Search results for: Ocular diseases

Authors: B. S. Raghavendra, D. Narayana Dutt

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Electroencephalogram (EEG) recordings are often contaminated with ocular and muscle artifacts. In this paper, the canonical correlation analysis (CCA) is used as blind source separation (BSS) technique (BSS-CCA) to decompose the artifact contaminated EEG into component signals. We combine the BSSCCA technique with wavelet filtering approach for minimizing both ocular and muscle artifacts simultaneously, and refer the proposed method as wavelet enhanced BSS-CCA. In this approach, after careful visual inspection, the muscle artifact components are discarded and ocular artifact components are subjected to wavelet filtering to retain high frequency cerebral information, and then clean EEG is reconstructed. The performance of the proposed wavelet enhanced BSS-CCA method is tested on real EEG recordings contaminated with ocular and muscle artifacts, for which power spectral density is used as a quantitative measure. Our results suggest that the proposed hybrid approach minimizes ocular and muscle artifacts effectively, minimally affecting underlying cerebral activity in EEG recordings.

Keywords: Blind source separation, Canonical correlationanalysis, Electroencephalogram, Muscle artifact, Ocular artifact, Power spectrum, Wavelet threshold.

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Authors: V Krishnaveni, S Jayaraman, K Ramadoss

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The electrical potentials generated during eye movements and blinks are one of the main sources of artifacts in Electroencephalogram (EEG) recording and can propagate much across the scalp, masking and distorting brain signals. In recent times, signal separation algorithms are used widely for removing artifacts from the observed EEG data. In this paper, a recently introduced signal separation algorithm Mutual Information based Least dependent Component Analysis (MILCA) is employed to separate ocular artifacts from EEG. The aim of MILCA is to minimize the Mutual Information (MI) between the independent components (estimated sources) under a pure rotation. Performance of this algorithm is compared with eleven popular algorithms (Infomax, Extended Infomax, Fast ICA, SOBI, TDSEP, JADE, OGWE, MS-ICA, SHIBBS, Kernel-ICA, and RADICAL) for the actual independence and uniqueness of the estimated source components obtained for different sets of EEG data with ocular artifacts by using a reliable MI Estimator. Results show that MILCA is best in separating the ocular artifacts and EEG and is recommended for further analysis.

Keywords: Electroencephalogram, Ocular Artifacts (OA), Independent Component Analysis (ICA), Mutual Information (MI), Mutual Information based Least dependent Component Analysis(MILCA)

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Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara

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Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.

Keywords: Ocular diseases, retinal fundus image, optic disc detection and segmentation, fully convolutional network, overlap measure.

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Authors: Parisa Shooshtari, Gelareh Mohamadi, Behnam Molaee Ardekani, Mohammad Bagher Shamsollahi

Abstract:

EEG signal is one of the oldest measures of brain activity that has been used vastly for clinical diagnoses and biomedical researches. However, EEG signals are highly contaminated with various artifacts, both from the subject and from equipment interferences. Among these various kinds of artifacts, ocular noise is the most important one. Since many applications such as BCI require online and real-time processing of EEG signal, it is ideal if the removal of artifacts is performed in an online fashion. Recently, some methods for online ocular artifact removing have been proposed. One of these methods is ARMAX modeling of EEG signal. This method assumes that the recorded EEG signal is a combination of EOG artifacts and the background EEG. Then the background EEG is estimated via estimation of ARMAX parameters. The other recently proposed method is based on adaptive filtering. This method uses EOG signal as the reference input and subtracts EOG artifacts from recorded EEG signals. In this paper we investigate the efficiency of each method for removing of EOG artifacts. A comparison is made between these two methods. Our undertaken conclusion from this comparison is that adaptive filtering method has better results compared with the results achieved by ARMAX modeling.

Keywords: Ocular Artifacts, EEG, Adaptive Filtering, ARMAX

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Authors: Nicoletta Adamo-Villani, Gerardo Beni, Jeremy White

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We introduce a new interactive 3D simulator of ocular motion and expressions suitable for: (1) character animation applications to game design, film production, HCI (Human Computer Interface), conversational animated agents, and virtual reality; (2) medical applications (ophthalmic neurological and muscular pathologies: research and education); and (3) real time simulation of unconscious cognitive and emotional responses (for use, e.g., in psychological research). Using state-of-the-art computer animation technology we have modeled and rigged a physiologically accurate 3D model of the eyes, eyelids, and eyebrow regions and we have 'optimized' it for use with an interactive and web deliverable platform. In addition, we have realized a prototype device for realtime control of eye motions and expressions, including unconsciously produced expressions, for application as in (1), (2), and (3) above. The 3D simulator of eye motion and ocular expression is, to our knowledge, the most advanced/realistic available so far for applications in character animation and medical pedagogy.

