基於穿戴式裝置之即時鬱血性心臟衰竭預警系統

Abstract

心臟衰竭是由於心臟輸血能力和充血能力降低所導致的主要公共衛生問題。在所有解決心臟衰竭問題的技術中，通過早期識別來預防心血管疾病是一種更成功的策略，用於降低疾病的盛行率。近年來為了應對心臟衰竭，穿戴式健康監測設備的使用有了顯著的增加。遠程監測有風險的病人是提供治療和保護他們的健康的有效方式。我們希望通過利用穿戴式設備提供的大量數據，包含 PPG 以及三軸加速度，使用數學方法來幫助心臟衰竭病患和醫生。在這項研究中，我們提供了一個集成的智能穿戴設備框架，可以提供可靠的分類結果，以通知有危險的病人。

Heart failure (HF) is a major public health problem caused by the heart's diminished capacity to pump and fill with blood. Among all techniques for addressing HF issues, prevention of cardiovascular disease by early identification is a more successful strategy for decreasing illness prevalence. To cope with HF, there has been a significant increase in the usage of wearable gadgets that measure health in recent years. Remote monitoring of at-risk patients is an efficient way to provide treatment and protect their health. We want to use mathematical approaches to help HF patients and clinicians by utilizing the massive amounts of data supplied by wearable devices. In this research, we offer an integrated framework for smart-wearing devices that can deliver reliable classification results to inform patients in danger.