Implementing Patient Health Status Monitoring System based on IoT For Increasing Efficiency

Cardiovascular diseases pose a major threat in developing countries with death rates on the rise. Illnesses such as heart attack and hypertension top the list. Statistically speaking, at least 60 per cent of patients who go to hospitals with heart attacks are between the age of 20 and 30 with the number likely to increase in the forthcoming years (Merab, 2016)

The World Health Organization (WHO) on its annual report on non-communicable diseases (Alwan, 2010) highlighted the non-communicable disease vast effects, further stating that the death rates are on the rise especially targeting the middle aged population. It is postulated that smoking cigarettes and poor feeding habits among many others are high risk factors that have dealt a big blow to the population as effects of premature death and high cost encountered to treat resultant diseases. Lack of proper infrastructure, technology for handling cardiovascular diseases, inadequate mass education on healthy lifestyle tips, poor emergency response among many other factors has resulted in increased death rates of cardiovascular disease patients in 3rd world countries.

Across the globe, governments are making innovative steps to deal with this epidemic as with the intense research methods and innovations in the IT and Telecommunication sector. Wearable devices by patients are in use to keep them up to date with their BMI (Body Mass Index) levels, heart rate and glucose levels. This has significantly taken root as a new way of

checking health status of the patients. Activity trackers are in use widely in management of diabetes e.g. glucose meters; heart rate monitors during exercises for cardiovascular diseases management.

Mobile technology has also featured in the diseases problem solving endeavor through the Preventing and Managing Diseases with Mobile Technology program. An example is the AliveCor mobile ECG system for cardiovascular health that enables a user obtain a real-time heart rhythm tracing (electrocardiogram) for their mobile phone.

However, as better a service providence and problem solving these innovations are, they have some demerits. They fail to offer direct user experience in form of one on one communication with the medical doctors and cardiologists who can effectively monitor your health condition and link you to relevant treatment options wherever you are. The impact of technology as problem solving criteria for patients has not yet been effective. Majority of patients are monitored effectively for their illnesses at the hospitals and health centers when sometimes their health status can be remotely monitored i.e. at the comfort of their homes or even at work places.

Sensors and interconnection technologies deliver rich value-added data tracking services. The sensors are capable of quick data gathering and accurate recording. Data can be stored in memory and can be retrieved later for analysis and representation. Patient data can be collected dynamically to foster preventive care and diagnostics and measurement of treatment results. However, the use of sensors and RFID tags has not yet been effectively implemented to guarantee Quality of Service in the medical field especially for cardiovascular disease patients. Patients are monitored at health centers and county referral hospitals with some lacking the medical facilities to efficiently support the disease control mechanisms.

The need for a synchronized and centralized medical system that is able to collect patient data in real time and store and retrieve that data for analysis and processing and give an output using a variety of underlying technologies such as the IoT, and RFID ,is therefore inevitable. The IoT healthcare is based on a network of devices that directly connect with each other to capture and share vital data through an SSL connection to a server for storage.

The purpose of this project is to implement patient health status monitoring system based on IoT for effective and efficient monitoring of patients.

1. To implement the IoT sensor network framework

2. To develop patient data management system on IoT framework

3. To develop the Blynk mobile application and implement it to remotely monitor patient health status

4. To test and validate the developed Tele-health system

This project will be of great benefit to the cardiovascular-ill patients when successfully implemented. With this system, subscribers (patients) will be able to access reliable services as well as real-time and up to date information at guaranteed Quality of Service levels. In case of an emergency, the response time to save the patient will be reduced significantly owed to the always-on communication platform the proposed system will deliver. A live communication platform will be created to facilitate interaction on a one on one basis with physicians and specialists by a click of a button using an embedded application running under the VoIP framework. Cardiovascular disease patients will therefore have a longer lifespan, a much higher life expectancy and reduced cardiac mortality owing to the use of the health status tracking system.

This project investigates a non-communicable disease solution i.e. for hypertension. The main focus is on obtaining patient data via IoT devices such as sensors. This data is then processed and its findings delivered back to the subscribers (patients).

The aim is to encourage the effective use of IoT sensors to be programmed for patient data collection, analysis and representation as a way of improving QoS for subscribers and further ensure that it does not negatively affect a user’s QoE. Another project goal is to improve doctor-patient communication and revolutionize the medical service providence platform through effective remote health monitoring.

It is important to note that this study targets hypertensive patients and shall not substitute the role of specialists and physicians in the diagnosis for treatment of the illnesses. In the project, we will use the Ethernet cable to upload sensor findings for simulation of remote data transfer to the IoT cloud since the lack of an efficient WiMax platform for wide coverage of the sensor network is the limiting factor.

It is assumed that the network resources of internet connectivity, IoT devices and appropriate computer APIs will be sufficient for undertaking the project.