Keywords: 3D animation, HCI, medical simulation, ocularmotion and expression.

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Authors: Irfan Z. Qureshi, Fareeha A., Wajid A. Khan

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Human amniotic membrane (HAM) is a useful biological material for the reconstruction of damaged ocular surface. The processing and preservation of HAM is critical to prevent the patients undergoing amniotic membrane transplant (AMT) from cross infections. For HAM preparation human placenta is obtained after an elective cesarean delivery. Before collection, the donor is screened for seronegativity of HCV, Hbs Ag, HIV and Syphilis. After collection, placenta is washed in balanced salt solution (BSS) in sterile environment. Amniotic membrane is then separated from the placenta as well as chorion while keeping the preparation in BSS. Scrapping of HAM is then carried out manually until all the debris is removed and clear transparent membrane is acquired. Nitrocellulose membrane filters are then placed on the stromal side of HAM, cut around the edges with little membrane folded towards other side making it easy to separate during surgery. HAM is finally stored in solution of glycerine and Dulbecco-s Modified Eagle Medium (DMEM) in 1:1 ratio containing antibiotics. The capped borosil vials containing HAM are kept at -80°C until use. This vial is thawed to room temperature and opened under sterile operation theatre conditions at the time of surgery.

Keywords: HAM, AMT, ocular transplant

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Authors: Kateřina Sekulová, Michal Šimon

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Ergonomics is a useful tool for creating a healthy and safe workplace. The long-term action of harmful conditions on the health of workers is the emergence of occupational disease, and the firm-s increased compensation costs associated with these diseases, but is also the loss of time needed for educating and including new workers in the work process. The article deals with the link of ergonomics to occupational diseases, factors which influence these diseases. In the conclusion, a model is described to help reduce the risk of selected occupational diseases using ergonomic principles and knowledge.

Keywords: ergonomics, occupational diseases, optimization, workplace health

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Authors: Khaled M. Ali, M. A. Abdel-Hamid, Ayman A. Mostafa

Abstract:

Objective: Safety and efficacy of Ahmed glaucoma valve implantation for the management of uveitis induced glaucoma evaluated on the five dogs with uncontrollable glaucoma. Materials and Methods: Ahmed Glaucoma Valve (AGV®; New World Medical, Rancho Cucamonga, CA, USA) is a flow restrictive, nonobstructive self-regulating valve system. Preoperative ocular evaluation included direct ophthalmoscopy and measurement of the intraocular pressure (IOP). The implant was examined and primed prior to implantation. The selected site of the valve implantation was the superior quadrant between the superior and lateral rectus muscles. A fornix-based incision was made through the conjunectiva and Tenon’s capsule. A pocket is formed by blunt dissection of Tenon’s capsule from the episclera. The body of the implant was inserted into the pocket with the leading edge of the device around 8-10 mm from the limbus. Results: No post-operative complications were detected in the operated eyes except a persistent corneal edema occupied the upper half of the cornea in one case. Hyphaema was very mild and seen only in two cases which resolved quickly two days after surgery. Endoscopical evaluation for the operated eyes revealed a normal ocular fundus with clearly visible optic papilla, tapetum and retinal blood vessels. No evidence of hemorrhage, infection, adhesions or retinal abnormalities was detected. Conclusion: Ahmed glaucoma valve is safe and effective implant for treatment of uveitic glaucoma in dogs.

Keywords: Ahmed valve, endoscopy, glaucoma, ocular fundus.

