara, Seher Arslankaya

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Frequently preferred in the field of engineering in particular, data mining has now begun to be used in the field of health as well since the data in the health sector have reached great dimensions. With data mining, it is aimed to reveal models from the great amounts of raw data in agreement with the purpose and to search for the rules and relationships which will enable one to make predictions about the future from the large amount of data set. It helps the decision-maker to find the relationships among the data which form at the stage of decision-making. In this study, it is aimed to determine the risk of heart attack at the first stage, to control it, and to make its resource planning with the method of data mining. Through the early and correct diagnosis of heart attacks, it is aimed to reveal the factors which affect the diseases, to protect health and choose the right treatment methods, to reduce the costs in health expenditures, and to shorten the durations of patients’ stay at hospitals. In this way, the diagnosis and treatment costs of a heart attack will be scrutinized, which will be useful to determine the risk of the disease at the first stage, to control it, and to make its resource planning.

Keywords: data mining, decision support systems, heart attack, health sector

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Authors: Ratna Farida Soenarto, Anas Alatas, Made Ryan Kharmayani

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Background: Conventional ultrafiltration (CUF) system was shown to be helpful in reducing anti-inflammatory mediators for patients who underwent open heart surgery. Additionally, modified ultrafiltration (MUF) has been shown to reduce anti-inflammatory mediators further while reducing interstitial fluid volume at the same time. However, there has been minimal data concerning the efficacy of combining both ultrafiltration methods. This study aims to compare inflammation marker, vascular resistance, and cardiac index on CUF+MUF patients with CUF only patients undergoing open heart surgery. Method: This is a single blind randomized controlled trial on patients undergoing open heart surgery between June 2021 - October 2021 in CiptoMangunkusumo National Referral Hospital and Jakarta Heart Hospital. Patients wererandomized using block randomization into modified ultrafiltration following conventional ultrafiltration (CUF+MUF) and conventional ultrafiltration (CUF) only. Outcome assessed in this study were 24-hoursinterleukin-6 levels, systemic vascular resistance (SVR), pulmonary vascular resistance (PVR), and cardiac index. Results: A total of 38patients were included (19 CUF+MUF and 19 CUF subjects). There was no difference in postoperative IL-6 level between groups (p > 0.05).No difference in PVR was observed between groups.Higher difference in SVR was observed in CUF+MUF group (-646 vs. -261dyn/s/cm-5, p < 0.05). Higher cardiac index was observed on CUF+MUF group (0.93 vs. 0.48, p < 0.05). Conclusion: Patients undergoing open heart surgery with modified ultrafiltration following conventional ultrafiltration had similar systemic inflammatory response and better cardiac response than those having conventional ultrafiltration.

Keywords: open-heart, CUF, MUF, SVR, PVR, IL-6

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Authors: F. Kovács, K. Kádár, G. Hosszú, Á. T. Balogh, T. Zsedrovits, N. Kersner, A. Nagy, Gy. Jeney

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The paper presents a novel screening method to indicate congenital heart diseases (CHD), which otherwise could remain undetected because of their low level. Therefore, not belonging to the high-risk population, the pregnancies are not subject to the regular fetal monitoring with ultrasound echocardiography. Based on the fact that CHD is a morphological defect of the heart causing turbulent blood flow, the turbulence appears as a murmur, which can be detected by fetal phonocardiography (fPCG). The proposed method applies measurements on the maternal abdomen and from the recorded sound signal a sophisticated processing determines the fetal heart murmur. The paper describes the problems and the additional advantages of the fPCG method including the possibility of measurements at home and its combination with the prescribed regular cardiotocographic (CTG) monitoring. The proposed screening process implemented on a telemedicine system provides an enhanced safety against hidden cardiac diseases.

Keywords: cardiac murmurs, fetal phonocardiography, screening of CHDs, telemedicine system

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Authors: Apostolos Kalatzis, Ashish Teotia, Vishnunarayan Girishan Prabhu, Laura Stanley

