scholarly journals Deep Learning-Based Arrhythmia Detection in Electrocardiograph

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yang Meng ◽  
Guoxin Liang ◽  
Mei Yue
Keyword(s):  
Heart Beat ◽  
Small Sample ◽  
Original Model ◽  
Massachusetts Institute Of Technology ◽  
Beth Israel Hospital ◽  
Arrhythmia Detection ◽  
Atrial Premature Beat ◽  
The Difference ◽  
Institute Of Technology ◽  
Sample Set

This study aimed to explore the application of electrocardiograph (ECG) in the diagnosis of arrhythmia based on the deep convolutional neural network (DCNN). ECG was classified and recognized with the DCNN. The specificity (Spe), sensitivity (Sen), accuracy (Acc), and area under curve (AUC) of the DCNN were evaluated in the Chinese Cardiovascular Disease Database (CCDD) and Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database, respectively. The results showed that in the CCDD, the original model tested by the small sample set had an accuracy (Acc) of 82.78% and AUC of 0.882, while the Acc and AUC of the translated model were 85.69% and 0.893, respectively, so the difference was notable ( P  < 0.05); the Acc of the original model and the translated model was 80.12% and 82.63%, respectively, in the large sample set, so the difference was obvious ( P  < 0.05). In the MIT-BIH database, the Acc of normal (N) heart beat (HB) (99.38%) was higher than that of the atrial premature beat (APB) (87.45%) ( P  < 0.05). In a word, applying the DCNN could improve the Acc of ECG for classification and recognition, so it could be well applied to ECG signal classification.

Applying the Anderson-Darling Test to Suicide Clusters

Crisis ◽  
2013 ◽  
Vol 34 (6) ◽  
pp. 434-437 ◽  
Author(s):  
Donald W. MacKenzie
Keyword(s):  
Poisson Process ◽  
Goodness Of Fit ◽  
Small Samples ◽  
Massachusetts Institute Of Technology ◽  
Homogeneous Poisson Process ◽  
Cornell University ◽  
The Difference ◽  
Suicide Clusters ◽  
Institute Of Technology ◽  
Anderson Darling

Background: Suicide clusters at Cornell University and the Massachusetts Institute of Technology (MIT) prompted popular and expert speculation of suicide contagion. However, some clustering is to be expected in any random process. Aim: This work tested whether suicide clusters at these two universities differed significantly from those expected under a homogeneous Poisson process, in which suicides occur randomly and independently of one another. Method: Suicide dates were collected for MIT and Cornell for 1990–2012. The Anderson-Darling statistic was used to test the goodness-of-fit of the intervals between suicides to distribution expected under the Poisson process. Results: Suicides at MIT were consistent with the homogeneous Poisson process, while those at Cornell showed clustering inconsistent with such a process (p = .05). Conclusions: The Anderson-Darling test provides a statistically powerful means to identify suicide clustering in small samples. Practitioners can use this method to test for clustering in relevant communities. The difference in clustering behavior between the two institutions suggests that more institutions should be studied to determine the prevalence of suicide clustering in universities and its causes.

scholarly journals Feature Extraction of ECG Signals using NI LabVIEW Biomedical Workbench and Classification with Artificial Neural Network

2019 ◽  
pp. 34-38
Author(s):  
Ebru Sayilgan ◽  
Savas Sahin
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Heart Beat ◽  
Massachusetts Institute Of Technology ◽  
Data Set ◽  
Ecg Signals ◽  
Multiple Classification ◽  
Sensitivity And Selectivity ◽  
Artificial Neural ◽  
Institute Of Technology

In this study, a data set containing normal and different heart beat types recorded by the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) was used for the detection of cardiac dysfunctions. In this data set, features were extracted using the LabVIEW Biomedical Workbench from the normal heartbeat and six different arrhythmia types. Obtained signals were evaluated by using Artificial Neural Network multiple classification method. Classification performances were compared before extracting the feature on the same data set. Classifier performances were evaluated by accuracy, sensitivity and selectivity performances criteria of classification. In the classifier performances, the "Normal" beat rate was found to be 99% accurate with the highest success compared to other arrhythmia types. As a result, both analysis methods are successful, but when the LabVIEW Biomedical Workbench is used, the classification results have achieved higher success.

An Application of the Interferometer Strain Gage in Photoelasticity

1935 ◽  
Vol 2 (3) ◽  
pp. A99-A102
Author(s):  
R. W. Vose
Keyword(s):  
Strain Gage ◽  
Poisson’S Ratio ◽  
Poisson's Ratio ◽  
Massachusetts Institute ◽  
Massachusetts Institute Of Technology ◽  
Lateral Deformation ◽  
Principal Stresses ◽  
Photoelastic Analysis ◽  
The Difference ◽  
Institute Of Technology

Abstract This paper was written at the suggestion of Mr. Mieth Maeser, in response to numerous inquiries concerning the methods of photoelastic analysis in use at the Massachusetts Institute of Technology. By the use of any of the usual photoelastic methods the difference of the principal stresses and their direction at any point in a suitable loaded specimen are determined, and through a knowledge of Poisson’s ratio their sum is obtained (and a solution made possible) by a measurement of the lateral deformation of the specimen by means of an interferometer strain gage. This instrument, together with its accessories and their use, is illustrated and described in the paper. Examples of the problems solved by the use of the instrument show its accuracy and the consistency of the results obtained by the method.

