ECG Arrhythmia Classification Using Spearman Rank Correlation and Support Vector Machine

2012 ◽  
pp. 591-598 ◽  
Author(s):  
Shreya Khare ◽  
Akshay Bhandari ◽  
Saurabh Singh ◽  
Anuja Arora
Keyword(s):  
Support Vector Machine ◽  
Rank Correlation ◽  
Support Vector ◽  
Spearman Rank Correlation ◽  
Spearman Rank ◽  
Ecg Arrhythmia Classification ◽  
Ecg Arrhythmia

scholarly journals Performance Analysis of ECG Arrhythmia Classification based on Different SVM Methods

2020 ◽  
Vol 9 (12) ◽  
pp. 45-49
Keyword(s):  
Support Vector Machine ◽  
Decision Function ◽  
Support Vector ◽  
Svm Classifier ◽  
Data Sets ◽  
Artery Disease ◽  
Ecg Arrhythmia Classification ◽  
The One ◽  
Ecg Arrhythmia ◽  
Ecg Data

Heart arrhythmias are the different types of heartbeats which are irregular in nature. In Tachycardia the heartbeat works too fast and in case of Bradycardia it works too slow. In the study of different cardiac conditions automatic detection of heart arrhythmia is done by the classification and feature extraction of Electrocardiogram(ECG) data. Various Support Vector Machine based methods are used to analyze and classify ECG signals for arrhythmia detection. There are several Support Vector Machine (SVM) methods used to classify the ECG data such as one against all, one against one and fuzzy decision function. This classification detects the existence of the arrhythmia and it helps the physicians to treat the heart patient with more accurate way. To train SVM, the MIT BIH Arrhythmia database is used which works with the heart disorder like sinus bradycardy, old inferior myocardial infarction, coronary artery disease, right bundle branch block. All three methods are implemented in proper way, and their rate of accuracy with SVM classifier is optimal when it is processed with the one-against-all method. The data sets of ECG arrhythmia are usually complex in nature, so for the SVM based classification one-against-all method has great impact and will fetch better result.

scholarly journals ELECTROCARDIOGRAM ARRHYTHMIA CLASSIFICATION SYSTEM USING SUPPORT VECTOR MACHINE BASED FUZZY LOGIC

2016 ◽  
Vol 9 (1) ◽  
pp. 35 ◽  
Author(s):  
Sugiyanto Sugiyanto ◽  
Tutuk Indriyani ◽  
Muhammad Heru Firmansyah
Keyword(s):  
Support Vector Machine ◽  
Fuzzy Logic ◽  
Support Vector ◽  
Ecg Signal ◽  
Average Value ◽  
Sensitivity Level ◽  
Accuracy Level ◽  
Baseline Wander ◽  
Ecg Arrhythmia Classification ◽  
Ecg Arrhythmia

Arrhythmia is a cardiovascular disease that can be diagnosed by doctors using an electrocardiogram (ECG). The information contained on the ECG is used by doctors to analyze the electrical activity of the heart and determine the type of arrhythmia suffered by the patient. In this study, ECG arrhythmia classification process was performed using Support Vector Machine based fuzzy logic. In the proposed method, fuzzy membership functions are used to cope with data that are not classifiable in the method of Support Vector Machine (SVM) one-against-one. An early stage of the data processing is the baseline wander removal process on the original ECG signal using Transformation Wavelet Discrete (TWD). Afterwards then the ECG signal is cleaned from the baseline wander segmented into units beat. The next stage is to look for six features of the beat. Every single beat is classified using SVM method based fuzzy logic. Results from this study show that ECG arrhythmia classification using proposed method (SVM based fuzzy logic) gives better results than original SVM method. ECG arrhythmia classification using SVM method based fuzzy logic forms an average value of accuracy level, sensitivity level, and specificity level of 93.5%, 93.5%, and 98.7% respectively. ECG arrhythmia classification using only SVM method forms an average value accuracy level, sensitivity level, and specificity level of 91.83%, 91.83%, and 98.36% respectively.