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Emotions are functional behaviors influenced by thoughts, stimuli, and other factors that induce neurophysiological changes in the human body. Understanding and classifying emotions are challenging as individuals have varying perceptions of their environments. Therefore, it is crucial that there are publicly available databases and virtual reality (VR) based environments that have been scientifically validated for assessing emotional classification. This study utilized two commercially available VR applications (Guided Meditation VR™ and Richie’s Plank Experience™) to induce acute stress and calm state among participants. Subjective and objective measures were collected to create a validated multimodal dataset and classification scheme for affective state classification. Participants’ subjective measures included the use of the Self-Assessment Manikin, emotional cards and 9 point Visual Analogue Scale for perceived stress, collected using a Virtual Reality Assessment Tool developed by our team. Participants’ objective measures included Electrocardiogram and Respiration data that were collected from 25 participants (15 M, 10 F, Mean = 22.28  4.92). The features extracted from these data included heart rate variability components and respiration rate, both of which were used to train two machine learning models. Subjective responses validated the efficacy of the VR applications in eliciting the two desired affective states; for classifying the affective states, a logistic regression (LR) and a support vector machine (SVM) with a linear kernel algorithm were developed. The LR outperformed the SVM and achieved 93.8%, 96.2%, 93.8% leave one subject out cross-validation accuracy, precision and recall, respectively. The VR assessment tool and data collected in this study are publicly available for other researchers.

Keywords: affective computing, biosignals, machine learning, stress database

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Authors: Samaneh Nazeri, Bagher Mojazi Amiri, Hamid Farahmand

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Production of high quality fish eggs with reasonable hatching rate makes a success in aquaculture industries. It is influenced by the environmental stimulators and inhibitors. Diazinon is a widely-used pesticide in Golestan province (Southern Caspian Sea, North of Iran) which is washed to the aquatic environment (3 mg/L in the river). It is little known about the effect of this pesticide on the embryogenesis of sturgeon fish, the valuable species of the Caspian Sea. Hormonal content of the egg is an important factor to guaranty the successful passes of embryonic stages. In this study, the fate of Persian sturgeon embryo to 24, 48, 72, and 96-hours exposure of diazinon (LC₅₀ dose) was tested. Also, the effect of thyroid hormones (T3 and T4) on these embryos was tested concurrently or separately with diazinon LC ₅₀ dose. Fertilized eggs are exposed to T3 (low dose: 1 ng/ml, high dose: 10 ng/ml), T4 (low dose: 1 ng/ml, high dose: 10 ng/ml). Six eggs were randomly selected from each treatment (with three replicates) in five developmental stages (two cell- division, neural, heart present, heart beaten, and hatched larvae). The possibility of changing T3, T4, and cortisol contents of the embryos were determined in all treated groups and in every mentioned embryonic stage. The hatching rate in treated groups was assayed at the end of the embryogenesis to clarify the effect of thyroid hormones and diazinon. The results indicated significant differences in thyroid hormone contents, but no significant differences were recognized in cortisol levels at various early life stages of embryos. There was also significant difference in thyroid hormones in (T3, T4) + diazinon treated embryos (P˂0.05), while no significant difference between control and treatments in cortisol levels was observed. The highest hatching rate was recorded in HT3 treatment, while the lowest hatching rate was recorded for diazinon LC₅₀ treatment. The result confirmed that Persian sturgeon embryo is less sensitive to diazinon compared to teleost embryos, and thyroid hormones may increase hatching rate even in the presence of diazinon.

Keywords: Persian sturgeon, diazinon, thyroid hormones, cortisol, embryo

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Authors: Takeshi Sato, Mizuki Nakajima, Macky Kato, Shoji Igawa

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The purpose of study was to investigate the effect of varying pole weights on energy expenditure, upper limb and lower limb muscle activity as Electromyogram during Nordic walking (NW). Four healthy men [age = 22.5 (±1.0) years, body mass = 61.4 (±3.6) kg, height = 170.3 (±4.3) cm] and three healthy women [age = 22.7 (±2.9) years, body mass = 53.0 (±1.7) kg, height = 156.7 (±4.5) cm] participated in the experiments after informed consent. Seven healthy subjects were tested on the treadmill, walking, walking (W) with Nordic Poles (NW) and walking with 1kg weight Nordic Poles (NW+1). Walking speed was 6 km per hours in all trials. Eight EMG activities were recorded by bipolar surface methods in biceps brachii, triceps brachii, trapezius, deltoideus, tibialis anterior, medial gastrocnemius, rectus femoris and biceps femoris muscles. And heart rate (HR), oxygen uptake (VO₂), and rate of perceived exertion (RPE) were measured. The level of significance was set at a = 0.05, with p < 0.05 regarded as statistically significant. Our results confirmed that use of NW poles increased HR at a given upper arm muscle activity but decreased lower limb EMGs in comparison with W. Moreover NW was able to increase more step lengths with hip joint extension during NW rather than W. Also, EMG revealed higher activation of upper limb for almost all NW and 1kgNW tests plus added masses compared to W (p < 0.05). Therefore, it was thought either of NW and 1kgNW were to have benefit as a physical exercise for safe, feasible, and readily training for a wide range of aged people in the quality of daily life. However, there was no significant effected in leg muscles activity by using 1kgNW except for upper arm muscle activity during Nordic pole walking.