Automatic Arrhythmia Detection

2010 ◽  
pp. 204-218
Author(s):  
Carlos M. Travieso ◽  
Jesús B. Alonso ◽  
Miguel A. Ferrer ◽  
Jorge Corsino
Keyword(s):  
Support Vector ◽  
Massachusetts Institute Of Technology ◽  
Classification Methods ◽  
Success Rates ◽  
Arrhythmia Detection ◽  
Time Frequency ◽  
Vector Machines ◽  
Institute Of Technology ◽  
Electrocardiogram Ecg ◽  
Frequency Features

In the present chapter, the authors have developed a tool for the automatic arrhythmias detection, based on time-frequency features and using a Support Vector Machines (SVM) as classifier. Arrhythmia Database Massachusetts Institute of Technology (MIT) has been used in the work in order to detect eight different states, seven are pathologies and one is normal. The unions of different blocks and its optimization have found success rates of 99.82% for RR’ interval detection from electrocardiogram (PQRST waves), and 99.23% for pathologic detection. In particular, the authors have used wavelet transform in order to characterize the wave of electrocardiogram (ECG), based on Biorthogonal family, achieving the most discriminative coefficients. A discussion on arrhythmia ECG classification methods is also presented in this paper.

Editorial: Advancing the Debate on Architecture, Planning, and Built Environment Research

2015 ◽  
Vol 9 (2) ◽  
Author(s):  
Ashraf M. Salama
Keyword(s):  
Learning Styles ◽  
Cultural Values ◽  
Urban Studies ◽  
Wide Spectrum ◽  
Journal Ranking ◽  
Massachusetts Institute Of Technology ◽  
Open Access Journals ◽  
Practice Based Research ◽  
Institute Of Technology ◽  
Number Of Citations

With an acceptance rate that does not exceed 25% of the total papers and articles submitted to the journal, IJAR – International Journal of Architectural Research is moving forward to position itself among the leading journals in architecture and urban studies worldwide. As this is the case since the beginning of volume 5, issue 1, March 2011, one must note that the journal has been covered by several data and index bases since its inception including Avery Index to Architectural Periodicals, EBSCO-Current Abstracts-Art and Architecture, INTUTE, Directory of Open Access Journals, Pro-Quest, Scopus-Elsevier and many university library databases across the globe. This is coupled with IJAR being an integral part of the archives and a featured collection of ArchNet and the Aga Khan Documentation Centre at MIT: Massachusetts Institute of Technology, Cambridge, MA.In 2014, IJAR was included in Quartile 2 / Q2 list of Journals both in ‘Architecture’ and ‘Urban Studies.’ As of May 2015, IJAR is ranked 23 out of 83 journals in ‘Architecture’ and 59 out of 119 in ‘Urban Studies.’ Rankings are based on the SJR (SCImago Journal Ranking); an Elsevier- SCOPUS indicator that measures the scientific influence of the average article in a journal. SJR is a measure of scientific influence of scholarly journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from. See here for more information (http://www.scimagojr.com/index.php) and (http://www.journalmetrics.com/sjr.php). While the journal is now on top of many of the distinguished journals in Elsevier- SCOPUS database, we will keep aspiring to sustain our position and move forward to Q1 group list and eventually in the top 10 journal list in the field. However, this requires sustained efforts and conscious endeavours that give attention to quality submissions through a rigorous review process. This edition of IJAR: volume 9, issue 2, July 2015 includes debates on a wide spectrum of issues, explorations and investigations in various settings. The issue encompasses sixteen papers addressing cities, settlements, and projects in Europe, South East Asia, and the Middle East. Papers involve international collaborations evidenced by joint contributions and come from scholars in universities, academic institutions, and practices in Belgium; Egypt; Greece; Italy; Jordan; Malaysia; Palestine; Qatar; Saudi Arabia; Serbia; Spain; Turkey; and the United Kingdom. In this editorial I briefly outline the key issues presented in these papers, which include topics relevant to social housing, multigenerational dwelling, practice-based research, sustainable design and biomimetic models, learning environments and learning styles, realism and the post modern condition, development and planning, urban identity, contemporary landscapes, and cultural values and traditions.

XX Rudi Dombusch, Keys to Prosperity. Free Markets, Sound Money, and bit of Luck The MIT Press 2000 Londres

2009 ◽  
Vol 33 (130) ◽  
Author(s):  
GERARDO REYES GUZMÁN
Keyword(s):  
Massachusetts Institute ◽  
Massachusetts Institute Of Technology ◽  
Free Markets ◽  
Institute Of Technology

Rudiger Dornbusch, destacado economista del Massachusetts Institute of Technology (MIT), analiza en esta trascendental obra tópicos como inflación, deuda, tipos de cambio, política externa y mercados emergentes. El marco conceptual descansa en la corriente de la escuela de Chicago, la cual parte del principio de que el mercado es el mecanismo que garantiza la creación del progreso en contraste con el Estado, que en su afán por encontrar soluciones perfectas, fracasa regularmente en sus cometidos.

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