 Welcome back all. Let's start with the next group, the General Health Monitor Project. Mentored by Mr. Chetan Jaiswal, Ms. Deepthi Ghusalkar, Mr. Harshvardhan K, Ms. Kirti Ambre, Mr. Padmaka Reddy and Mr. Varun Matkaikar. Managed by Mr. Rajesh Kushalkar. The major objective of GHM is that it can be used for personal health monitoring without any need of going to a doctor. The team is here, so let's start with the presentation. Hello everyone, I'm Sanjana and I'm representing the General Health Monitor Group. My team members are Poonam, Jagruti, Purva, Ashish, Diganta and Sameer. We would like to thank our mentors and Rajesh sir for providing constant support throughout the course of this project. Here are some quick facts. More than 235 million people suffer from asthma. More than 40% of the adults above the age of 25 suffer from high blood pressure and over 30% of the people are enemic. Lastly, more than 600,000 people die annually due to heart diseases. Hence there's a need to develop a health monitoring system which will help in early diagnosis and early treatment of these diseases. Here are some currently available health and fitness devices. The first one is the Angel Sensor. It monitors heart rate, temperature and blood oxygen. The next one is the Samsung Gear Fit. It monitors blood glucose, blood pressure and sleep. The third one is the Jawbone Up which measures movement, sleep and food. The goal of our project was to develop this health monitoring system which would measure certain vital body parameters and to display this health data on an Android app and store this into the server database for future reference of the doctor and the patient. So our system consists of three parts. The first one is hardware, the second one is the Android app and the third one is the web app. So when the appropriate tab is clicked on the Android app, the data from the sensors is displayed on the Android app and stored in the local database of the SQI database. And when the internet connection becomes available, it is pushed onto the server and stored permanently in the server database. And this data can be viewed by the doctor and the patient using the web app. So the vital body parameters we were able to implement in our system were the peak flow, blood pressure, temperature, oxygen saturation level and ECG. So the peak flow is the maximum speed of person's expiration. So like I said earlier, more than 235 million people across the world suffer from asthma. And during an asthma attack, the person's windpipe swells up and there's a drop in peak flow. Hence it's a very important vital body parameter. So the sensor we used was the liquid flow sensor. It consists of a rotor with magnets and a hall effect sensor. So when the air is blown into this liquid flow sensor, the rotor rotates and there's a change in magnetic field. And due to this change in magnetic field, the hall effect sensor generates pulses. And the peak flow can be measured by counting the number of pulses generated. The normal range for the peak flow is 400 to 600 litres per minute, the blood pressure. Blood pressure is the pressure of the blood in the circulatory system. More than 40% of the people above the age of 25 suffer from hypertension. So again, this is a vital body parameter. The sensor we used was the SunROM Technologies Blood Pressure Sensor. It sends digital values for systolic pressure, diastolic pressure and heart rate. Next piece. So as we all know, the most common ailment is fever. And for a lot of the other diseases, the first symptoms is a fever. So it's again a vital body parameter. The sensor we used was LM35. So it gives an output voltage which is proportional to the Celsius temperature. The normal body temperature is 37 degree Celsius. So the oxygen saturation level. So oxygen saturation level is the concentration of oxygen in the blood. The sensor we used for our purpose was a SPO2 Sensor Probe. It is supposed to be worn around the finger and it emits lights of two different wavelengths. The red light and the IR light. And it works on the principle of transmittance. So when the red light and the IR light are emitted, the transmitted light is absorbed by the photodiode and is converted to current. So the oxygen saturation level can be calculated as concentration of oxygenated hemoglobin divided by total concentration of hemoglobin in the blood. Next piece. So ECG is the recording of the electrical activity of the heart. Like I said, more than 600,000 people across the world die annually due to heart diseases. The sensor we used for ECG calculation was ECG clamps. Now the signal that we get from ECG clamps is very weak and gets mixed up with noise by the time we actually get to measure it. So we need a signal conditioning circuit which will filter and amplify these signals. So as we can see, this is the signal we got after filtering and amplifying the ECG signals. So all these sensors were interfaced with a microcontroller. And the microcontroller we used was STM32F303. It is a high-performance microcontroller that operates at the frequency of 72 MHz. So sensors were interfaced with microcontroller. Now microcontroller is interfaced with an Android app. And now Purva will talk more about the Android app. Thank you, Sanjana. I will be explaining the Android part. We have developed an Android app called as Droid. So we have used Android because it is most widely used operating system and it is open source. We have used SQLite for saving the data. It is because it is easy to access it, it is fast and it is simple. Next please. If the user has registered himself, he can directly use the login. And if he has not registered, he has two ways. If net is available, he can register himself and then login. Or else we have a guest login. In guest login, the data won't be saved, it would just be displayed. So here is the login screen in which he can enter his user ID, password and login. Once the user clicks on the tab, such as temperature tab, the sensors will send the data and it will be displayed on the Android app. So the value will be displayed at the center. It will be surrounded by a circle which indicates his status like normal, caution or emergency. The green circle indicates it is normal and it is also displayed at below. The eye signifies, like when you click on it, you get a pop-up in which all the reference ranges are given. We have a blood pressure tab in which the systolic, diastolic and the pulse rate are shown. Along with this also we have status and the reference ranges. This is for peak flow. In peak flow we have a button called a start and stop. Once you start, you can blow in and all the values will be recorded. The highest value will be chosen as the peak flow and it will be saved in the escalate. So this is for pulse oxy. Here you will see the ring has become orange because the value is in the caution range. Here also we have the reference range and all. This is for ECG. In ECG, we are showing the live data using a graph along with the status. Along with ECG, we also show the heart rate of the