Keywords: Nordic walking, electromyogram, heart rate, RPE

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Authors: Yuxi Wang, Xuan Gao

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Traditional Chinese medicine has been used in the treatment of coronary heart disease (CHD) for centuries, and in recent years, the research data on the efficacy of traditional Chinese medicine through clinical trials has gradually increased to explore its real efficacy and internal pharmacology. However, due to the complexity of traditional Chinese medicine prescriptions, the efficacy of each component is difficult to clarify, and pharmacological research is challenging. This study aims to systematically review and clarify the clinical efficacy of traditional Chinese medicine in the treatment of coronary heart disease through a meta-analysis. Based on PubMed, CNKI database, Wanfang data, and other databases, eleven randomized controlled trials and 1091 CHD subjects were included. Two researchers conducted a systematic review of the papers and conducted a meta-analysis supporting the positive therapeutic effect of traditional Chinese medicine in the treatment of CHD.

Keywords: coronary heart disease, Chinese medicine, treatment, meta-analysis

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Authors: Sukovatov K.Yu., Bezuglova N.N.

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Winter precipitation variability over the Altai Krai was investigated by retrieving temporal patterns. The spectral singular analysis was used to describe the variance distribution and to reduce the precipitation data into a few components (modes). The associated time series were related to large-scale atmospheric and oceanic circulation indices by using lag cross-correlation and wavelet-coherence analysis. GPCC monthly precipitation data for rectangular field limited by 50-550N, 77-880E and monthly climatological circulation index data for the cold season were used to perform SSA decomposition and retrieve statistics for analyzed parameters on the time period 1951-2017. Interannual variability of winter precipitation over the Altai Krai are mostly caused by three natural factors: intensity variations of momentum exchange between mid and polar latitudes over the North Atlantic (explained variance 11.4%); wind speed variations in equatorial stratosphere (quasi-biennial oscillation, explained variance 15.3%); and surface temperature variations for equatorial Pacific sea (ENSO, explained variance 2.8%). It is concluded that under the current climate conditions (Arctic amplification and increasing frequency of meridional processes in mid-latitudes) the second and the third factors are giving more significant contribution into explained variance of interannual variability for cold season atmospheric precipitation over the Altai Krai than the first factor.

Keywords: interannual variability, winter precipitation, Altai Krai, wavelet-coherence

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Authors: Olumuyiwa Idowu Ojo, Oluwatobi Peter Olowo

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The study developed a Geographical Information Systems (GIS) database and mapped inter-annual changes in crop yields of cassava, cowpea, maize, rice, melon and yam as a response to inter-annual rainfall and temperature variability in Southwest, Nigeria. The aim of this project is to study the comparative analysis of the weather variability impact of six crops yield (Rice, melon, yam, cassava, Maize and cowpea) in South Western States of Nigeria (Oyo, Osun, Ekiti, Ondo, Ogun and Lagos) from 1991 – 2007. The data was imported and analysed in the Arch GIS 9 – 3 software environment. The various parameters (temperature, rainfall, crop yields) were interpolated using the kriging method. The results generated through interpolation were clipped to the study area. Geographically weighted regression was chosen from the spatial statistics toolbox in Arch GIS 9.3 software to analyse and predict the relationship between temperature, rainfall and the different crops (Cowpea, maize, rice, melon, yam, and cassava).

Keywords: GIS, crop yields, comparative analysis, temperature, rainfall, weather variability

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Authors: Arega Shumetie Ademe, Belay Kassa, Degye Goshu, Majaliwa Mwanjalolo

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Currently the world economy is suffering from one critical problem, climate change. Some studies done before identified that impact of the problem is region specific means in some part of the world (temperate zone) there is improvement in agricultural performance but in some others like in the tropics there is drastic reduction in crop production and crop income. Climate variability is becoming dominant cause of short-term fluctuation in rain-fed agricultural production and income of developing countries. The purely rain-fed Ethiopian agriculture is the most vulnerable sector to the risks and impacts of climate variability. Thus, this study tried to identify impact of climate variability on crop income of smallholders in Ethiopia. The research used eight rounded unbalanced panel data from 1994- 2014 collected from six villages in the study area. After having all diagnostic tests the research used fixed effect method of regression. Based on the regression result rainfall and temperature deviation from their respective long term averages have negative and significant effect on crop income. Other extreme devastating shocks like flood, storm and frost, which are sourced from climate variability, have significant and negative effect on crop income of households’. Parameters that notify rainfall inconsistency like late start, variation in availability at growing season, and early cessation are critical problems for crop income of smallholder households as to the model result. Given this, impact of climate variability is not consistent in different agro-ecologies of the country. Rainfall variability has similar impact on crop income in different agro-ecology, but variation in temperature affects cold agro-ecology villages negatively and significantly, while it has positive effect in warm villages. Parameters that represent rainfall inconsistency have similar impact in both agro-ecologies and the aggregate model regression. This implies climate variability sourced from rainfall inconsistency is the main problem of Ethiopian agriculture especially the crop production sub-sector of smallholder households.

