Figure 1. Block Diagram of IoT Based Health Monitoring System
In recent years, there is a tremendous rise in physical and mental issues related to abnormal heart rate and blood pressure. These issues can often lead to death. This brings in a condition where continuous monitoring of heart rate and blood pressure is crucial. Monitoring in hospitals can be uncomfortable for various reasons and at times it can get interrupted. A portable patient monitoring system for round the clock ambulatory monitoring can offer better service for this purpose. The goal of this paper is to design a sensor network system for health and safety application with the use of Internet of Things (IOT) to store and transmit the activity of an individual. This system involves the use of heart rate and SpO2 sensor, blood pressure sensor and temperature sensor for measuring the physical parameters of the individual. The sensors are interfaced with the Arduino Uno. GSM module is connected to the system for alerting the doctor in case of emergency. The use of GPS makes it possible to track the location of the individual. Further all the patient's data are stored in cloud for future accessing.
With growing population, the number of diseases are also increasing tremendously. This is due to the lack of consciousness on health. Improper sleep, unhealthy eating habits, lack of workout are some of the reasons of prevailing malady. Hypertension (high blood pressure) can lead to severe health complications and increase the risk of heart disease, stroke, and sometimes death. Hypertension is the leading cause of mortality in the world, responsible for 9.4 million deaths worldwide every year. About 30 % of adults have raised BP and prevalence of hypertension increased with Body Mass Index (BMI) and age. It has now become clear that daily BP readings have greater predictive power for cardiovascular events than isolated in-clinic measurements, because the later practice may introduce white-coat hypertension, masked hypertension, and ignores the BP variability. Heart rate also provide lot of information about the physical as well as mental activity of an individual. Both heart rate and blood pressure indicate how well our heart is working and can signal potential cardiac problems. Oxygen saturation is an essential element in the management and understanding of patient care. Oxygen is tightly regulated within the body because hypoxemia can lead to many acute adverse effects on individual organ systems. These include the brain, heart, and kidneys. By monitoring the parameters such as blood pressure, heart rate and oxygen saturation at a frequent pace, the heart related illness could be avoided. There are many cost-effective methods for patient health monitoring available, however, an IoT based monitoring is required, when the patient is not at the hospital. The fact that they are being monitored when at home gives the patient a sense of peace and helps them to be relaxed and stress free where ever they are, given that their location can be known by the authorized people. In comparison to the existing approaches, some of the distinguishing characteristics of this IoT based model can be outlined as follows:
Miah et al. (2013) propose a method in which the heart rate of a human body can be measured considering the change of blood volume using microcontroller based methods. They have implemented a low cost computer based heart rate monitoring system which is portable. Pawar (2014) gives a continuous patient heart rate monitoring system and also uses GSM to alert the doctor. Again, this approach is only suitable when the patient is at the hospital. The proposed paper gives a solution for continuous patient monitoring even when the patient is outside the hospital.
Mahmood and Ercelecbi (2018) gives oscillography and korotkoff methods of measuring blood pressure. The issue with this model is that data can be stored up to only 100 records in the MCU internal memory. The proposed model overcomes that problem by using cloud to store as much data as needed. Liang-Yu Shyu et al. (2012) provides a cuffless method for blood pressure monitoring. Though it seems a convenient way of monitoring blood pressure it lacks accuracy. The primary goal of the proposed model is to give accurate readings.
Gohlke et al. (2020) presents the usage of two PPG sensors, one placed at the wrist and the other placed at finger tip of the patient to obtain the heart rate. PPG is a cuff-less and non-invasive method to measure changes in blood volume. Chu et al. (2017) proposed a non-invasive optical heart rate monitor based on one chip integration microcontroller solution for Photoplethysmogram (PPG) heart rate monitor. The PPG monitor circuit was implemented in the MSP430I2041 which achieved easy detection operating environment for body PPG signal acquisition. Disadvantage of this method is noise would be present.
Narasimhan et al. (2018) proposed a blood pressure measurement which is achieved using a two-dimensional capacitive tactile sensor array that is located next to a digital artery. The digital artery pressure waveform data collected are used to estimate the arterial blood pressure. Shaltis et al. (2008) presents a new principle for noninvasive blood pressure measurements through a modified volume-oscillometric technique that eliminates an inflatable pressure cuff, and instead takes advantage of natural hydrostatic pressure changes caused by raising and lowering the subject's arm. Azhari et al. (2017) propose a method which uses an optical sensor to measure the amount of oxygen saturation in blood. The light sources used to detect the PPG signal are separated by a switch and are then digitized into SpO2 values. The major disadvantage in this method is that the patient might feel inconvenience while wearing the headband containing the sensor and system set.
Natarasan and Sekar (2020) proposed a method for measuring SpO2 based on the principle of Beer's law. Beer's law states that the amount of light absorbed is proportional to the concentration of absorbing substance. An application is also developed in this method which sends a push notification to the doctor via a cloud server where the patient's data are securely stored and can be viewed by the doctor. Elagha et al. (2019) presents the design of a non-invasive medical device that is capable of monitoring and measuring the saturation of peripheral oxygen (SpO2) in a patient's blood as well as their heartbeat rate simultaneously. A PIC microcontroller and an optical sensor were used and the acquired signals from the sensor were filtered, processed, numerically calculated and displayed by the Matlab program.
A continuous temperature monitoring system has been designed by Joseph et al. (2018). With the use of temperature sensor and the android application, the body temperature of the infants could be monitored continuously whereas the existing thermometer can only measure the current temperature value. An IOT based health monitoring and tracking system for soldiers is proposed by Patii and Iyer (2017). Pulse rate, body temperature, and oxygen level of the soldiers can be monitored. GPS is used to track the location of the servicemen. The transmission of these parameters to the control room is carried out by IoT.
