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Talk · International Conference on Computing, Communication and Networking Technologies · June 24, 2024

Wireless ECG Monitoring and Automated Heart Diagnosis: A Mobile App Solution Using Deep Learning

Sunil M, Thippaluru Tharun Sai, Thokali Sanjay, Uppalapati Dhanush, C. Jyotsna

Jyotsna Chandrasekharan
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Abstract

This research presents a novel solution to the serious global health issue of cardiovascular diseases. The suggested technology revolutionizes remote cardiac monitoring by combining wireless Electrocardiogram sensors and powerful deep learning algorithms. A user-friendly mobile application acts as a center for data collection, storage, and analysis in real time. More importantly, a convolutional neural network can be used for the automatic detection of cardiac problems by pattern extraction from Electrocardiogram readings. The system enables immediate action by sending real-time notifications for detected anomalies, while also keeping a detailed historical record for long-term monitoring. Prioritizing data security, messages are encrypted, and the system contains user authentication mechanisms that are in line with healthcare standards. Engaging individuals in proactive health management, this proposal aims to foster cooperation between users and healthcare providers for better patient outcomes. The suggested system shall offer accessibility, accuracy, and user centricity, coupled with a new approach toward solving the global cardiovascular disease crisis using wireless Electrocardiogram monitoring and deep learning technology.

ECG Monitoring and AnalysisNon-Invasive Vital Sign MonitoringArtificial Intelligence in Healthcarewireless ECG monitoringremote cardiac monitoringconvolutional neural networks

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