Keywords: climate variability, crop income, household, rainfall, temperature

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Authors: Y. Melis, E. Apicella, E. Dozio, L. Mendolicchio

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Introduction: Feeding and Eating Disorders (FED) represent the psychiatric pathology with the highest mortality rate and one of the major disorders with the highest psychiatric and clinical comorbidity. The vagus nerve represents one of the main components of the sympathetic and parasympathetic nervous system and is involved in important neurophysiological functions. In FED, there is a spectrum of symptoms which with TaVNS (Transcutaneous Auricular Vagus Nerve Stimulation) therapy, is possible to have a therapeutic efficacy. Materials and Methods: Sample subjects are composed of 15 female subjects aged > 18 ± 51. Admitted to a psychiatry community having been diagnosed according to DSM-5: anorexia nervosa (AN) (N= 9), bulimia nervosa (BN) (N= 5), binge eating disorder (BED) (N= 1). The protocol included 9 weeks of Ta-VNS stimulation at a frequency of 1.5-3.5 mA for 4 hours per day. The variables detected are the following: Heart Rate Variability (HRV), Hamilton Depression Rating Scale (HAMD-HDRS-17), Body Mass Index (BMI), Beck Anxiety Index (BAI). Results: Data analysis showed statistically significant differences between recording times (p > 0.05) in HAM-D (t0 = 18.28 ± 5.31; t4 = 9.14 ± 7.15), in BAI (t0 = 24.7 ± 10.99; t4 = 13.8 ± 7.0). The reported values show how during (T0-T4) the treatment there is a decay of the degree in the depressive state, in the state of anxiety, and an improvement in the value of BMI. In particular, the BMI in the AN-BN sub-sample had a minimum gain of 5% and a maximum of 11%. The analysis of HRV did not show a clear change among subjects, thus confirming the discordance of the activity of the sympathetic and parasympathetic nervous system in FED. Conclusions: Although the sample does not possess a relevant value to determine long-term efficacy of Ta-VNS or on a larger population, this study reports how the application of neuro-stimulation in FED may become a further approach therapeutic. Indeed, substantial improvements are highlighted in the results and confirmed hypotheses proposed by the study.

Keywords: feeding and eating disorders, neurostimulation, anxiety disorders, depression

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Authors: Jonnalagadda Naveen, M. P. S. Tomar, Putluru Satish, Palanisamy Dharani

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Present investigation was carried out on a single specimen of the heart of yellow-bellied sea snake, which accidentally came to the seashore with the fisherman’s net. After the death, these specimens was preserved in 10% neutral buffered formalin and observe for its morphology. The literature cited revealed that meager information was available on the anatomy of the heart of this species of snake thus present study was planned on the gross anatomy of the heart of yellow-bellied sea snake. The heart of yellow-bellied sea snake was located between 28-35th rib in an oblique direction in the pericardial sac. It was three chambered with the complete division of atria but the ventricular cavity was incompletely divided. The apex did not show any gubernaculum cordis. The sinus venosus was the common cavity for confluence of anterior and posterior vana cava and the jugular vein was opened with anterior vena cava. The opening of posterior vena cava was slit-like and it was guarded by membranous valves whereas no valve could be observed at the opening of anterior vana cava and the jugular vein. Both the caval veins ran along the right border of the heart. Pulmonary vein was single which later divided into two branches. The length-width index for the atria was 1.33 whereas it was 1.67 for the ventricle. The atrioventricular canal was situated slightly towards the left of the midline of the heart and was divided into a right cavum pulmonale and left cavum arteriosum of which the right one was slightly larger and longer than the left. The cavum venosum was present in between the cavum pulmonale and the cavum arteriosum. The Ventricle was elongated triangle muscular compartment with ventrally located apex. Internally the cavity of ventricle was divided into two partial chambers dorsally by a muscular ridge and ventrally by an incomplete inter ventricular septum.

