scholarly journals Classification of Hypertensive and Normotensive Subjects Using Bilateral Differential Biopotential Signals

2021 ◽  
Author(s):  
Arindam Sarkar ◽  
Bhaswati Goswami ◽  
Ratna Ghosh
Keyword(s):  
Blood Pressure ◽  
Random Forest ◽  
High Blood Pressure ◽  
Pivotal Role ◽  
Modern World ◽  
Hypertensive Subject ◽  
Normotensive Subjects ◽  
Electrocardiogram Ecg ◽  
Day By Day

Abstract Hypertension or high blood pressure is a severe health issue in the modern world, especially in this pandemic scenario, that can cause many heart related diseases or even death, and it is increasing day by day. For this reason, a reliable, automatic and easy to use system for hypertensive subject detection is an important focus for the researchers. Biopotential signals can play a pivotal role in this regard. Though, few strategies were proposed based on electrocardiogram (ECG) or electrodermal (EDA) signals, but those require special circuitry, as well as trained persons. In this article, a method is proposed to classify hypertensive and normotensive subjects using differential biopotential signals. Neither special circuitry, nor much expertise is required for handling this system. It was assumed that progression of rest is dependent upon blood pressure. To serve the purpose, signals were acquired from both hypertensive and normotensive subjects bilaterally for 10 continuous minutes. Result of the random forest (RF) classification establishes that from the analysis of the progression of the bilaterally acquired differential biopotential signals, hypertensive subjects can be distinguished from normotensive subjects.

scholarly journals Gambaran Tekanan Darah pada Pasien Sindrom Koroner Akut di RS Khusus Jantung Sumatera Barat Tahun 2011-2012

2014 ◽  
Vol 3 (2) ◽  
Author(s):  
Meidiza Ariandiny ◽  
Afriwardi Afriwardi ◽  
Masrul Syafri
Keyword(s):  
Blood Pressure ◽  
Acute Coronary Syndrome ◽  
High Blood Pressure ◽  
Acute Coronary Syndromes ◽  
Univariate Analysis ◽  
Gender Classification ◽  
Coronary Syndrome ◽  
Coronary Syndromes ◽  
Heart Hospital

AbstrakPenyakit jantung koroner merupakan penyakit degeneratif dengan permasalahan yang serius karena prevalensinya yang terus meningkat. Keadaan yang mengkhawatirkan dari penyakit jantung koroner adalah pada fase akut atau disebut dengan sindrom koroner akut. Salah satu faktor yang menyebabkan terjadinya sindrom koroner akut adalah tekanan darah yang tinggi yang mengakibatkan pecahnya plak aterosklerotik. Penelitian bertujuan untuk mengetahui gambaran tekanan darah pada pasien sindrom koroner akut di RS Khusus Jantung, Sumatera Barat dan mengetahui jenis hipertensi yang terjadi. Penelitian dilakukan dengan mengambil data sekunder yaitu data tekanan darah awal masuk rumah sakit pada pasien sindrom koroner akut di RS Khusus Jantung, Sumatera Barat pada bulan Maret-April 2013. Penelitian ini merupakan studi deskriptif observasional dengan total sampling. Analisis data yang dilakukan adalah analisis univariat. Hasil penelitian dari 145 data ditemukan bahwa hipertensi (tekanan darah tinggi) sebanyak 88 pasien (61%), prehipertensi sebanyak 33 pasien (23%), dan normotensi sebanyak 24 pasien (16%), dengan jenis hipertensi yaitu hipertensi kombinasi sebanyak 53 pasien (60%), hipertensi sistolik sebanyak 20 pasien (23%) dan hipertensi diastolik sebanyak 15 pasien (17%). Kelompok usia yang terbanyak yaitu usia 46-55 tahun (30%) diikuti kelompok usia 66-75 tahun (25%), 56-65 tahun (24%), >76 tahun (10%), 36-45 tahun (0,8%), dan < 35 tahun (0,2%) dengan jenis kelamin laki-laki sebesar 74% dan perempuan sebesar 26%. Kesimpulan dari hasil penelitian adalah gambaran tekanan darah pada pasien sindrom koroner akut yang terbanyak yaitu hipertensi dengan jenis hipertensi kombinasi. Kelompok usia terbanyak yaitu usia 46-55 tahun dengan jenis kelamin laki-laki.Kata kunci: tekanan darah, hipertensi, sindrom koroner akutAbstractCoronary heart disease is a degenerative disease. It becomes serious because the prevalence continues increase. The worst condition is the acute phase which is called acute coronary syndrome. The high blood pressure is one of the risk factors of acute coronary syndrome because it lead atherosclerotic plaques ruptured. This research aims is to describe the blood pressure and the type of hypertension in patients with acute coronary syndromes in The Heart Hospital, West Sumatera. This research took the secondary data of admission blood pressure in patients hospitalized with acute coronary syndrome in The Heart Hospital, West Sumatera, March - April 2013. This research is an observational descriptive study with a total sampling. Data analysis was performed univariate analysis. The results of 145 data were 88 patients (61%) had hypertension (high blood pressure), 33 patients (23%) were prehypertension, and 24 were normotensive (16%). The type of hypertension were 53 patients with combination hypertension (60%), 20 patients with systolic hypertension (23%) and 15 patients with diastolic hypertension (17%). Based on the age classification of hypertension, found that 46-55 years were 30%, 66-75 years were 25%, 56-65 years were 24%, > 76 years were 10%, 36-45 years were 0.8%, and < 35 years were 0.2%. based on gender classification of hypertension found that male gender were 74% and women were 26%. The conclusion of this research find that the largest blood pressure in patients with acute coronary syndromes is hypertension, the largest type of hypertension is combination hypertension, the largest age classification is 46-55 years, and the largest gender classification is male.Keywords:blood pressure, hypertension, acute coronary syndrome

scholarly journals Multimorbidity patterns among COVID-19 deaths: proposal for the construction of etiological models

