International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017
p-ISSN: 2395-0072
www.irjet.net
Design of Self-Learning System for Diagnosing Health Parameters using ANFIS Anitha.A [1], Mahalakshmi.R [2], Vidhya.J3, Jayanthi.G4 Student[1,2,3]Assistant professor[4], Department of ECE, Parisutham Institute of Technology & Science, Tamil Nadu, India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract – Nowadays, predicting of heart diseases is critical issue for humans. In previous, heart diseases cannot be identified before it attacks. This paper describes the work of self learning system for monitoring heart activities using ANFIS. Here, heart diseases can be understood after reaching abnormal state or in any fall detection stage. This paper develops a method of classifying the degree of heart diseases in patients using ANFIS. Neural network will predict the targeted level and fuzzy-logic compares the targeted level with current inputs and optimizes it. Here IoT plays a major role. The predicted and optimized data about heart disease is posted in the server for continuous information and it will be posted for every 10seconds interval. Hence the preliminary stages of heart diseases can be identified and recovered and also current problems and future directions can be identified. Key Words: ECG, Pulse Oximeter, Arduino UNO, ThingSpeak server. 1. INTRODUCTION
Heart diseases mainly occur due to blocking of blood vessels. It includes coronary artery diseases, myocardial infarction, bradycardia and tachycardia. This may be caused by high blood pressure, obesity, smoking, poor diet. High blood pressure results in 13% of CVD deaths, tobacco results in 9%, stoutness 5% and diabetes 6%. Coronary vascular disease is avoidable by predicting it earlier. Human computer interaction system is a study of relationship between people and computers mediated information. The future of human computer interaction system lies in how intelligently these systems can take into account the user’s context like Application areas, social organisation and work. Researchers on recognising the daily activities of people has progressed steadily but little focus has been devoted to recognizing jointly activities as well as movements in a specific activity.
outdoor precision GPS. Through health care centre, doctors can assist the detailed health condition of a patient when the patient reached the abnormal stage or fall, that notification for rescuing them is send to healthcare box. Healthcare box constantly record the status of the ECG signal. Once abnormal stage is reached, it will give an emergency notification to doctors and concerned family members. It has some disadvantages like remote monitoring of patients, prediction of diseases is not possible, heavy cost.
2. PROPOSED SYSTEM In this paper, Neuro-Fuzzy based health diagnosis and Arduino is used as a gateway to communicate to the various sensors such as ECG sensor, Temperature sensor, and Pulse Oximeter sensor. The microcontroller picks up the sensor data and sends it to the network through WiFi and hence provides real time monitoring of the health care parameters for doctors. Initially, ANFIS algorithm is converted as embedded C code and it is dumped in microcontroller. Usually ANFIS has two parts: a) Training b) Testing. In the training part, targeted level is set by giving some data as input from the data set of LVM file. During testing, the clinical input data from the patient body is compared with the targeted values. The data can be accessed anytime by the doctor. In this, remote monitoring system is that the data as to be securely transmitted to the destination end and provision is made to allow only authorized user to access the data. User/doctor can access the data by logging in to the html webpage. At the time of extremity situation in order to prevent the patient from abnormal situation, a twitter alert message is sent to the doctor through ThingSpeak server (Internet of Things) which is connected to the controller. A mobile application software (ThingsView) is also provided to check the health conditions of a patient continuously through the mobile phone.
1.1 EXISTING APPROACH In the existing system, health care system was used to monitor the physiological signal and current position of a patient by automatic learning feature. Health care box was used for automatic detection of ECG signals and position of the patient. ECG acquisition module detects the signal and transmits it to the health care centre. The position of the patient position of patient can be recognized using an © 2017, IRJET
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