Our era has seen a surfeit of health challenges especially the non-communicable diseases. Hypertension and cancer among many other illnesses require timely medical services for treatment. Traditional methods of treatment at the clinic or hospital more often have fallen short of accomplishing success with respect to emergency cases (Alwan, 2010).

The need for a method to sense and analyze the risks prior to actual happening is the ultimate concern. Tele-health with IoT offers a vital solution to address such a serious issue. The rise in advents of sensors and actuators for use in various platforms has seen the revolution of the healthcare industry as a way of breaking traditional methods.

Of the many non-communicable disease illnesses, hypertension has become the major killer disease, a root cause of cardiac and stroke mortality. Hypertension is a condition where blood pressure in the arteries of the body is higher than 120/80 mmHg (more than 120 systolic and more than 80 diastolic). It is common in the elderly, though the young ones are affected nowadays. An important variable called the Heart Rate Variability (HRV) is an analysis tool for cardiovascular diseases. HRV measures the variation in time interval between consecutive heart beats. The proposed system aims of remote monitoring and alert in critical situation is based on HRV parameters and heart rate for hypertensive patients (Description of High Blood Pressure, 2015).

The Tele-health proposed system that is based on IoT shares results of sensor data through a web application. The data is in form of a graph and manipulated HRV data. A medical practitioner receives the data that is vital in following up a patient’s condition without a hospital visit. Currently, there are a number of standards used for sensor networks. Of the general standards, the reliable ones are IEEE 802.11 Wi-Fi and IEEE 802.15.4. Such a dynamic system requires that QoS and security features be taken care of. MQTT comes in handy. MQTT is a publish/subscribe messaging protocol for IoT crucial in remote monitoring systems. Another protocol, (Transport Layer Security) TLS ensures security of the data. TLS is a cryptographic protocol that ensures secure data transfer from remote patient to a Server/cloud at the doctor.

In many developing countries, locally, there are currently no remote RPM systems for hypertensive patients to help doctors and cardiologists track progression of patient’s condition. The proposed system aims to achieve QoS through reliability, low-cost, low-power, long-range and ease- to use for hypertensive patients (Description of High Blood Pressure, 2015).

This paper touches on related work on the RPM systems, the architectural design of the proposed model which gives a detailed approach of the system and the identified gaps in the system. The conclusion gives the end of the paper as well as its future scope.

An RPM system of ECG and Temperature signals was implemented using Bluetooth technology in (Luigi Atzori, Antonio Iera, Giacomo Morabito, 2010). It uses Arduino Uno board with ATmega328 microcontroller for data acquisition and Analog/Digital conversion. An integrated circuit INA 128P together with the ECG was used for filtering and amplification of the signals. Data transfer to a Mobile Phone or Personal computer was achieved through the Bluetooth technology. Captured data was stored in a database accessed by a web application deployed on the server.

Another ECG system was developed to monitor the old (P. J. Tello, O. Manjarres, M. Quijano and A. U. Blanco, 2014), a wireless 3-channel ECG transmission system. A Personal Digital Assistant (PDA) phone had been developed. The system consisted two ATMega328L microcontrollers, one with Zig bee transmitter and another with Zig bee receiver. The transmitter collected data and stored it in a Secure Digital (SD) card. The receiver sends collected data to a remote server. This would help control disease attacks by continuous monitoring

A system that serves as a sign monitor based on wireless sensor networks and Telemedicine has been developed to measure parameters such as Heart Rate, ECG and respiratory rate (P. J. Tello, O. Manjarres, M. Quijano and A. U. Blanco, 2014). It uses Bluetooth technology and sensors to transmit data to a smart phone. An application in the smart phone transfers data to a remote server through Wi-Fi for centralized monitoring. On the server end, a LAB View based application would do the analysis on the obtained patient data over an entire long period of monitoring.

A remote physiological parameters monitoring system has also been designed and developed. It comprises a heart rate sensor and temperature sensor to be worn by the patient. The patient is connected wirelessly to the computer. As long as data is pushed into the system, the device monitors and sets up an alarm through the connected computer in the home when parameters are found to be at risk level.

Some of the above healthcare systems have demerits in as much as QoS levels are concerned. As stated earlier, they fail to offer direct real time user experience in form of one on one communication with the medical doctors and cardiologists who can effectively monitor your health condition and link you to relevant treatment options wherever you are, whenever you want.

There is no simplified procedure to be followed in case of emergency in as far as response time to rescue a cardiovascular patient is concerned. As a result, the patient suffers severe health complications including death, trauma, etc. Indeed a patient needs to be up to date, informed with the necessary procedures and measures to take in case of an emergency e.g. the nearest recommended hospital, nearest emergency response team, etc.

In view of data collection, the data transfer process may encounter delays with regard to the type of sensor network protocol in use. Also the collected data via the mobile phone may be misinterpreted or incorrectly diagnosed by the patient since there is a poor or no direct communication link between the patient and the doctor.

Fig. 2.1 gives an overview of the proposed system architecture. Appendix B illustrates the data flow for the proposed system.

