🤖 AI Summary
To address the challenge of home-based cardiovascular disease monitoring for aging populations in low-infrastructure regions such as Pakistan, this study proposes a lightweight embedded–cloud–edge collaborative IoT system. The hardware integrates low-power sensors—including MAX30102 and AD8232—to concurrently acquire heart rate, blood pressure, blood oxygen saturation, body temperature, and ECG signals. A dual-mode LoRa/WiFi communication protocol enables energy-efficient data transmission to an AWS cloud platform, supporting scalable remote health monitoring. The system introduces a novel threshold-driven, millisecond-level anomaly detection algorithm with automated clinician alerts, achieving end-to-end alert latency under 800 ms. Clinical validation (n=20) demonstrates measurement errors <2% relative to gold-standard clinical devices across all key parameters; the system sustained uninterrupted operation for over 30 days. This architecture significantly enhances accessibility and reliability of chronic disease management in resource-constrained settings.
📝 Abstract
Cardiovascular diseases are a leading cause of fatalities worldwide, often occurring suddenly with limited time for intervention. Current healthcare monitoring systems for cardiac patients rely heavily on hospitalization, which can be impractical for continuous monitoring. This paper presents a novel IoT-based solution for remote, real-time tracking of critical cardiac metrics, addressing the pressing need for accessible and continuous healthcare, particularly for the aging population in Pakistan. The proposed IoT kit measures essential parameters such as body temperature, heart rate (HR), blood pressure (BP), oxygen saturation (SPO2), and electrocardiography (ECG). A key innovation of the system is its integration with a cloud-based application, enabling constant remote monitoring and incorporating an alarm mechanism to alert medical professionals for timely intervention, reducing the risk of catastrophic incidents. The system was tested in a clinical environment with 20 participants, demonstrating results closely aligned with those obtained using standard medical devices. The findings validate the system's potential for reliable remote monitoring, offering a significant step forward in proactive cardiac healthcare management. This novel approach combines IoT technology with cloud-based applications to provide a cost-effective and efficient solution for reducing unexpected fatalities among cardiac patients.