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Authors: Nicoletta Adamo-Villani, Gerardo Beni, Jeremy White

Abstract:

We introduce, a new interactive 3D simulation system of ocular motion and expressions suitable for: (1) character animation applications to game design, film production, HCI (Human Computer Interface), conversational animated agents, and virtual reality; (2) medical applications (ophthalmic neurological and muscular pathologies: research and education); and (3) real time simulation of unconscious cognitive and emotional responses (for use, e.g., in psychological research). The system is comprised of: (1) a physiologically accurate parameterized 3D model of the eyes, eyelids, and eyebrow regions; and (2) a prototype device for realtime control of eye motions and expressions, including unconsciously produced expressions, for application as in (1), (2), and (3) above. The 3D eye simulation system, created using state-of-the-art computer animation technology and 'optimized' for use with an interactive and web deliverable platform, is, to our knowledge, the most advanced/realistic available so far for applications to character animation and medical pedagogy.

Keywords: 3D animation, HCI, medical simulation, ocularmotion and expression.

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Authors: V Krishnaveni, S Jayaraman, A Gunasekaran, K Ramadoss

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The ElectroEncephaloGram (EEG) is useful for clinical diagnosis and biomedical research. EEG signals often contain strong ElectroOculoGram (EOG) artifacts produced by eye movements and eye blinks especially in EEG recorded from frontal channels. These artifacts obscure the underlying brain activity, making its visual or automated inspection difficult. The goal of ocular artifact removal is to remove ocular artifacts from the recorded EEG, leaving the underlying background signals due to brain activity. In recent times, Independent Component Analysis (ICA) algorithms have demonstrated superior potential in obtaining the least dependent source components. In this paper, the independent components are obtained by using the JADE algorithm (best separating algorithm) and are classified into either artifact component or neural component. Neural Network is used for the classification of the obtained independent components. Neural Network requires input features that exactly represent the true character of the input signals so that the neural network could classify the signals based on those key characters that differentiate between various signals. In this work, Auto Regressive (AR) coefficients are used as the input features for classification. Two neural network approaches are used to learn classification rules from EEG data. First, a Polynomial Neural Network (PNN) trained by GMDH (Group Method of Data Handling) algorithm is used and secondly, feed-forward neural network classifier trained by a standard back-propagation algorithm is used for classification and the results show that JADE-FNN performs better than JADEPNN.

Keywords: Auto Regressive (AR) Coefficients, Feed Forward Neural Network (FNN), Joint Approximation Diagonalisation of Eigen matrices (JADE) Algorithm, Polynomial Neural Network (PNN).

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Authors: Piyush Samant, Ravinder Agarwal

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Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: Complementary and alternative medicine, Iridology, iris, feature extraction, classification, disease prediction.

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Authors: H. Al-Khalaifa, A. Al-Nasser

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The viewpoint towards the use of drugs or vaccines against avian parasitic diseases is one of the most striking challenges in avian medical parasitology. This includes many difficulties associated with drug resistance and in developing prophylactic vaccines. In many instances, the potential success of a vaccination in controlling parasitic diseases in poultry is well-documented. However, some medical, technical and financial limitations are still paramount. On the other hand, chemotherapy is not very well-recommended due to a number of medical limitations. But in the absence of an effective vaccine, drugs are used against parasitic diseases. This paper sheds light on some the advantages and disadvantages of using vaccination and drugs in controlling parasitic diseases in poultry species. The usage of chemotherapeutic drugs is discussed with some examples. Then, more light will be shed on using vaccines as a potentially effective and promising control tool.

Keywords: Drugs, parasitology, poultry, vaccines.

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Authors: Ilma Robo, Saimir Heta, Merilda Tarja, Sonila Kapaj, Eduart Kapaj, Geriona Lasku

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The classification of periodontal diseases has changed significantly in favor of simplifying the protocol of diagnosis and periodontal treatment. This review study aims to highlight the latest publications in the new periodontal disease classification, talking about the most significant differences versus the old classification with the tendency to express the advantages or disadvantages of clinical application. The aim of the study also includes the growing tendency to link the way of classification of periodontal diseases with predetermined protocols of periodontal treatment of the diagnoses included in the classification. The new classification of periodontal diseases is rather comprehensive in its subdivisions, as the disease is viewed in its entirety, with the biological dimensions of the disease, the degree of aggravation and progression of the disease, in relation to risk factors, predisposition to patient susceptibility and impact of periodontal disease to the general health status of the patient.

Keywords: Periodontal diseases, clinical application, periodontal treatment, oral diagnosis.