person. For the registered user, we have a special tab called as profile tab in which we show all these details. If internet is available, the person can also edit his profile and save it. There is a button called as messages. If net is available, once the user clicks on the message button, all the messages sent by the doctor will be displayed here. The person can also change his password using the Android app. We have the help button in which all the details are given like how to use this app and we have a logout button in order to come out. After this, Samir will explain the web application. Thank you. I will be explaining about the user interface of the web application. In the web application, there are three types of user. First is admin, second is doctor, third is patient. Coming to admin, this is the welcome screen for admin. Here he can see his profile information. Here he can also edit his profile, change his password. At the top we can see different tabs that are for different features. When he will click on doctor tab, a search box will appear. He can search that particular doctor according to his first name, last name, city or state. A list of matching searches will appear and he can click on that particular patient and the profile information will be visible. He can see the profile information. Similar action can be done for searching a doctor also by clicking on doctor tab. When he will click on request tab, all the requests from the doctor will be shown. These requests are generated when the doctor is registering himself on the system. He can click on that request and see the profile of that doctor and he can accept or reject that particular doctor. Coming to doctor, this is the welcome screen for doctor. All the profile information is shown here. He can edit his profile and change his password. When he will click on patient tab, all the patient that under his supervision will be listed here. He can pick any one of the patient and the profile information of that patient will come here. There are several options related to that particular patient that is shown on the left side. Next, when he will choose view health option, this screen will appear. This screen is showing all the health parameters of that particular patient. Initially, we are giving data for last month but using that date picker, he can give any date and go back and see the data. Suppose a particular date is having more than one session. Suppose the patient has taken more than one value in that particular date. He can click on that particular point and can see all the data of that particular date. Next, this is the graph for body temperature. This is for peak flow. Next, this is for pulse oxy and this is for electrocardiogram. Next, we have incorporated additional features such as doctor can send messages to the doctor about his health, precaution and prescription. He can also refer that particular patient to another doctor by choosing refer doctor option. Next, when he will click on the request tab, all the request from the patient will be seen here. He can view all the profile information and can accept or reject that particular patient. He can also refer that particular patient without accepting the request to the different doctor. Next, now coming to patient. This is the welcome screen for patient. All the profile information will be shown here. Next, when he will click on view health tab, he can also see his health parameters in a similar way that a doctor can see. Next, when he will click on doctors, all the doctor data supervising him will be shown here. He can also add a new doctor from this search tab and can add a new doctor. Next, these are the messages from the doctor. Have you implemented patient software different from doctor software? Yeah. Why the patient is not implemented as a doctor with a single patient himself? So that I don't have to recode whole bunch of software. Sir, there are different features for doctor and patient. So, we have used different modules. That's okay. What feature for doctor is different from patient? So, he can... So, why can't the patient, any individual be his own patient? So, he can see his thing. Why I have to write different software? Both of them are seeing only data except that doctor has got a full list. This fellow has got only one. That is written in a similar way but the view is different. That is coming in patient. Why I am not using the same code? Somebody talked to me about reusability and I told him my software is always reusable. We have same software. Same software. Yes? No, it's not same software. It's very difficult to write a software where a person is his own doctor. That you are not written, please. That we have not... Correct. If the doctor wants to see monitor his... Okay, go ahead. Telling you how to think. When he will click on message tab, all the message from the doctor will come here and the system generated message such as doctor has accepted your request or doctor has removed you will also be here. Now, Degantha will tell about challenges. Thank you, Sameer. The challenges that we face in this project. First challenge we face when interfacing the Android device with the STM32. We had two options, USB and Bluetooth. But we chose Bluetooth because we intend to make this sensor into a wearable device. It's for ease of access and use. Next, we had this... By measuring ECG and pulse-oxy signals, as you all know these signals are very faint signals in the body. It was difficult to extract the signal. And you know, we had lots of noise also because we were implementing these signals as well as the circuit in bread bowl. So, it was difficult to extract the signal and get accurate results. Next, please. What did we learn? First of all, being a part of integrated development lab group, we learned about hardware and software implementing those in the same project. In the hardware part, we learned about the new mic control STM32 programming it and interfacing with the sensors. In the software part, we learned about communication between the server and the application that we developed with application and applications. Next, please. For future scope, we are thinking about making this integrated sensors into one wearable device and we can add more health parameters like blood glucose levels, cholesterol levels and tracking the sleep pattern. Also, we can add more features in the Android app. Like, presently, we have just displayed the status. We can also add health tips according to the status. Like, suppose in emergency, what you can do, if it's caution, what you can do. And also, since we are logging the data, we can analyze the data. I'll predict what disease it can have but he might tend to. Next, please. In conclusion, I'd like to say that we have successfully implemented blood pressure, peak flow and boy temperature. ECG and pulse oxy needs more work because we need to implement it in the PCB. Next, please. These are the references and next, please. Let's move to demo video or live demo. This is Android UI. This is UI for web application.