Wireless ECG with Machine Learning-Based Diagnostic Analysis

Monisha C M, Lakshmi D, V. Ramanathan, P. Mahalakshmi
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Abstract

The Internet of Things (IoT) is one of the smartest healthcare and management applications. This project aims to create a device that is a modern model of everyday ECG devices used by the doctors of our society these days. Wireless technologies and wearable sensors enable effective patient monitoring. Heart disease can't be taken lightly. Because heart disease has become a major problem for the last few decades and many people die due to certain health problems. Analyzing or monitoring the ECG signal at an early stage can prevent various heart diseases. The data from wearable sensors can be processed, analyzed, and classified using machine learning algorithms. The proposed method can be used to monitor and classify arrhythmia patients. Sensors worn by patients with arrhythmia and continuous monitoring can be done using IoT Cloud. This way the patient benefits because they have the freedom to be mobile and monitor in their normal environment. In this project, IoT Cloud is used to expand patient care, a way to monitor patients, visualize patient arrhythmia and classify hospital data.
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基于机器学习的无线心电图诊断分析
物联网(IoT)是最智能的医疗保健和管理应用之一。这个项目的目的是创造一个设备,是一个现代模型的日常心电图设备使用的医生在我们的社会这些天。无线技术和可穿戴传感器使有效的患者监测成为可能。心脏病是不能轻视的。因为在过去的几十年里,心脏病已经成为一个主要问题,许多人死于某些健康问题。早期分析或监测心电信号可以预防各种心脏疾病。来自可穿戴传感器的数据可以使用机器学习算法进行处理、分析和分类。该方法可用于心律失常患者的监测和分类。心律失常患者佩戴的传感器可以使用物联网云进行持续监测。这样病人就会受益,因为他们可以在正常的环境中自由活动和监控。在这个项目中,物联网云被用来扩展病人护理,一种监测病人、可视化病人心律失常和分类医院数据的方式。
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