Nookhao et al. (2020) proposed a portable heartbeat and body temperature monitoring system. The device shows the heartbeat and temperature readings on LCD display and at the same time sends them to the cloud platform in real-time via Wi-Fi. B. Hu et al. (2018) proposes a home health care and monitoring architecture for the elderly people. There are sensors integrated in the system to measure human vital sign, sleeping and movement pattern. The output readings are transmitted to cloud storage where it is able to provide real time information to close family members and care takers. The developed system is able to send out emergency request when elders are in danger at home.
The drawbacks in the existing systems are overcome in the proposed system by continuous monitoring of heart rate and blood pressure and blood oxygen saturation (SpO2). The paper is organized as follows. Section I covers the proposed methodology for patient monitoring. Results and discussion of the proposed method is given in section II. Final section III covers the conclusion.
The block diagram of the proposed health monitoring model is shown in Figure 1. In this model a compact equipment is designed. The design consists of Arduino UNO microcontroller, blood pressure sensor, Max 30100 pulse oximetry sensor which measures the oxygen saturation level as well as heart rate, LM35 temperature sensor, ESP8266 Wi-Fi module, LCD, GPS and GSM modules.
Figure 1. Block Diagram of IoT Based Health Monitoring System
The Arduino Uno is an open-source microcontroller board based on the Microchip ATmega328P microcontroller and developed by Arduino.cc. It has 20 digital input/output pins, a 16 MHz resonator, a USB connection, a power jack, an in-circuit system programming (ICSP) header, and a reset button. Arduino obtains the analog data from the sensors, processes it and provides the result to LCD. It is powered using USB cable. UART Serial communication takes place in Arduino.
Arduino IDE software is used for interfacing the sensors to the board. Embedded C is used for coding the board. Figure 2 shows the description of Arduino UNO board.
Figure 2. Schematic Diagram of Arduino UNO Board
The MAX30100 is an integrated pulse oximetry and heart rate monitor sensor solution. It combines two LEDs, a photo detector, optimized optics, and low-noise analog signal processing to detect pulse oximetry and heart-rate signals. The structure of MAX 30100 sensor is shown in Figure 3. The MAX30100 operates from 1.8V and 3.3V power supplies and can be powered down through software with negligible standby current, permitting the power supply to remain connected at all times. In this paper the MAX30100 sensor is used to get the heart rate and oxygen saturation levels of the patient. It works on the principle of differential absorption.
Figure 3. Structure of MAX 30100 Sensor
The ESP8266 Wi-Fi Module is a self-contained SOC with integrated TCP/IP protocol stack that can give any microcontroller access to the Wi-Fi network. The ESP8266 shown in Figure 4 is capable of either hosting an application or offloading all Wi-Fi networking functions from another application processor. Each ESP8266 module comes pre-programmed with an AT command set firmware, meaning, you can simply hook this up to the Arduino device and get about as much Wi-Fi ability as a Wi- Fi Shield offers. In the proposed method, this module is used to store the data in the cloud and can be accessed from anywhere in the world.
Figure 4. ESP8266 Wi-Fi Module
GPS, or the Global Positioning System, is a global navigation satellite system that provides location, velocity and time synchronization. GPS is everywhere. You can find GPS systems in your car, your smart phone and your watch. GPS helps you get where you are going, from point A to point B. The GPS receiver calculates its own position and time based on data received from multiple GPS satellites. Each satellite carries an accurate record of its position and time, and transmits that data to the receiver. In this paper GPS tracking system is used to track the location of the patient. Figure 5 shows the PPG Signal.
Figure 5. PPG Signal
GSM stands for Global System for Mobile communication and is a digital mobile network that is primarily used with mobile phones in Europe and other parts of the world. The technique uses different Time Division Multiple Access (TDMA). GSM compresses uses digitalization to compress data and sends it through a channel with two other streams of user data, with each taking place in their own time slots. Here the GSM module is used to send continuous messages to the physician indicating the readings of the patient. In case of abnormality an alert call is made to the physician.
Heart rate, Blood pressure and oxygen saturation are some of the important parameters of human body which gives information about the physical and mental wellbeing of the patient. With the proposed model it is possible to measure these parameters at ease. It is known that normal heart rate is usually stated as 60 to 100 beats per minute. Slower than 60 is bradycardia ("slow heart"); faster than 100 is tachycardia ("fast heart"). The MAX30100 sensor employed in this system monitors the heart rate and detects any abnormality from the PPG signal. The PPG signal is shown in Figure 5.
The oxygen saturation can also be detected from the pulse oximetry MAX30100 sensor, and thus any deviation from the normal level can be detected. Hypoxemia occurs when the blood oxygen level falls below the normal level. The classification of Hypoxemia is indicated in Table 1.
Table 1. Classification of Hypoxemia
The blood pressure sensor in this model is used to monitor the data to make sure it is does not exceeds the threshold. The variations of systolic and diastolic blood pressure variations are indicated in Figure 6.
Figure 6. Systolic and Diastolic Pressure Variations
An efficient health monitoring system was proposed in this paper. The system employs sensors such as heart rate and blood pressure sensor which are interfaced with Arduino Uno for monitoring of the patient. This model makes continuous monitoring of physical parameters possible without going to the hospital. The monitored data is stored in the cloud for further access. The system also has features for alerting the caretaker through call in case of emergency. The main advantage of this model is that it provides 24h uninterrupted monitoring of patient's parameters, thus making efficient health monitoring feasible and more comfortable to the patients.