IOT based heart attack prediction wearable device for human life saving
Project summary: Many people have become more concerned about having a sudden cardiac arrest. With the increase in popularity of smart wearable devices, an opportunity to provide an Internet of Things (IoT) solution has become more available. Unfortunately, out of hospital survi
2025-06-28 16:33:34 - Adil Khan
IOT based heart attack prediction wearable device for human life saving
Project Area of Specialization Internet of ThingsProject SummaryProject summary:
Many people have become more concerned about having a sudden cardiac arrest. With the increase in popularity of smart wearable devices, an opportunity to provide an Internet of Things (IoT) solution has become more available. Unfortunately, out of hospital survival rates are low for people suffering from sudden cardiac arrests. The objective of this research is to present a multisensory system using a smart IoT system that can collect Body Area Sensor (BAS) data to provide early warning of an impending cardiac arrest. The goal is to design and develop an integrated smart IoT system with a low power communication module to discreetly collect heart rates and body temperatures using a smartphone without it impeding on everyday life. This research introduces the use of signal processing and machine-learning techniques for sensor data analytics to identify predict and/or sudden cardiac arrests with a high accuracy.
Through the availability and advancement of wearable IoT devices, it aids patients in monitoring and controlling their health metrics. An example of the benefits is that a patient can be made aware of the status of their condition with the aid of such devices at any time. That information can then be made available to the treating health care professional to provide prompt action for a condition or save the life of the user in an emergency. Connected health is proving to be a major application for developing technologies.
Project Objective:
The strength of our system relies on existing wireless communications to provide low power with maximum freedom of movement to users in their physical activity. In addition, we have used small, light-weight smart IoT devices that are user friendly, like the smartphone and the wrist-band.
To integrate the sensors, we used the output of the embedded sensors to perform an extensive set of experiments for evaluating and discriminating between normal and abnormal heart rate patterns. Subjects wear the embedded sensors and carry their smartphone in their pocket or hold it in their hands. The embedded ECG and temperature sensors constantly collect the heart parameters while the subject is living a normal life. After receiving the data through a low power Bluetooth communication channel, the smartphone will process the data to classify whether the user’s condition is normal or abnormal. A quantitative heart rate analysis is performed in the Android platform which gives the user the option of viewing his/her real-time plots of the ECG signal and body temperature.
The IoT device constantly collects data from the user and sends it to smartphone via a Bluetooth communication module. All the processing and data analysis take place in the application where the user has the option to view user real-time plots. These plots provide the user a basic idea of his/her body’s status. The user does not have maintained a record of his/her data to ensure that s/he is in a healthy or unhealthy state since the application’s job is to alert the user upon an emergency. Finally, when the algorithm senses an abnormality it immediately alerts the user.
Project Implementation MethodProject implementation Method:
In this project we used different components and design an IOT based heart attack prediction device which predicts the heart beat.
The initial prototype system consists of GPS and GSM module, an Arduino Uno a pulse sensor.The other components are the power supply unit along with a smartphone with an application.
The Arduino simply serves as an Analog to Digital Converter (ADC) . An Arduino is an open-source physical computing platform based on a simple I/O board and a developmental environment that implements the processing/wiring language. The Arduino is programmed to read analog signals from the pulse and create a data packet to convert the signals into digital.
The performance of the device can be determined by measuring the current consumption which tells us how long the device can be powered. The voltage supplied from the battery is constant since the Arduino Mini takes the voltage it needs and supplies to the devices connected to it. The typical way to determine the performance of the device is by checking the amount of current that is drawn from the battery in the different modes. The two modes in which we test the device are the idle mode and the connected/transmitting mode. The measuring unit of the battery is in milliamp hour (mAH) which is an energy measure. A battery with 2200 mAH will work for an hour if the current drawn from it is always 2200 mA. Similarly, if the current draw is 1100 mA, the battery would last two hours. Therefore, to measure how long the device can be powered in the on state without the battery draining, we need to calculate the average current draw of the IoT device. Table 3 shows the current draws, the device’s lifetime, and the power consumption during the two modes for the IoT device.
Benefits of the ProjectBenefits of project:
Heart rate monitoring is a vital aspect of maintaining
heart health. People from different age groups have different
ranges for maximum and minimum values of heart rate, the
monitoring system must be compatible enough to tackle this
scenario. In this paper, an IoT based system has been
implemented that can monitor the heartbeat from the output given by a hardware system consisting of a NodeMCU and pulse sensor.
Further, an alert system is added which is executed if the
heartbeat goes below or above the permissible level given in the devised algorithm. The alert message is received by the doctor through a mobile phone application. By using this prototype the doctors can access the heartbeat data of the patient from any location.The nurses or the duty doctor available at the hospital can monitor the heart rate of the patient in the serial monitor through the real-time monitoring system. The prototype is integrated with GPS technology to monitor the live location of the device from any part of the world and uses a local server to provide
security, privacy and low latency. The heartbeat data and other personal details of the patient are stored in the cloud, this can be utilized for future studies on the health condition of the patient. The location of patient will be send by GSM module to emergency contact for quick treatment.
Technical details of final deliverable:
we use the relationship between an individual’s pulse rate to design an algorithm that predicts heart attacks. This required a very good understanding of the human’s body behavior in both normal and abnormal states. The normal states are simpler and can be analyzed easily.A person’s heart rate in normal cases would range from 60 to 100 beats per minute. Any heart rate out of that scope is something that needs to be diagnosed properly and as soon as possible. Of course, humans have different heart rates in normal states which can vary for different age groups and different health conditions. Athletes tend to have lower heart rates around 50 to 60 beats per minute in resting state, while when exercising their heart rates can go up to 150 beats per minute or even more. People who do not normally exercise can have heart rates ranging from 70 to 90 beats per minute. So, it’s very important to consider the different subjects that are under study. Thus, we propose a smartphone-based heart attack prediction system that can alert users about their abnormal ECG patterns. Since abnormal ECG patterns can lead to a myocardial infarction, the system uses the identification of an abnormal heart-rate to alert the user regarding a potential heart attack. The proposed system is useful, not only among elderly, but also has a scope in identifying heart disease among children, adults, and stroke patients. Keeping track of a user’s body temperature is very helpful and can provide additional indications to help predict heart attacks. In general, prior to heart attacks, people’s body temperatures tend to go up. Even though there is a correlation between these entities, we do not assume that there is a direct relationship between them; however, this correlation gives a better chance of prediction
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 40150 | |||
| Arduino uno | Equipment | 1 | 1500 | 1500 |
| Heart beat sensors | Equipment | 10 | 300 | 3000 |
| Wi-Fi module | Equipment | 1 | 4000 | 4000 |
| GSM module | Equipment | 1 | 4500 | 4500 |
| GPS module | Equipment | 1 | 4000 | 4000 |
| Temprature sensor | Equipment | 1 | 200 | 200 |
| Connecting wires | Equipment | 50 | 70 | 3500 |
| LCD | Equipment | 1 | 500 | 500 |
| Resisters | Equipment | 10 | 20 | 200 |
| Bluetooth chip | Equipment | 1 | 1500 | 1500 |
| Transformer | Equipment | 1 | 3000 | 3000 |
| Inductors | Equipment | 3 | 150 | 450 |
| Capacitors | Equipment | 15 | 50 | 750 |
| Relays | Equipment | 3 | 300 | 900 |
| Diods | Equipment | 5 | 50 | 250 |
| Degital heart beat screen | Equipment | 1 | 1500 | 1500 |
| Bread boards | Equipment | 1 | 400 | 400 |
| Miscellaneous | Miscellaneous | 10 | 1000 | 10000 |