Keywords: aorta, atrium, heart, sea snake, sinus venosus, ventricle

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Authors: Shekoufeh Behdad, Sahar Yadegari, Alireza Ghehrazad, Amirhossein Yadegari

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Background: In this study, we compared the effect of intravenous dexamethasone with placebo on hemodynamic variables and hypotension in patients undergoing cesarean section under spinal anesthesia. Materials and methods: This double-blind, randomized clinical trial was conducted with the approval of the university ethics committee. Written informed consent was obtained from all participating patients. Before spinal anesthesia, patients were randomly assigned to receive either dexamethasone (8 mg IV) or placebo (normal saline). Hemodynamic variables, including systolic, diastolic, and mean arterial blood pressures, as well as heart rate, were measured before drug administration and every 3 minutes until the birth of the neonate and then every 5 minutes until the end of surgery. Side effects such as hypotension, bradycardia, nausea, and vomiting were assessed and recorded for all the patients. Results: There were no significant differences in mean systolic, diastolic, and mean arterial blood pressures before and after administration of the studied drugs in both groups (P.Value>0.05), but heart rate and the incidence of hypotension in the dexamethasone group were less than placebo significantly. Conclusions: Intravenous administration of 8 mg dexamethasone before spinal anesthesia in females undergoing cesarean section can reduce the incidence of post-spinal hypotension without causing serious side effects.

Keywords: cesarean section, hypotension, spinal anesthesia, dexamethasone

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Authors: Maryam Borjali

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Introduction. Mortality due to noncommunicable diseases has increased in the world today with the advent of demographic shifts, growing age, and lifestyle patterns in the world, which have been affected by economic and social crises. Congenital heart defects are one of the forms of diseases that have raised infant mortality worldwide. e objective of present study was to identify nonmedical determinants related to this abnormality from the mother’s perspectives. Methods. is research was a qualitative study and the data collection method was a semistructured interview with mothers who had children with congenital heart diseases referring to the Shahid Rajaei Heart Hospital in Tehran, Iran. A thematic analysis approach was employed to analyze transcribed documents assisted by MAXQDA Plus version 12. Results. Four general themes and ten subthemes including social contexts (social harms, social interactions, and social necessities), psychological contexts (mood disorders and mental well-being), cultural contexts (unhealthy lifestyle, family culture, and poor parental health behaviors), and environmental contexts (living area and polluted air) were extracted from interviews with mothers of children with congenital heart diseases. Conclusions. Results suggest that factors such as childhood poverty, lack of parental awareness of congenital diseases, lack of proper nutrition and health facilities, education, and lack of medical supervision during pregnancy were most related with the birth of children with congenital heart disease from mothers’ prospective. In this regard, targeted and intersectorial collaborations are proposed to address nonmedical determinants related to the incidence of congenital heart diseases.

Keywords: congenital_cou, cultural, social, platform

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Authors: Rohit Sane, Snehal Dongre, Pravin Ghadigaonkar, Rahul Mandole

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The present study was designed to evaluate efficacy of heart failure reversal therapy (HFRT) that uses herbal procedure (panchakarma) and allied therapies, in chronic heart failure (CHF) patients with low ejection fraction. Methods: This efficacy study was conducted in CHF patients (aged: 25-65 years, ejection fraction (EF) < 30%) wherein HFRT (60-75 minutes) consisting of snehana (external oleation), swedana (passive heat therapy), hrudaydhara(concoction dripping treatment) and basti(enema) was administered twice daily for 7 days. During this therapy and next 30 days, patients followed the study dinarcharya and were prescribed ARJ kadha in addition to their conventional treatment. The primary endpoint of this study was evaluation of maximum aerobic capacity uptake (MAC) as assessed by 6-minute walk distance (6MWD) using Cahalins equation from baseline, at end of 7 day treatment, follow-up after 30 days and 90 days. EF was assessed by 2D Echo at baseline and after 30 days of follow-up. Results: CHF patients with < 30% EF (N=52, mean [SD] age: 58.8 [10.8], 85% men) were enrolled in the study. There was a 100% compliance to study therapy. A significant improvement was observed in MAC levels (7.11%, p =0.029), at end of 7 day therapy as compared to baseline. This improvement was maintained at two follow-up visits. Moreover, ejection fraction was observed to be increased by 6.38%, p=0,012 as compared to baseline at day 7 of the therapy. Conclusions: This 90 day follow up study highlights benefit of HFRT, as a part of maintenance treatment for CHF patients with reduced ejection fraction.