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Authors: Jae-Yeon Song, Seung-Yerl Lee, Kyu-Yeul Wang, Byung-Soo Kim, Sang-Seol Lee, Seong-Seob Shin, Jae-Young Choi, Chong Ho Lee, Jeahyun Park, Duck-Jin Chung

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In this paper, we propose disease diagnosis hardware architecture by using Hypernetworks technique. It can be used to diagnose 3 different diseases (SPECT Heart, Leukemia, Prostate cancer). Generally, the disparate diseases require specified diagnosis hardware model for each disease. Using similarities of three diseases diagnosis processor, we design diagnosis processor that can diagnose three different diseases. Our proposed architecture that is combining three processors to one processor can reduce hardware size without decrease of the accuracy.

Keywords: Diagnosis processor, Hypernetworks, Leukemia, Mask, Prostate cancer, SPECT Heart data

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Authors: Adama Sow, Abdoulaye Guiss´e, Oumar Niang

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To assist medical diagnosis, we propose a federation of several existing and open medical ontologies and terminologies. The goal is to merge the strengths of all these resources to provide clinicians the access to a variety of shared knowledges that can facilitate identification and association of human diseases and all of their available characteristic signs such as symptoms and clinical signs. This work results to an integration model loaded from target known ontologies of the bioportal platform such as DOID, MESH, and SNOMED for diseases selection, SYMP, and CSSO for all existing signs.

Keywords: Medical decision, medical ontologies, ontologies integration, linked data, knowledge ingeneering, e-health system.

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Authors: M. Grabowski, K. Macnar, J. Skrzyński

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Huge losses in apple production are caused by pathogens that cannot be seen shortly after harvest. After-harvest thermotherapy treatments can considerably improve control of storage diseases on apples and become an alternative to chemical pesticides. In the years 2010-2012 carried out research in this area. Apples of 'Topaz' cultivar were harvested at optimal maturity time for long storage and subject to water bath treatment at 45, 50, 52, 55°C for 60, 120, 180 and 240 seconds. The control was untreated fruits. After 12 and 24 weeks and during so called simulated trade turnover the fruits were checked for their condition and the originators of diseases were determined by using the standard phytopathological methods. The most common originator of 'Topaz' apple infection during storage were the fungi of genus Gloeosporium. In this paper it was proven that for effective protection of 'Topaz' apples against diseases, thermotherapy by using water treatments at temperature range of 50-52°C is quite sufficient.

Keywords: apple storage diseases, prolonged fruit storage, 'Topaz' apples, thermotherapeutic treatments.

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Authors: Kang-Hung Yang, Jin-Yuan Hsu

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In recent years, several severe large-scale influenza outbreaks happened in many countries, such as SARS in 2005 or H1N1 in 2009. Those influenza Epidemics have greatly impacts not only on people-s life and health, but medical systems in different countries. Although severe diseases are more experienced, they are not fully controlled. Governments have different policies to control the spreads of diseases. However, those policies have both positive and negative social or economical influence on people and society. Therefore, it is necessary and essential to develop an appropriate model for evaluations of policies. Consequently, a proper measure can be implemented to confront the diseases. The main goal of this study is to develop a SIR-based model for the further evaluations of the candidate policies during the influenza outbreaks.

Keywords: SIR, influenza, systems dynamic model, H1N1

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Authors: Faith-Michael E. Uzoka, Boluwaji A. Akinnuwesi, Taiwo Amoo, Flora Aladi, Stephen Fashoto, Moses Olaniyan, Joseph Osuji

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The overarching aim of this study is to develop a soft-computing system for the differential diagnosis of tropical diseases. These conditions are of concern to health bodies, physicians, and the community at large because of their mortality rates, and difficulties in early diagnosis due to the fact that they present with symptoms that overlap, and thus become ‘confusable’. We report on the first phase of our study, which focuses on the development of a fuzzy cognitive map model for early differential diagnosis of tropical diseases. We used malaria as a case disease to show the effectiveness of the FCM technology as an aid to the medical practitioner in the diagnosis of tropical diseases. Our model takes cognizance of manifested symptoms and other non-clinical factors that could contribute to symptoms manifestations. Our model showed 85% accuracy in diagnosis, as against the physicians’ initial hypothesis, which stood at 55% accuracy. It is expected that the next stage of our study will provide a multi-disease, multi-symptom model that also improves efficiency by utilizing a decision support filter that works on an algorithm, which mimics the physician’s diagnosis process.

