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IoT-Driven System for Continuous Monitoring of Heart Disease Patients Post-Surgery

2024/10/15 by Jayed Bin Harez, Shapla Akter, Harez, Jayed Bin +9
Computer Science · Engineering · #FOS: Physical sciences #Instrumentation and Detectors (physics.ins-det) #IoT and Edge/Fog Computing #Non-Invasive Vital Sign Monitoring

paper · pdf · doi:10.48550/arxiv.2410.11269

openalex publication_date 2024/10/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Healthcare technology has advanced with the development of an IoT-based real-time monitoring system for post-operative heart disease patients. This system integrates advanced sensor technologies with cloud-connected platforms to continuously track vital signs, enabling more effective post-operative care. The system employs the HW-827 Heart Rate Sensor and DS18B20 Temperature Sensor, integrated with an ESP32 for wireless connectivity, to collect real-time data. Data was collected from 20 participants in each of the following categories: healthy individuals, pre-operative heart disease patients, and post-operative heart disease patients. The results revealed distinct physiological variations across the groups. Healthy individuals maintained stable temperatures (mean 36.3°C), while post-operative patients exhibited slightly elevated temperatures (mean 36.6°C). Heart rate analysis indicated higher rates in pre-operative (mean 87.8 bpm) and post-operative patients (mean 82.0 bpm) compared to healthy individuals (mean 72.4 bpm). ECG analysis showed elevated readings in pre-operative patients (mean 0.16 mV) compared to healthy individuals (mean 0.10 mV) and post-operative patients (mean 0.12 mV). Statistical analyses, including ANOVA tests, confirmed significant differences among the groups in terms of temperature (F(2, 12) = 4.57, p < 0.05), heart rate (F(2, 12) = 5.91, p < 0.01), and ECG readings (F(2, 12) = 3.24, p < 0.05). This study demonstrates the potential of IoT technologies in enhancing post-operative care through continuous monitoring and data-driven insights. It emphasizes the role of real-time patient data in improving personalized healthcare management.

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