Abstract
Hypertension is a common and chronic disease and causes severe damage to patients' health. Blood pressure of a human being is controlled by the autonomic nervous system. Heart rate variability (HRV) is an impact of the autonomic nervous system and an indicator of the balance of the cardiac sympathetic nerve and vagus nerve. HRV is a good method to recognize the severity of hypertension due to the specificity for prediction. In this paper, we proposed a novel fine-grained HRV analysis method to enhance the precision of recognition. In order to analyze the HRV of the patient, we segment the overnight electrocardiogram (ECG) into various scales. 18 HRV multidimensional features in the time, frequency, and nonlinear domain are extracted, and then the temporal pyramid pooling method is designed to reduce feature dimensions. Multifactor analysis of variance (MANOVA) is applied to filter the related features and establish the hypertension recognizing model with relevant features to efficiently recognize the patients' severity. In this paper, 139 hypertension patients' real clinical ECG data are applied, and the overall precision is 95.1%. The experimental results validate the effectiveness and reliability of the proposed recognition method in the work.
Highlights
Hypertension is a common and chronic disease, and the hypertensive patients have no symptom when it is in the early stage
When the patient is in the sleep state, the patients’ Heart rate variability (HRV) have no disturbance from external environment, and HRV can reflect the physiological status of the body, for hypertension patients, and accurately reflect the severity of the illness
We mark tags to the patients by the hospital according to the European society of hypertension (ESH) guidelines. e ECG Holter was performed after a one-month antihypertensive therapy washout. erefore, the patients are divided into mild, normal hypertension, and primary hypertension patients, and in primary patients, level I is divided into moderate, level 2 and level 3 hypertension patients are divided into severe
Summary
Hypertension is a common and chronic disease, and the hypertensive patients have no symptom when it is in the early stage. The most prominent problems of the treatment of hypertension are low awareness, low treatment, and low control It is highly regarded as the dangerous healthy problem throughout the world because of its high prevalence and its association with increased risk of cardiovascular disease. Based on the above statements, it is a reasonable way to recognize the severity of hypertension by HRV extracted from the ECG in overnight sleep. Long-term analysis is often a 24-hour analysis, including all activities of human being all day, such as eating, working, and sleeping; short-term analysis is an analyzing of 5 minutes HRV data. We propose a fine-grained HRV analysis method to enhance the precision of the severity of hypertension recognition.
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