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A New Pattern Recognition Method for Detection and Localization of Myocardial Infarction Using T-Wave Integral and Total Integral as Extracted Features from One Cycle of ECG Signal

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Journal of Biomedical Science and Engineering 2014年第10期7卷 818-824页

作者： Naser Safdarian nader jafarnia dabanloo Gholamreza Attarodi Department of Biomedical Engineering Dezful Branch Islamic Azad University Dezful Iran Department of Biomedical Engineering Science and Research Branch Islamic Azad University Tehran Iran

In this paper we used two new features i.e. T-wave integral and total integral as extracted feature from one cycle of normal and patient ECG signals to detection and localization of myocardial infarction (MI) in left ventricle of heart. In our previous work we used some features of body surface potential map data for this aim. But we know the standard ECG is more popular, so we focused our detection and localization of MI on standard ECG. We use the T-wave integral because this feature is important impression of T-wave in MI. The second feature in this research is total integral of one ECG cycle, because we believe that the MI affects the morphology of the ECG signal which leads to total integral changes. We used some pattern recognition method such as Artificial Neural Network (ANN) to detect and localize the MI, because this method has very good accuracy for classification of normal signal and abnormal signal. We used one type of Radial Basis Function (RBF) that called Probabilistic Neural Network (PNN) because of its nonlinearity property, and used other classifier such as k-Nearest Neighbors (KNN), Multilayer Perceptron (MLP) and Naive Bayes Classification. We used PhysioNet database as our training and test data. We reached over 76% for accuracy in test data for localization and over 94% for detection of MI. Main advantages of our method are simplicity and its good accuracy. Also we can improve the accuracy of classification by adding more features in this method. A simple method based on using only two features which were extracted from standard ECG is presented and has good accuracy in MI localization.

关键词： ECG Signal Classification Signal Processing Myocardial Infarction Features Extraction Neural Network

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Providing a Therapeutic Scheduling for HIV Infected Individuals with Genetic Algorithms Using a Cellular Automata Model of HIV Infection in the Peripheral Blood Stream

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Journal of Biomedical Science and Engineering 2017年第3期10卷 77-106页

作者： Gelayol Nazari Golpayegani Amir Homayoun Jafari nader jafarnia dabanloo Department of Biomedical Engineering Science and Research Branch Islamic Azad University Tehran Iran Medical Physics and Biomedical Engineering Department School of Medicine Tehran University of Medical Science Tehran Iran Research Center for Biomedical Technologies and Robotics (RCBTR) Tehran University of Medical Sciences Tehran Iran

The aim of this study is to develop two-dimensional cellular automata model of HIV infection that depicts the dynamics involved in the interactions between acquired immune system and HIV infection in the peripheral blood stream. The appropriate biological rules of cellular automata model have been extracted from expert knowledge and the model has been simulated with determined initial conditions. Obtained results have been validated through comparing with the accepted AIDS reference curve. The new rules and states were added to the proposed model to show the effects of applying combined antiretroviral therapy. Our results showed that by applying RTI and PI drugs with maximum drug effectiveness, comparing with cases in which no treatment was applied, the steady state concentrations of healthy (infected) CD4+T cells were increased (decreased) 53% (41%). Also, the use of cART with maximum drug effectiveness led to a 69% reduction in the steady state level of viral load. At this time, obtained results have been validated through comparing with available clinical data. Our results showed good agreement with both reference curve and the clinical data. In the second phase of this study, by applying genetic algorithms, a therapeutic schedule has been provided that its use, while maintaining the quality of the treatment, leads to a 47% reduction in both drug dosage and the side effects of antiretroviral drugs.

关键词： HIV Infection Cellular Automata Model Combined Antiretroviral Therapy Genetic Algorithms

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A Systematic Review of the Use of Commercial Wearable Activity Trackers for Monitoring Recovery in Individuals Undergoing Total Hip Replacement Surgery

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Cyborg and Bionic Systems 2022年第1期2022卷 141-156页

作者： Nasibeh Babaei Negin Hannani nader jafarnia dabanloo Shayan Bahadori Department of Biomedical Engineering Science And Research BranchIslamic Azad UniversityTehranIran Faculty of Health and Social Science Bournemouth UniversityBournemouthUK

The innovation of wearable devices is advancing *** monitors can be used to improve the total hip replacement(THR)patients’recovery process and reduce *** systematic review assessed the body-worn accelerometers used instudies to enhance the rehabilitation process and monitor THR *** databases such as Cochrane Database of Systematic Reviews library,CINAHL Complete VR,Science Citation Index,and MedlineVR from January 2000 to January 2022 were *** to inclusion criteria,fourteen eligible studies that utlised commercial wearable technology to monitorphysical activity both before and after THR were *** evidence quality was assessed with RoB 2.0 and ROBINS-IThis study demonstrates that wearable device technology might be feasible to predict,monitor,and detect physical activityfollowing *** could be used as a motivational tool to increase patients'mobility and enhance the recovery ***,wearable activity monitors could provide a better insight into the individual's activity level in contrast to subjective *** ***,they have some limitations,and further evidence is needed to establish this technology asthe primary device in THR rehabilitation.

关键词： Surgery assessed Recovery

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