Keywords: chronic heart failure, functional capacity, heart failure reversal therapy, oxygen uptake, panchakarma

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Authors: Jyotismita Talukdar

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In this paper, a study has been made on the possibility and accuracy of early prediction of several Heart Disease using Artificial Neural Network. (ANN). The study has been made in both noise free environment and noisy environment. The data collected for this analysis are from five Hospitals. Around 1500 heart patient’s data has been collected and studied. The data is analysed and the results have been compared with the Doctor’s diagnosis. It is found that, in noise free environment, the accuracy varies from 74% to 92%and in noisy environment (2dB), the results of accuracy varies from 62% to 82%. In the present study, four basic attributes considered are Blood Pressure (BP), Fasting Blood Sugar (FBS), Thalach (THAL) and Cholesterol (CHOL.). It has been found that highest accuracy(93%), has been achieved in case of PPI( Post-Permanent-Pacemaker Implementation ), around 79% in case of CAD(Coronary Artery disease), 87% in DCM (Dilated Cardiomyopathy), 89% in case of RHD&MS(Rheumatic heart disease with Mitral Stenosis), 75 % in case of RBBB +LAFB (Right Bundle Branch Block + Left Anterior Fascicular Block), 72% for CHB(Complete Heart Block) etc. The lowest accuracy has been obtained in case of ICMP (Ischemic Cardiomyopathy), about 38% and AF( Atrial Fibrillation), about 60 to 62%.

Keywords: coronary heart disease, chronic stable angina, sick sinus syndrome, cardiovascular disease, cholesterol, Thalach

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Authors: Ammar S. M. Moohialdin, Bambang T. Suhariadi, Mohsin Siddiqui

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This paper addresses the application of physiological status monitoring (PSM) for assessing the impact of harsh weather conditions on sports activities in universities in Saudi Arabia. Real sports measurement was conducted during sports activities such that the physiological status (HR and BR) of five students were continuously monitored by using Zephyr BioHarness^TM 3.0 sensors in order to identify the physiological bonds and zones. These bonds and zones were employed as indicators of the associated physiological risks of the performed sports activities. Furthermore, a short yes/no questionnaire was applied to collect information on participants’ health conditions and opinions of the applied PSM sensors. The results show the absence of a warning system as a protective aid for the hazardous levels of extremely hot and humid weather conditions that may cause dangerous and fatal circumstances. The applied formulas for estimating maximum HR provides accurate estimations for Maximum Heart Rate (HR_max). The physiological results reveal that the performed activities by the participants are considered the highest category (90–100%) in terms of activity intensity. This category is associated with higher HR, BR and physiological risks including losing the ability to control human body behaviors. Therefore, there is a need for immediate intervention actions to reduce the intensity of the performed activities to safer zones. The outcomes of this study assist the safety improvement of sports activities inside universities and athletes performing their sports activities. To the best of our knowledge, this is the first paper to represent a special case of the application of PSM technology for assessing sports activities in universities considering the impacts of harsh weather conditions on students’ health and safety.

Keywords: physiological status monitoring (PSM), heart rate (HR), breathing rate (BR), Arabian Gulf

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Authors: Mecheri Zeid Belmecheri, Maamar Ahfir, Izzet Kale

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Automatic cardiac auscultation is still a subject of research in order to establish an objective diagnosis. Recorded heart sounds as Phonocardiogram signals (PCG) can be used for automatic segmentation into components that have clinical meanings. These are the first sound, S1, the second sound, S2, and the systolic and diastolic components, respectively. In this paper, an automatic method is proposed for the robust segmentation of heart sounds. This method is based on calculating an intermediate sawtooth-shaped signal from the length variation of the recorded Phonocardiogram (PCG) signal in the time domain and, using its positive derivative function that is a binary signal in training a Recurrent Neural Network (RNN). Results obtained in the context of a large database of recorded PCGs with their simultaneously recorded ElectroCardioGrams (ECGs) from different patients in clinical settings, including normal and abnormal subjects, show a segmentation testing performance average of 76 % sensitivity and 94 % specificity.

Keywords: heart sounds, PCG segmentation, event detection, recurrent neural networks, PCG curve length

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Authors: Karakhalis N. B.

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This study aimed to determine the prevalence of heparin resistance among cardiac surgical pediatric and neonatal patients and identify associated risk factors. Materials and Methods: The study included 306 pediatric and neonatal patients undergoing on-pump cardiac surgery. Patients whose activated clotting time (ACT) targets were achieved after the first administration of heparin formed the 1st group (n=280); the 2nd group (n=26) included patients with heparin resistance. The initial assessment of the haemostasiological profile included determining the PT, aPPT, FG, AT III activity, and INR. Intraoperative control of heparinization was carried out with a definition of ACT using a kaolin activator. A weight-associated protocol at the rate of 300 U/kg with target values of ACT >480 sec was used for intraoperative heparinization. Results: The heparin resistance was verified in 8.5% of patients included in the study. Repeated heparin administration at the maximum dose of≥600 U/kg is required in 80.77% of cases. Despite additional heparinization, 19.23% of patients had FFP infusion. There was reduced antithrombin activity in the heparin resistance group (p=0.01). Most patients with heparin resistance (57.7%) were pretreated with low molecular weight heparins during the preoperative period. Conclusion: Determining the initial level of antithrombin activity can predict the risk of developing heparin resistance. The factor analysis verified hidden risk factors for heparin resistance to the heparin pretreatment, chronic hypoxia, and chronic heart failure.

