Cy Sician-Revolutionizing Patient Health Monitoring System with auto-diagnosis
Budhaditya Bhattacharya1, Prakhar Jain2, Sudeshna Das3
1Budhaditya Bhattacharya*, School of Electronics & Communication Engineering, Vellore Institute of Technology, Vellore, India.
2Prakhar Jain, School of Electronics & Communication Engineering, Vellore Institute of Technology, Vellore, India.
3Sudeshna Das, School of Electronics & Communication Engineering, Vellore Institute of Technology, Vellore, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 26, 2020. | Manuscript published on April 10, 2020. | PP: 1809-1813 | Volume-9 Issue-6, April 2020. | Retrieval Number: F4571049620/2020©BEIESP | DOI: 10.35940/ijitee.F4571.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cardiovascular diseases (CVD) has emerged as one of the major causes for death in all over the world. This paper displays a framework to remotely screen, health of Cardiovascular disease affected patients utilizing Machine to Machine (M2M) innovation which is a part of the project called CySician . Real time patient health monitoring system is advantageous to the patients and society as it will significantly reduce medical charges, waiting time for patient and improve patient handling capability of any hospital. In this patient health monitoring system pulse rate, ECG, body temperature, Body Mass Index(BMI) and general clinical interrogation is finished by a chatbot named “LifeBot”. The primary components associated with this project are pulse sensor, Raspberry Pi 3B+ (processing unit), temperature sensor module sensor, utilizing Machine Learning (ML) calculation it automatically analyzes the accumulated information to propose prescription to the patient. After the patient is diagnosed and the disease is detected, the patient will be notified with the kind of medication he needs. If the problem is nominal, the patient will be suggested with a basic treatment and will be monitored regularly. If the problem is of major scale, the patient will be directed to the payment gateway where he will be asked to pay a nominal fee for appointment from doctors to continue his check-up .Ultimately, the final well-being report is displayed to the doctor on the User interface that is visible on PC/Laptop.
Keywords: CVD, M2M, Health Monitoring, Pulse rate, BP, ECG, BMI, LIFEBOT, ML, Raspberry Pi, Payment Gateway
Scope of the Article: Health Monitoring and Life Prediction of Structures.