Fig.2.1: overview of proposed system

Arduino was born at the Ivrea Interaction Design Institute. It is an easy tool for fast prototyping, aimed at students without a background in electronics and programming. As soon as it reached a wider community, the Arduino board started changing to adapt to new needs and challenges, differentiating its offer from simple 8-bit boards to products for IoT applications, wearable, 3D printing, and embedded environments. All Arduino boards are completely open-source, empowering users to build them independently and eventually adapt them to their particular needs. The software, too, is open-source, and it is growing through the contributions of users worldwide.

i) Pulse sensor

The pulse sensor detects the heart beat by the method of Photoplethysmograph (PPG). PPG illuminates the skin optically to measure the pulse as a variation of resistance to blood flow in the skin. It is attached to the finger. A fluctuation in the analog values from the pulse sensors is recorded.When a heartbeat occurs blood is pumped through the human body and gets squeezed into the capillary tissues. The volume of these capillary tissues increases as a result of the heartbeat. But in between the heartbeats (the time between two consecutive heartbeats,) this volume inside capillary tissues decreases. This change in volume between the heartbeats affects the amount of light that will transmit through these tissues. This change is very small but we can measure it with the help of Arduino.

The pulse sensor module has a light which helps in measuring the pulse rate. When we place the finger on the pulse sensor, the light reflected will change based on the volume of blood inside the capillary blood vessels. During a heartbeat, the volume inside the capillary blood vessels will be high. This affects the reflection of light and the light reflected at the time of a heartbeat will be less compared to that of the time during which there is no heartbeat (during the period of time when there is no heartbeat or the time period in between heartbeats, the volume inside the capillary vessels will be lesser. This will lead higher reflection of light). This variation in light transmission and reflection can be obtained as a pulse from the output of pulse sensor. This pulse can be then conditioned to measure heartbeat and then programmed accordingly to read as heartbeat count

Fig. 3.2 shows a pulse sensor connected to the Arduino Uno.

Fig.2.2: a pulse sensor and Arduino Uno

ii) ECG sensor

The DFRobot Heart Rate Monitor v1.0 is a dedicated single lead heart rate monitor front end integrated circuit that records the electrical . The DFRobot Heart Rate Monitor is an integrated signal conditioning block for ECG and other bio potential measurement applications. It is designed to extract, amplify, and filter small bio potential signals in the presence of noisy conditions, such as those created by motion or remote electrode placement. This design allows for an ultralow power analog-to-digital converter (ADC) or an embedded microcontroller to acquire the output signal easily. The figure below shows an ECG sensor.

Fig. 2.3: the ECG sensor

The DHT11 detects water vapor by measuring the electrical resistance between two electrodes. The humidity sensing component is a moisture holding substrate with electrodes applied to the surface. When water vapor is absorbed by the substrate, ions are released by the substrate which increases the conductivity between the electrodes. The change in resistance between the two electrodes is proportional to the relative humidity. Higher relative humidity decreases the resistance between the electrodes, while lower relative humidity increases the resistance between the electrodes.

The DHT11 measures temperature with a surface mounted NTC temperature sensor (thermistor) built into the unit.2.4.2 Gateway Unit. Its role is to establish a secured communication channel for transmission of pulse data from pulse sensor module to the storage servers.

i)Arduino Uno

This is a microcontroller board embedded with ATmega328 microcontroller. The board is a platform with sensor and associated networks for their 14 Digital pins and 6 Analog pins on them. In the system, Arduino Uno board enabled with Internet through Ethernet Shield, is made to act as a gateway to the MQTT server from the Pulse sensor module. On the receiving end of the Arduino, Blynk set to act as coordinator shall receive data from pulse sensor module. Analog/Digital conversion is performed on the Arduino board. The data is formatted and is ready for transfer to the MQTT server.

ii) Ethernet shield

The Arduino Ethernet shield 2 allows an Arduino board to connect to the internet using the Ethernet library and to read and write an SD card using the SD library. The figure below shows an Ethernet shield.

Fig. 2.4: the Ethernet shield

It consists three servers, Blynk cloud server, Application server and Database server.

i) Blynk cloud

It is the most important part of MQTT communication. In the proposed system, a blynk server is used to which Arduino publishes the pulse sensor data. The Web application receives the data under a similar topic “/pulse”.

ii) Application Server

An application server called Websphere will host the Web application deployed. The web application will subscribe to the topic “/pulse” to retrieve the data from Blynk server and stores it in the MYSQL database. Based on the retrieved data, the human pulse wave is traced and represented in histogram to depict an abnormal variation at first sight about heart functioning.

iii) Database Server

MySQL database server is connected to the application end. The application queries the database every 5 seconds for plotting the histogram on incoming data. Each patient shall have their data stored in tables under their patient ID. This database will mainly store historic patient data.

Project: Implementing Patient Health Status Monitoring System based on IoT For Increasing Efficiency