2020 ◽  
Vol 44 ◽  
pp. 1
Author(s):  
Julián A. Fernández-Niño ◽  
John A. Guerra-Gómez ◽  
Alvaro J. Idrovo
Keyword(s):  
Blood Pressure ◽  
Cardiovascular Disease ◽  
Respiratory Disease ◽  
High Blood Pressure ◽  
Health Conditions ◽  
Older Individuals ◽  
Age Related ◽  
Probability Of Death ◽  
Polynomial Regressions

Objectives. To describe patterns of multimorbidity among fatal cases of COVID-19, and to propose a classification of patients based on age and multimorbidity patterns to begin the construction of etiological models. Methods. Data of Colombian confirmed deaths of COVID-19 until June 11, 2020, were included in this analysis (n=1488 deaths). Relationships between COVID-19, combinations of health conditions and age were explored using locally weighted polynomial regressions. Results. The most frequent health conditions were high blood pressure, respiratory disease, diabetes, cardiovascular disease, and kidney disease. Dyads more frequents were high blood pressure with diabetes, cardiovascular disease or respiratory disease. Some multimorbidity patterns increase probability of death among older individuals, whereas other patterns are not age-related, or decrease the probability of death among older people. Not all multimorbidity increases with age, as is commonly thought. Obesity, alone or with other diseases, was associated with a higher risk of severity among young people, while the risk of the high blood pressure/diabetes dyad tends to have an inverted U distribution in relation with age. Conclusions. Classification of individuals according to multimorbidity in the medical management of COVID-19 patients is important to determine the possible etiological models and to define patient triage for hospitalization. Moreover, identification of non-infected individuals with high-risk ages and multimorbidity patterns serves to define possible interventions of selective confinement or special management.

scholarly journals Automatic Classification of Hypertension Types Based on Personal Features by Machine Learning Algorithms

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Majid Nour ◽  
Kemal Polat
Keyword(s):  
Machine Learning ◽  
Blood Pressure ◽  
Random Forest ◽  
Decision Tree ◽  
Systolic Blood Pressure ◽  
Diastolic Blood Pressure ◽  
Decision Tree Classifier ◽  
Tree Classifier ◽  
C4.5 Decision Tree

Hypertension (high blood pressure) is an important disease seen among the public, and early detection of hypertension is significant for early treatment. Hypertension is depicted as systolic blood pressure higher than 140 mmHg or diastolic blood pressure higher than 90 mmHg. In this paper, in order to detect the hypertension types based on the personal information and features, four machine learning (ML) methods including C4.5 decision tree classifier (DTC), random forest, linear discriminant analysis (LDA), and linear support vector machine (LSVM) have been used and then compared with each other. In the literature, we have first carried out the classification of hypertension types using classification algorithms based on personal data. To further explain the variability of the classifier type, four different classifier algorithms were selected for solving this problem. In the hypertension dataset, there are eight features including sex, age, height (cm), weight (kg), systolic blood pressure (mmHg), diastolic blood pressure (mmHg), heart rate (bpm), and BMI (kg/m2) to explain the hypertension status and then there are four classes comprising the normal (healthy), prehypertension, stage-1 hypertension, and stage-2 hypertension. In the classification of the hypertension dataset, the obtained classification accuracies are 99.5%, 99.5%, 96.3%, and 92.7% using the C4.5 decision tree classifier, random forest, LDA, and LSVM. The obtained results have shown that ML methods could be confidently used in the automatic determination of the hypertension types.

scholarly journals Effect of Antihypertensive Therapy on SCORE-Estimated Total Cardiovascular Risk: Results from an Open-Label, Multinational Investigation—The POWER Survey

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Guy De Backer ◽  
Robert J. Petrella ◽  
Assen R. Goudev ◽  
Ghazi Ahmad Radaideh ◽  
Andrzej Rynkiewicz ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Primary Care ◽  
High Blood Pressure ◽  
Cvd Risk ◽  
Open Label ◽  
Substantial Risk ◽  
Blood Pressures ◽  
Score Model ◽  
The Impact

Background.High blood pressure is a substantial risk factor for cardiovascular disease.Design & Methods.The Physicians' Observational Work on patient Education according to their vascular Risk (POWER) survey was an open-label investigation of eprosartan-based therapy (EBT) for control of high blood pressure in primary care centers in 16 countries. A prespecified element of this research was appraisal of the impact of EBT on estimated 10-year risk of a fatal cardiovascular event as determined by the Systematic Coronary Risk Evaluation (SCORE) model.Results.SCORE estimates of CVD risk were obtained at baseline from 12,718 patients in 15 countries (6504 men) and from 9577 patients at 6 months. During EBT mean (±SD) systolic/diastolic blood pressures declined from 160.2 ± 13.7/94.1 ± 9.1 mmHg to 134.5 ± 11.2/81.4 ± 7.4 mmHg. This was accompanied by a 38% reduction in mean SCORE-estimated CVD risk and an improvement in SCORE risk classification of one category or more in 3506 patients (36.6%).Conclusion.Experience in POWER affirms that (a) effective pharmacological control of blood pressure is feasible in the primary care setting and is accompanied by a reduction in total CVD risk and (b) the SCORE instrument is effective in this setting for the monitoring of total CVD risk.

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