Keywords: Medical diagnosis, tropical diseases, fuzzy cognitive map, decision support filters, malaria differential diagnosis.

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: Data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data.

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: A. Faro, D. Giordano, M. Pennisi, G. Scarciofalo, C. Spampinato, F. Tramontana

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The paper proposes a methodology to process the signals coming from the Transcranial Magnetic Stimulation (TMS) in order to identify the pathology and evaluate the therapy to treat the patients affected by demency diseases. In particular, a fuzzy model is developed to identify the demency of the patients affected by Subcortical Ischemic Vascular Dementia and to measure the positive effect, if any, of a repetitive TMS on their motor performances. A tool is also presented to support the mentioned analysis.

Keywords: TMS, SIVD, Electromiography , Fuzzy Logic.

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Authors: A.C. Duarte, C.I.L. Justino, K. Duarte, A.C. Freitas, R. Pereira, P. Chaves, P. Bettencourt, S. Cardoso, T.A.P. Rocha-Santos

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This paper aims at overviewing the topics of a research project (CARDIOSENSOR) on the field of health sciences (biomaterials and biomedical engineering). The project has focused on the development of a nanosensor for the assessment of the risk of cardiovascular diseases by the monitoring of C-reactive protein (CRP), which has been currently considered as the best validated inflammatory biomarker associated to cardiovascular diseases. The project involves tasks such as: 1) the development of sensor devices based on field effect transistors (FET): assembly, optimization and validation; 2) application of sensors to the detection of CRP in standard solutions and comparison with enzyme-linked immunosorbent assay (ELISA); and 3) application of sensors to real samples such as blood and saliva and evaluation of their ability to predict the risk of cardiovascular disease.

Keywords: Carbon nanotubes field effect transistors, cardiovascular diseases, C-reactive protein, sensor.

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Authors: E. F. P. Leme, L. J. R. Lopez, D. G. Goroso

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In this paper as showed a non-invasive 3D eye tracker for optometry clinical applications. Measurements of biomechanical variables in clinical practice have many font of errors associated with traditional procedments such cover test (CT), near point of accommodation (NPC), eye ductions (ED), eye vergences (EG) and, eye versions (ES). Ocular motility should always be tested but all evaluations have a subjective interpretations by practitioners, the results is based in clinical experiences, repeatability and accuracy don-t exist. Optometric-lab is a tool with 3 (tree) analogical video cameras triggered and synchronized in one acquisition board AD. The variables globe rotation angle and velocity can be quantified. Data record frequency was performed with 27Hz, camera calibration was performed in a know volume and image radial distortion adjustments.

Keywords: Eye Tracking, strabismus, eye movements, optometry.

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Authors: Ling-Lih Shen, Feng-Chuan Pan

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Chronic diseases prevailed along with economic growth as well as life style changed in recent years in Taiwan. According to the governmental statistics, hypertension related disease is the tenth of death causes with 1,816 died directly from hypertension in 2010. There were more death causes amongst the top ten had been proofed that having strong association with the hypertension, such as heart diseases, cardiovascular diseases, and diabetes. Hypertension or High blood pressure is one of the major indicators for chronic diseases, and was generally perceived as the major causes of mortality. The literature generally suggested that regular physical exercise was helpful to prevent the occurrence or to ease the progress of a hypertension. This paper reported the process and outcomes in detailed of an improvement project of physical exercise intervention specific for hypertension patients. Physical information were measured before and after the project to obtain information such as weight, waistline, cholesterol (HD & LD), blood examination, as well as self-perceived health status. The intervention project involved a six-week exercise program, of which contained three times a week, 30 minutes of tutored physical exercise intervention. The project had achieved several gains in changing the subjects- behavior in terms of many important biophysical indexes. Around 20% of the participants had significantly improved their cholesterols, BMI, and changed unhealthy behaviors. Results from the project were encouraging, and would be good reference for other samples.

Keywords: Intervention, biological information, hypertension patients, behavioral changes, chronic disease

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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: A. Faro, D. Giordano, M. Pennisi, G. Scarciofalo, C. Spampinato, F. Tramontana

Abstract:

The paper proposes a methodology to process the signals coming from the Transcranial Magnetic Stimulation (TMS) in order to identify the pathology and evaluate the therapy to treat the patients affected by demency diseases. In particular, a fuzzy model is developed to identify the demency of the patients affected by Subcortical Ischemic Vascular Dementia (SIVD) and to measure the effect of a repetitive TMS on their motor performances. A tool is also presented to support the mentioned analysis.

