Heart Rate Monitoring System

Patil, Minal; Madankar, Abhishek; Khandait, P. D.

doi:10.1109/icaccs.2019.8728501

Cited by 14 publications

(3 citation statements)

References 3 publications

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“…It utilizes the sensor to measure oxygen saturation and heart rate. Sensor and matrix keypad are interfaced to the Raspberry Pi that allows checking heart rate readings and transmitting them over to cloud [8]. When one of the fingers is placed on the sensor's surface, a digital representation of the heartbeat is produced.…”

Section: Proposed Systemmentioning

confidence: 99%

Edge Computing-Based Cardiac Monitoring and Detection System in the Internet of Medical Things

Murugesan,

Naganathan

2024

MEDIN

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Currently, cardiac disease becomes one of the major health issues in the world. The death due to cardiac arrests has been increasing day by day. The survival rate for the sudden cardiac arrest is low. It is possible to save 60% human life by continuously monitoring the fitness of the person. In recent times, the Internet of Things is emerging promising technologies. If the doctor cannot monitor the patient face to face, there Internet of Things plays important role in remotely monitoring the patient’s condition. With the rise in the use of smart wearable gadgets, the contribution of IoT will be more. In this paper, about five predictor model are analyzed for a particular dataset and chosen the best as Random forest algorithm. The proposed system integrates oxygen saturation level and heart rate sensor data from MAX30100 sensor for monitoring the patient’s vital signs. The remaining parametric data of the patient (AGE, GENDER, BLOOD SUGAR LEVEL, BLOOD PRESSURE LEVEL, GENETIC ISSUE and CHLOESTEROL LEVEL) are fed through the matrix keypad. The designed system monitors the online patient’s vitals continuously. The patient’s vitals will be stored in the edge server and also analyzed. The chosen predictor model checks the vital data for any abnormality and based on abnormality data detection in the heart rate, the warning message is conveyed to the nearby health care center via Thingspeak cloud. By tracking the patient’s GPS location, the server cloud sends alert notification along with the GPS location to the nearby health center and to the registered mobile numbers.

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Section: Proposed Systemmentioning

confidence: 99%

Edge Computing-Based Cardiac Monitoring and Detection System in the Internet of Medical Things

Murugesan,

Naganathan

2024

MEDIN

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“…Wearable devices constitute an effective, convenient, and handy solution for monitoring the HR of COVID-19 patients. Patil et al (2019) developed a wireless device to continuously monitor heart activity. The system acquires and processes the data from a photoplethysmography (PPG) sensor and provides short message service (SMS) to medical staff and parents for quick rescue.…”

Section: Wearable Devices and Sensors To Detect Covid-19 Symptomsmentioning

confidence: 99%

Wearable devices and IoT applications for symptom detection, infection tracking, and diffusion containment of the COVID-19 pandemic: a survey

Fazio

Giannoccaro

Carrasco

et al. 2021

Front Inform Technol Electron Eng

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Until a safe and effective vaccine to fight the SARS-CoV-2 virus is developed and available for the global population, preventive measures, such as wearable tracking and monitoring systems supported by Internet of Things (IoT) infrastructures, are valuable tools for containing the pandemic. In this review paper we analyze innovative wearable systems for limiting the virus spread, early detection of the first symptoms of the coronavirus disease COVID-19 infection, and remote monitoring of the health conditions of infected patients during the quarantine. The attention is focused on systems allowing quick user screening through ready-to-use hardware and software components. Such sensor-based systems monitor the principal vital signs, detect symptoms related to COVID-19 early, and alert patients and medical staff. Novel wearable devices for complying with social distancing rules and limiting interpersonal contagion (such as smart masks) are investigated and analyzed. In addition, an overview of implantable devices for monitoring the effects of COVID-19 on the cardiovascular system is presented. Then we report an overview of tracing strategies and technologies for containing the COVID-19 pandemic based on IoT technologies, wearable devices, and cloud computing. In detail, we demonstrate the potential of radio frequency based signal technology, including Bluetooth Low Energy (BLE), Wi-Fi, and radio frequency identification (RFID), often combined with Apps and cloud technology. Finally, critical analysis and comparisons of the different discussed solutions are presented, highlighting their potential and providing new insights for developing innovative tools for facing future pandemics.

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“…This indicates a regular heart rhythm in Figure 1, the cardiac signal forms a PQRST wave pattern, where the P wave indicates atrial depolarization triggered by the SA node, the PR segment indicates the cessation of impulses at the AV node, the QRS wave indicates ventricular depolarisation, the ST wave indicates the absence of impulses due to the refractory period and the TCardial period. According to Patil et al [5], normal ECG waves have characteristics as shown in Table 1. In general, the calculation of the heart rate (BPM) value starts from the interval between R and R, which indicates the period of heartbeat that can be converted into heart rate (H): H=6000/(R-R) (bpm), where R-R is the interval between peak signal R and peak signal R measured in milliseconds.…”

Section: Introductionmentioning

confidence: 99%

IoT-based health information system using MitApp for abnormal electrocardiogram signal monitoring

Utomo,

Triwiyanto,

Luthfiyah

et al. 2024

Bulletin EEI

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Information systems are currently developing very rapidly, and this is inseparable from the role of internet of things (IoT) technology, especially in the world of telemedicine. MitApp is an open-source application that can be used to monitor electrocardiogram (ECG) signals in real-time. The aim of this study is to develop an IoT-based ECG signal monitoring system that utilizes the MitApp application to detect abnormal ECG signals that are characterized by symptoms of cardiac arrhythmias. To process ECG signal data obtained from lead electrode results, the research method utilizes Arduino Uno as a microcontroller. The result is then displayed on the thin film transistor (TFT) layer using the Nextion module. The ESP32 module is used as a Wi-Fi module to send data to the MitApp app on a smartphone. The results showed that the results of the comparison test of ECG signal module data with ECG simulator tools with beats per minute values of 60, 80, 100, 120, and 140 obtained an error rate of 0.05. Based on these results, there is potential to develop this feature and integrate the system with the patient management system to improve the effectiveness of remote monitoring.

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Heart Rate Monitoring System

Cited by 14 publications

References 3 publications

Edge Computing-Based Cardiac Monitoring and Detection System in the Internet of Medical Things

Edge Computing-Based Cardiac Monitoring and Detection System in the Internet of Medical Things

Wearable devices and IoT applications for symptom detection, infection tracking, and diffusion containment of the COVID-19 pandemic: a survey

IoT-based health information system using MitApp for abnormal electrocardiogram signal monitoring

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