HUBUNGAN BEBAN KERJA PERAWAT DENGAN KELENGKAPAN PENGISIAN DOKUMENTASI ASUHAN KEPERAWATAN

2020 ◽  
Vol 5 (2) ◽  
pp. 588
Author(s):  
Etlida Wati ◽  
Ulva Arini
Keyword(s):  
Nursing Care ◽  
Rank Correlation ◽  
Bivariate Analysis ◽  
Spearman Rank Correlation ◽  
Cross Sectional ◽  
Weight Category ◽  
Spearman Rank ◽  
Hospital Room ◽  
Analysis Technique ◽  
Nurse Workload

<p>Documentation is an activity of recording, reporting or recording an event and activities carried out in the form of providing services that are considered important and valuable. One factor that can influence documentation is the nurse's workload. The purpose of this study is to identify the relationship between nurses' workload and the application of documentation in the Hj. Anna Lasmanah Banjarnegara. This  research is quantitative with a cross sectional approach descriptive correlation design. Samples were taken with a total sampling of 65 nurses. Instruments to measure documentation using observation sheets. While the nurse workload instrument uses a questionnaire sheet. The analysis technique uses Spearman Rank correlation. Based on the research results of the workload of a nurse in the hospital room , most of them are in the weight category, as many as 46 respondents (70.8%). Application of nursing care documentation in the hospital room Hj. Anna Lasmanah Banjarnegara, most of them are respondents in the incomplete category as many as 63 respondents (96.9%). There is a significant relationship between nurse workload with the application of documentation, this is evidenced by the results of the Spearman Rank correlation bivariate analysis, which is r = 0.688 with p = 0.000 &lt;0.05. It is hoped that management will motivate nurses to complete the documentation of nursing care</p>

scholarly journals Does continuity in nursing staff matter? A pilot study on correlation of central line-associated bloodstream infections and employee turnover

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Thomas Scheier ◽  
Stefan P. Kuster ◽  
Mesida Dunic ◽  
Christian Falk ◽  
Hugo Sax ◽  
...  
Keyword(s):  
Nursing Staff ◽  
Employee Turnover ◽  
Rank Correlation ◽  
Bloodstream Infections ◽  
Central Line ◽  
Incidence Rates ◽  
Nursing Personnel ◽  
Care Hospital ◽  
Spearman Rank Correlation ◽  
Spearman Rank

Abstract Background Understaffing has been previously reported as a risk factor for central line-associated bloodstream infections (CLABSI). No previous study addressed the question whether fluctuations in staffing have an impact on CLABSI incidence. We analyzed prospectively collected CLABSI surveillance data and data on employee turnover of health care workers (HCW) to address this research question. Methods In January 2016, a semiautomatic surveillance system for CLABSI was implemented at the University Hospital Zurich, a 940 bed tertiary care hospital in Switzerland. Monthly incidence rates (CLABSI/1000 catheter days) were calculated and correlations with human resources management-derived data on employee turnover of HCWs (defined as number of leaving HCWs per month divided by the number of employed HCWs) investigated. Results Over a period of 24 months, we detected on the hospital level a positive correlation of CLABSI incidence rates and turnover of nursing personnel (Spearman rank correlation, r = 0.467, P = 0.022). In more detailed analyses on the professional training of nursing personnel, a correlation of CLABSI incidence rates and licensed practical nurses (Spearman rank correlation, r = 0.26, P = 0.038) or registered nurses (r = 0.471, P = 0.021) was found. Physician turnover did not correlate with CLABSI incidence (Spearman rank correlation, r =  −0.058, P = 0.787). Conclusions Prospectively determined CLABSI incidence correlated positively with the degree of turnover of nurses overall and nurses with advanced training, but not with the turnover of physicians. Efforts to maintain continuity in nursing staff might be helpful for sustained reduction in CLABSI rates.

scholarly journals In vivo calibration of the T2* cardiovascular magnetic resonance method at 1.5 T for estimation of cardiac iron in a minipig model of transfusional iron overload

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Peter Diedrich Jensen ◽  
Asbjørn Haaning Nielsen ◽  
Carsten Wiberg Simonsen ◽  
Ulrik Thorngren Baandrup ◽  
Svend Eggert Jensen ◽  
...  
Keyword(s):  
Rank Correlation ◽  
Calibration Data ◽  
Iron Loading ◽  
Spearman Rank Correlation ◽  
Calibration Equation ◽  
Spearman Rank ◽  
Cardiac Iron ◽  
In Vivo Calibration ◽  
Spearman Rank Correlation Coefficient

