

ECG Monitoring Using Arduino UNO
Abstract
Wellbeing today is difficult for everybody, and monitoring one's wellness consistently is vital for carrying on with a sound life. However, due to the high cost and time commitment of modern medical examinations, people frequently fail to attend them or are unable to do so on a daily basis, putting them at risk for serious illness. This report proposes a minimal expense, high-precision IOT-based wearable wellbeing checking framework considering the main thing in need of attention. The proposed model is made up of the pulse sensor MAX30100, the temperature sensor NTC (Negative Temperature Coefficient), the OLED display, and Bluetooth HC-05. The proposed system uses the beat sensor MAX 30100, the temperature sensor NTC, and the RTC DS1307 to estimate the heart rate, oxygen level, internal heat level, and work out the date, year, and month. It then displays these data on a 0.96-inch OLED screen so that the customer can see how healthy they are all the time. These data can also be viewed by the user on their mobile phone. The client can either save these information to their cell phone or transfer them to the cloud, where any approved client can sign in and view the information, regardless of whether that individual is far away from the client. This sort of framework enjoys the benefit of being modest and offering exact outcomes. There are three sections to the mobile application. The first section displays data before saving it to the device and uploading it to the cloud. The subsequent part counts the number of steps the client that took and the number of calories they consumed. The third part takes information from the client and chooses if the client is in peril mode. Assuming the client is in peril mode, the status will change to "Risk" and the name of the illness will likewise be displayed in the android application to show that the patient will have this sickness. Just two sorts of infections can be anticipated utilizing the proposed strategy — coronary illness and fever.
References
Kiourexidou, M., Natsis, K., Bamidis, P., Antonopoulos, N., Papathanasiou, E., Sgantzos, M., & Veglis, A. (2015). Augmented reality for the study of human heart anatomy. International Journal of Electronics Communication and Computer Engineering, 6(6), 658.
Das, S. (2013). The development of a microcontroller based low cost heart rate counter for health care systems. International Journal of Engineering Trends and Technology, 4(2), 207-211.
Pulse, I. E. (2012). A DIY photoplethys mographic sensor for measuring heart rate. Embedded Lab, 13.
Sankar Kumar, S., Gayathri, N., Nivedhitha, D., & Priyanka, A. S. (2015). A Cost effective Arduino Module for Bedridden patient’s Respiratory Monitor and Control. International Journal of advanced research trends in engineering and technology (IJARTET) VOL. II, SPECIAL ISSUE XXI.
Subudhi, C. S. K., & Sivanandam, S. (2014). Intelligent Wireless Patient Monitoring and Tracking System (Using Sensor Network and Wireless Communication).
Refbacks
- There are currently no refbacks.