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arXiv · 2505.18173

IoT-Enabled Hemodynamic Surveillance System: AD8232 Bioelectric Signal Processing with ESP32

Hemalatha R J·Shubham Malhotra·Shivapanchakshari T G·Lokesh K·Dev Anand D·Samson Jebakumar S
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Abstract

This dissertation proposes an electrocardiogram (ECG) tracking device that diagnoses cardiopulmonary problems using the Internet of Things (IoT) desired results. The initiative is built on the internet observing an electrocardiogram with the AD8232 heart rhythm sensor and the ESP32 expansion kit, using an on-premise connected device platform to transform sensing input into meaningful data. That subsequently supervises an ECG signal and delivers it to an intelligent phone via Wi-Fi for data analysis. That is the pace of the circulating. Assessing body temperature, pulse rate, and coronary arteries are vital measures to defend your health. The heartbeat rate may be measured in two ways: there are by palpating the pulse at the wrist or neck directly or other alternative by utilizing a cardiac sensor. Monitoring alcohol levels in cardiac patients is critical for measuring the influence of liquor on their health and the efficacy of therapy. It assists in recognizing the association between alcohol consumption and cardiac issues, rather than rhythm recorded in beats per minute (bpm). An IR transmitter/receiver pair (OLED) needs to stay compatible up near the sensor's knuckle current or voltage pulse. The detector's electrical output is evaluated by suitable electronic circuits to produce a visual clue (digital display). We must design a cost-effective, user-friendly, and efficient ECG monitoring system with contemporary technology for both persons imprisoned by disease or aging, as well as healthcare professionals. Microcontroller combined with software. A smartphone application is created to monitor the cardiovascular health of distant patients in real-time

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Hemalatha R J, Shubham Malhotra, Shivapanchakshari T G, Lokesh K, Dev Anand D, Samson Jebakumar S. 2025-05-14. IoT-Enabled Hemodynamic Surveillance System: AD8232 Bioelectric Signal Processing with ESP32. https://arxiv.org/abs/2505.18173

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