International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 05 | May 2025
p-ISSN: 2395-0072
www.irjet.net
Advanced cardiac health monitoring system Mohini Agrawal*1, Abhishek Kumar*1, Kunal Maurya *1 , Awanish Kumar Shukla *1 1 Mohini Agrawal UG Student, Department of Electronic and Communication Engineering, Shri Ramswaroop
Memorial College of Engineering and Management, Lucknow, Uttar Pradesh, India 2 Abhishek Kumar UG Student, Department of Electronic and Communication Engineering, Shri Ramswaroop
Memorial College of Engineering and Management, Lucknow, Uttar Pradesh, India
3 Kunal Maurya UG Student, Department of Electronic and Communication Engineering, Shri Ramswaroop Memorial
College of Engineering and Management, Lucknow, Uttar Pradesh, India
4 Awanish Kumar Shukla Professor, Department of Electronic and Communication Engineering, Shri Ramswaroop
Memorial College of Engineering and Management, Lucknow, Uttar Pradesh, India *** 1. INTRODUCTION Abstract - The rising global burden of cardiovascular diseases (CVDs) underscores an ever-growing need for realAccording to WHO, CVDs continue to be one of the most time, accurate, and user-friendly cardiac monitoring systems troublesome problems of global health, causing 17.9 million as an effective preventative measure for early diagnosis and deaths a year. This is a heartbreaking number that highlights treatments. It also proposes a novel model of cardiac health the need for effective, constant, and seamless cardiac health monitoring system using an ESP32 microcontroller along with monitoring platforms. In general, the prevention of MI, blood pressure and ECG sensing technologies. In order to arrhythmias, HF by hypertension and other CVDs involve reduce noise and motion artifact, the system first harvested comprehensive monitoring and early detection of all cardiac signals via ECG electrodes. This stage amplifies and processes related to cardiac function. BP measurement and filters these signals. Store Data: Upload processed data to an electrocardiography (ECG) have long been of great significance online repository for analysis Using feature extraction and in cardiology as routine diagnostic procedures. The ECG has machine learning algorithms, the system is able to generalize been utilized for over 70 years as one of the major diagnostic multiple cardiac conditions but not limited to Normal rhythm, instruments used in the assessment of electrical function of Premature Ventricular Contractions (PVC), Right Bundle the heart for pathology tailors and failures such as ischemia or Branch Block (RBBB), Left Bundle Branch Block (LBBB). The arrhythmias. Furthermore, blood pressure is a mainstay of mobile application interface acts as an extra part of the clinical assessment of cardiovascular health, especially for architecture that easily relays the diagnostic results to family atherosclerosis and hypertension. But both conventional and health professionals. This feedback loop facilitates ways of tracking ECG and blood pressure are limitedly used for continuous monitoring of patients outside of traditional clinical settings, where they can only be operated in specified clinical settings with the potential for improving remote intervals. Clinically important, worrisome symptoms that arise patient management and timely alerting. Modern between visits may therefore go undetected — particularly infrastructural support for modern cardiac healthcare: such as among patients with intermittent. Advancements in wearable the integration of sensing, wearable technologies, mobile electronics, wireless communication systems, and algorithms communication, and intelligent diagnosis in the cloud. The of machine learning (ML) have transformed intelligent health system combines clinical-grade monitoring with consumermonitoring systems that can be automated into reality. These grade wearable. systems attempt to combat many of these limitations. Today, with the integration of biosensors and IOT (Internet of Things) Key Words: CardiacHealthMonitoring,Electrocardiogram linked wearable, cardiac health parameters can be monitored (ECG), Blood Pressure Sensor, Wearable Health Devices, continuously and in real time without going to the patients. Internet of Things (IoT), Machine Learning Algorithms, ESP8266 Microcontroller, Real-time Health Diagnosis, These developments increase patient compliance and Remote Patient Monitoring Systems, Advanced Healthcare engagement, but also equip physicians with timely data to Technology. make improved clinical decisions. But commercial wearable technologies such as fitness analysis and smart watches; Impact Factor value: 8.315
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