Keywords: congenital heart disease, heparin, antithrombin, activated clotting time, heparin resistance

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Authors: Kuei-Yu Chien, Nai-Wen Kan, Wan-Chun Wu, Guo-Dong Ma, Shu-Chen Chen

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Purpose: The purpose of this study was to investigate the responses of systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate (HR), rating of perceived exertion (RPE) and lactate following continued high-intensity interval exercise in water and on land. The results of studies can be an exercise program design reference for health care and fitness professionals. Method: A total of 20 volunteer postmenopausal women was included in this study. The inclusion criteria were: duration of menopause > 1 year; and sedentary lifestyle, defined as engaging in moderate-intensity exercise less than three times per week, or less than 20 minutes per day. Participants need to visit experimental place three times. The first time visiting, body composition was performed and participant filled out the questionnaire. Participants were assigned randomly to the exercise environment (water or land) in second and third time visiting. Water exercise testing was under water of trochanter level. In continuing jump testing, each movement consisted 10-second maximum volunteer jump for two sets. 50% heart rate reserve dynamic resting (walking or running) for one minute was within each set. SBP, DBP, HR, RPE of whole body/thigh (RPEW/RPET) and lactate were performed at pre and post testing. HR, RPEW, and RPET were monitored after 1, 2, and 10 min of exercise testing. SBP and DBP were performed after 10 and 30 min of exercise testing. Results: The responses of SBP and DBP after exercise testing in water were higher than those on land. Lactate levels after exercise testing in water were lower than those on land. The responses of RPET were lower than those on land post exercise 1 and 2 minutes. The heart rate recovery in water was faster than those on land at post exercise 5 minutes. Conclusion: This study showed water interval jump exercise induces higher cardiovascular responses with lower RPE responses and lactate levels than on-land jumps exercise in postmenopausal women. Fatigue is one of the major reasons to obstruct exercise behavior. Jump exercise could enhance cardiorespiratory fitness, the lower-extremity power, strength, and bone mass. There are several health benefits to the middle to older adults. This study showed that water interval jumping could be more relaxed and not tried to reach the same land-based cardiorespiratory exercise intensity.

Keywords: interval exercise, power, recovery, fatigue

Procedia PDF Downloads 382

Authors: B. B. Siswanto, A. Halimi, K. M. H. J. Tandayu, C. Abdillah, F. Nanda , E. Chandra

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Nowadays, modern cardiac biomarkers, such as ST2 and NT-proBNP, have important roles in predicting morbidity and mortality in heart failure patients. Abnormalities of serum electrolytes, sepsis or infection, and deteriorating renal function will worsen the conditions of patients with heart failure. It is intriguing to know whether cardiac biomarkers elevations are affected by laboratory findings in heart failure patients. We recruited 65 patients from the heart failure clinic in NCVC Harapan Kita in 2014-2015. All of them have consented for laboratory examination, including cardiac biomarkers. The findings were recorded in our Research and Development Centre and analyzed using linear regression to find whether there is a relationship between laboratory findings (sodium, potassium, creatinine, and leukocytes) and ST2 or NT-proBNP. From 65 patients, 26.9% of them are female, and 73.1% are male, 69.4% patients classified as NYHA I-II and 31.6% as NYHA III-IV. The mean age is 55.7+11.4 years old; mean sodium level is 136.1+6.5 mmol/l; mean potassium level is 4.7+1.9 mmol/l; mean leukocyte count is 9184.7+3622.4 /ul; mean creatinine level is 1.2+0.5 mg/dl. From linear regression logistics, the relationship between NT-proBNP and sodium level (p<0.001), as well as leukocyte count (p=0.002) are significant, while NT-proBNP and potassium level (p=0.05), as well as creatinine level (p=0.534) are not significant. The relationship between ST2 and sodium level (p=0.501), potassium level (p=0.76), leukocyte level (p=0.897), and creatinine level (p=0.817) are not significant. To conclude, laboratory findings are more sensitive in predicting NT-proBNP elevation than ST2 elevation. Larger studies are needed to prove that NT-proBNP correlation with laboratory findings is more superior than ST2.

