Enhanced hypertension classifier based on photoplethysmogram signal using statistical analysis and extreme learning machine method

Abstract

: Hypertension prevalence is known to increase with urbanization and ageing population. The combination of urbanization and ageing can have a compounding effect on the prevalence of hypertension. As populations age in urban areas, there is a higher risk of developing hypertension due to both lifestyle factors and physiological changes. This has significant public health implications, as hypertension is a major risk factor for cardiovascular disease, stroke, and kidney disease. The aim of this study is establishing an operator independent screening technique with reliable accuracy in classifying hypertensive subjects using finger photoplethysmogram signal. In achieving the targeted