Abstract Background Non-invasive estimation of the cardiac iron concentration (CIC) by T2* cardiovascular magnetic resonance (CMR) has been validated repeatedly and is in widespread clinical use. However, calibration data are limited, and mostly from post-mortem studies. In the present study, we performed an in vivo calibration in a dextran-iron loaded minipig model. Methods R2* (= 1/T2*) was assessed in vivo by 1.5 T CMR in the cardiac septum. Chemical CIC was assessed by inductively coupled plasma-optical emission spectroscopy in endomyocardial catheter biopsies (EMBs) from cardiac septum taken during follow up of 11 minipigs on dextran-iron loading, and also in full-wall biopsies from cardiac septum, taken post-mortem in another 16  minipigs, after completed iron loading. Results A strong correlation could be demonstrated between chemical CIC in 55 EMBs and parallel cardiac T2* (Spearman rank correlation coefficient 0.72, P < 0.001). Regression analysis led to [CIC] = (R2* − 17.16)/41.12 for the calibration equation with CIC in mg/g dry weight and R2* in Hz. An even stronger correlation was found, when chemical CIC was measured by full-wall biopsies from cardiac septum, taken immediately after euthanasia, in connection with the last CMR session after finished iron loading (Spearman rank correlation coefficient 0.95 (P < 0.001). Regression analysis led to the calibration equation [CIC] = (R2* − 17.2)/31.8. Conclusions Calibration of cardiac T2* by EMBs is possible in the minipig model but is less accurate than by full-wall biopsies. Likely explanations are sampling error, variable content of non-iron containing tissue and smaller biopsies, when using catheter biopsies. The results further validate the CMR T2* technique for estimation of cardiac iron in conditions with iron overload and add to the limited calibration data published earlier.

scholarly journals Interactional Justice and Employees’ Commitment to Supervisor in Nigerian Health Sector

2015 ◽  
Vol 2 (5) ◽  
pp. 7-17 ◽  
Author(s):  
Ajogwu Akoh ◽  
Edwinah Amah
Keyword(s):  
Health Sector ◽  
Rank Correlation ◽  
Interactional Justice ◽  
Survey Questionnaire ◽  
Spearman Rank Correlation ◽  
Interpersonal Justice ◽  
Informational Justice ◽  
Spearman Rank ◽  
The Relationship ◽  
Spearman Rank Correlation Coefficient

This research was designed to study the relationship between interactional justice and employees’ commitment to supervisor in Nigerian health sector. A self-administered survey questionnaire was sent out to a sample size of 103 employees, resulting in 99 responses out of which 13 copies of the questionnaire were not statistically usable. The Spearman rank correlation coefficient was used for data analysis, and our findings reveal that employees who have received fair informational and interpersonal treatments commit themselves to their supervisors. We discovered that the degree of influence exerted by interpersonal justice on employees’ commitment to supervisor was stronger than that of informational justice. We concluded that employees attach themselves to supervisors that are fair in communication and relationship. The fairness of interaction and communication boost employees’ confidence, impacting positively on employees’ commitment to supervisor and making employees see themselves as part owners in the organization. We, therefore, recommended that organizational managers or supervisors should communicate and relate properly with employees, in order to satisfy their customers and other stakeholders.

scholarly journals Analisis Faktor-Faktor Yangberhubungandengan Motivasi Petani Dalam Berusahatani Lada Di Kabupaten Aceh Besar

2016 ◽  
Vol 1 (1) ◽  
pp. 394-409
Author(s):  
Zainuddin Zainuddin ◽  
Safrida Safrida ◽  
Elvira Iskandar
Keyword(s):  
Rank Correlation ◽  
Measurement Scale ◽  
Primary Data ◽  
Spearman Rank Correlation ◽  
West Kalimantan ◽  
Spearman Rank ◽  
Aceh Province ◽  
Level Of Motivation ◽  
Service Agencies ◽  
Pepper Plants

ABSTRACTOne of the commodities that became the mainstay of Indonesia's exports is commodities pepper. In Indonesia, many pepper plants grown in the provinces of Lampung, Bangka, West Kalimantan and Aceh. Pepper plants in several regencies / cities in Aceh province. However, the development of commodity pepper planting area tends to decrease in almost every district. Aceh Besar district as a granary, pepper production in Aceh province also decreased acreage planting area. This condition is very contradictory because demand and prices of pepper are high but has not been used optimally. This is a reflection of the low motivation of farmers in pepper farming. The purpose of this study was to determine the level of motivation pepper farmers and determine the factors related to the motivation of farmers. The data analysis method used is Likert measurement scale systems and Spearman rank correlation. The data used are primary data time series period 2008-2013. Based on test results using a Likert scale of measurement that the level of motivation of farmers in pepper farming in Aceh Besar district in the high category. Based on the factors that have been tested using Spearman rank correlation, it is known that factors related to the level of motivation of farmers in pepper farming is the motivation of farmers with the availability of inputs, farmers motivated by cosmopolitan nature of farmers, and the motivation of farmers by supporting institutions. While revenue and service agencies there are not to relation with the motivation of pepper farmers. Keywords: Pepper Farm, Farmer Motivation Levels, External Factors, Spearman Rank Correlation

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