Keywords: TMS, EMG, fuzzy logic, transcranial magnetic stimulation.

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Authors: Daniel C. S. Lim, W. Y. Tan

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The world is facing a growing food crisis. The concerns of food nutritional value, food safety and food security are becoming increasingly real. There is also a direct relationship to the risk of diseases, particularly chronic diseases, to the food we consume. So, there are increasing concerns about the modern day food ecosystem creating foods that can provide the nutritional components for organ function sustenance, as well as, taking a serious view on diet-related diseases. This paper addresses some of the above concerns and gives an overview of the current global situation relating to food nutrition and safety. The paper reviews nutritional aspects of food today compared to those of the last century, compares whole foods found in supermarkets versus those organically grown, as well as population behaviour towards food choices. It provides scientific insights into the effects of some of the global trends such as climate change and other changes environmental changes, and presents what individuals and corporations are doing to use the latest nutritional technologies as strategic assets. Finally, it briefly highlights some of the innovative solutions that are being applied to address several of the above concerns.

Keywords: Food crisis, food safety, nutritional aspects of food today compared to those of the last century, global trends.

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Authors: Zahra Emami, Mohammad Ebrahim Khamseh, Nahid Hashemi Madani, Iman Kermani

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The aim of the study was to map scientific research on adrenal gland diseases in the Middle East countries through the Web of Science database using scientometric analysis. Data were analyzed with Excel software; and HistCite was used for mapping of the scientific texts. In this study, from a total of 268 retrieved records, 1125 authors from 328 institutions published their texts in 138 journals. Among 17 Middle East countries, Turkey ranked first with 164 documents (61.19%), Israel ranked second with 47 documents (15.53%) and Iran came in the third place with 26 documents. Most of the publications (185 documents, 69.2%) were articles. Among the universities of the Middle East, Istanbul University had the highest science production rate (9.7%). The Journal of Clinical Endocrinology & Metabolism had the highest TGCS (243 citations). In the scientific mapping, 7 clusters were formed based on TLCS (Total Local Citation Score) & TGCS (Total Global Citation Score). considering the study results, establishment of scientific connections and collaboration with other countries and use of publications on adrenal gland diseases from high ranking universities can help in the development of this field and promote the medical practice in this regard. Moreover, investigation of the formed clusters in relation to Congenital Hyperplasia and puberty related disorders can be research priorities for investigators.

Keywords: Mapping, scientific research, adrenal gland diseases, scientometric.

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Authors: C. S. Marques, M. J. Reis Lima, J. Oliveira, E. Teixeira-Lemos

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The growing concerns for physical wellbeing and health have been reflected in the way we choose food in our table. Nowadays, we are all more informed consumers and choose healthier foods. On the other hand, stroke, cancer and atherosclerosis may be somehow minimized by the intake of some bioactive compounds present in food, the so-called nutraceuticals and functional foods. The aim of this work was to make a revision of the published studies about the effects of some bioactive compounds, namely lycopene in human health, in the prevention of diseases, thus playing the role of a functional food. Free radical in human body can induce cell damage and consequently can be responsible for the development of some cancers and chronic diseases. Lycopene is one of the most powerful antioxidants known, being the predominant carotenoid in tomato. The respective chemistry, bioavailability, and its functional role in the prevention of several diseases will be object of this work. On the other hand, the inclusion of lycopene in some foods can also be made by biotechnology and represents a way to recover the wastes in the tomato industry with nutritional positive effects in health.

Keywords: Tomato, lycopene, bioavailability, functional foods, carotenoids, cancer and antioxidants.

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Authors: Einalou Z., Najafi Z., Maghooli K. Zandi Y, Sheibeigi A

Abstract:

In this study, an investigation over digestive diseases has been done in which the sound acts as a detector medium. Pursue to the preprocessing the extracted signal in cepstrum domain is registered. After classification of digestive diseases, the system selects random samples based on their features and generates the interest nonstationary, long-term signals via inverse transform in cepstral domain which is presented in digital and sonic form as the output. This structure is updatable or on the other word, by receiving a new signal the corresponding disease classification is updated in the feature domain.

Keywords: Cepstrum, databank, digestive disease, acousticsignal.

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