Keywords: heart failure, laboratory, NT-proBNP, ST2

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Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Abdoulahad Allamine

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The objective of this study is to assess the impact of climate variability on agriculture and food security in 43 countries of sub-Saharan Africa. We use for this purpose the data from BADC bases, UNCTAD, and WDI FAOSTAT to estimate a VAR model on panel data. The sample is divided into three (03) agro-climatic zones, more explicitly the equatorial zone, the Sahel region and the semi-arid zone. This allows to highlight the differential impacts sustained by countries and appropriate responses to each group of countries. The results show that the sharp fluctuations in the volume of rainfall negatively affect agriculture and food security of countries in the equatorial zone, with heavy rainfall and high temperatures in the Sahel region. However, countries with low temperatures and low rainfall are the least affected. The hedging policies against the risks of climate variability must be more active in the first two groups of countries. On this basis and in general, we recommend integration of agricultural policies between countries is done to reduce the effects of climate variability on agriculture and food security. It would be logical to encourage regional and international closer collaboration on the development and dissemination of improved varieties, ecological intensification, and management of biotic and abiotic stresses facing these climate variability to sustainably increase food production. Small farmers also need training in agricultural risk hedging techniques related to climate variations; this requires an increase in state budgets allocated to agriculture.

Keywords: agro-climatic zones, climate variability, food security, Sub-Saharan Africa, VAR on panel data

Procedia PDF Downloads 347

Authors: Kun Chen, Yan Wang, Yangyu Zhao, Shufang Li, Lian Chen, Xiaoyue Guo, Jue Zhang, Jing Fang

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The coupling strength between uterine electromyography (UEMG) and Fetal heart rate (FHR) signals during peripartum reflects the fetal biophysical activities. Therefore, UEMG-FHR coupling characterization is instructive in assessing placenta function. This study introduced a physiological marker named elevated frequency of UEMG-FHR coupling (E-UFC) and explored its predictive value for pregnancies complicated by pre-eclampsia and small for gestational age (SGA). Placental insufficiency patients (n=12) and healthy volunteers (n=24) were recruited and participated. UEMG and FHR were recorded non-invasively by a trans-abdominal device in women at term with singleton pregnancy (32-37 weeks) from 10:00 pm to 8:00 am. The product of the wavelet coherence and the wavelet cross-spectral power between UEMG and FHR was used to weight these two effects in order to quantify the degree of the UEMG-FHR coupling. E-UFC was exacted from the resultant spectrogram by calculating the mean value of the high-coherence (r > 0.5) frequency band. Results showed the high-coherence between UEMG and FHR was observed in the frequency band (1/512-1/16Hz). In addition, E-UFC in placental insufficiency patients was weaker compared to healthy controls (p < 0.001) at group level. These findings suggested the proposed approach could be used to quantitatively characterize the fetal biophysical activities, which is beneficial for early detection of placental insufficiency and reduces the occurrence of adverse pregnancy.

Keywords: uterine electromyography, fetal heart rate, coupling analysis, wavelet analysis

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Authors: Mohammed Alenezy

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The function of cardiac motion can be used as an indicator of the heart abnormality by evaluating longitudinal, circumferential, and Radial Strain of the left ventricle. In this paper, the Radial Strain and SR is studied using tagged MRI (tMRI) data during the cardiac cycle on the mid-ventricle level of the left ventricle. Materials and methods: The short-axis view of the left ventricle of five healthy human (three males and two females) and four healthy male rats were imaged using tagged magnetic resonance imaging (tMRI) technique covering the whole cardiac cycle on the mid-ventricle level. Images were processed using Image J software to calculate the left ventricle wall Radial Strain and radial SR. The left ventricle Radial Strain and radial SR were calculated at the mid-ventricular level during the cardiac cycle. The peak Radial Strain for the human and rat heart was 40.7±1.44, and 46.8±0.68 respectively, and it occurs at 40% of the cardiac cycle for both human and rat heart. The peak diastolic and systolic radial SR for human heart was -1.78 s-1 ± 0.02 s-1 and 1.10±0.08 s-1 respectively, while for rat heart it was -5.16± 0.23s-1 and 4.25±0.02 s-1 respectively. Conclusion: This results show the ability of the tMRI data to characterize the cardiac motion during the cardiac cycle including diastolic and systolic phases which can be used as an indicator of the cardiac dysfunction by estimating the left ventricle Radial Strain and radial SR at different locations of the cardiac tissue. This study approves the validity of the tagged MRI data to describe accurately the cardiac radial motion.

Keywords: left ventricle, radial strain, tagged MRI, cardiac cycle

Procedia PDF Downloads 456