Advancing Remote and Continuous Cardiovascular Patient Monitoring through a Novel and Resource-efficient IoT-Driven Framework
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.
Code (0)
등록된 구현이 없습니다.
Tasks
Electrocardiography (ECG)Similar Papers 제목 키워드 기반
Predicting Medical Interventions from Vital Parameters: Towards a Decision Support System for Remote Patient Monitoring
Cardiovascular diseases and heart failures in particular are the main cause of non-communicable disease mortality in the world. Constant patient monitoring enables better medical treatment as it allows practitioners to r…
A Survey of Challenges and Opportunities in Sensing and Analytics for Cardiovascular Disorders
Cardiovascular disorders account for nearly 1 in 3 deaths in the United States. Care for these disorders are often determined during visits to acute care facilities, such as hospitals. While the length of stay in these s…
BIG-bench Machine LearningDecision MakingAn Electrocardiogram Monitoring Device Based on STM32
Cardiovascular diseases remain the leading cause of morbidity and mortality, particularly in aging populations, with rising rates of heart-related incidents in middle-aged and even younger individuals. Currently availabl…
A Novel real-time arrhythmia detection model using YOLOv8
In a landscape characterized by heightened connectivity and mobility, coupled with a surge in cardiovascular ailments, the imperative to curtail healthcare expenses through remote monitoring of cardiovascular health has …
Arrhythmia DetectionExplainable Artificial Intelligence (XAI)Quality Assessment of Photoplethysmography Signals For Cardiovascular Biomarkers Monitoring Using Wearable Devices
Photoplethysmography (PPG) is a non-invasive technology that measures changes in blood volume in the microvascular bed of tissue. It is commonly used in medical devices such as pulse oximeters and wrist worn heart rate m…
Photoplethysmography (PPG)