IoT based Telemedicine system using Healthy pi

HealthyPi is the first fully open-source, full-featured vital sign monitor. Using the Raspberry Pi as it?s computing and display platform, the HealthyPi add-on HAT (hardware attached on top) turns the Raspberry Pi into a vital sign monitoring system.

Project Title

IoT based Telemedicine system using Healthy pi

Project Area of Specialization

Internet of Things

Project Summary

HealthyPi is the first fully open-source, full-featured vital sign monitor. Using the Raspberry Pi as it’s computing and display platform, the HealthyPi add-on HAT (hardware attached on top) turns the Raspberry Pi into a vital sign monitoring system.

Pakistan is a densely populated country where the healthcare facilities are not available especially for those living in remote areas. From the report of Survey of Pakistan, major population belongs to rural areas. Medical doctors prefer to work in urban areas due to living facilities and other fringe benefits. Even there are some areas where hospitals are available but medical staff is far from sufficient. This leads to a terrible situation. Moreover, People can't afford expensive transportation. The need of the hour is to have an online telemedicine system just like tele education system

Telemedicine is a concept that focuses on any medical action concerning a factor of distance. In which the interaction between doctors and clinic involve telecommunication technique.

For this sake we are making a model called Tele-Health kit that could be used by everyone from a lower class nurse to even patient himself/herself in their homes. Our model will almost take all necessary information that will be sent to a registered doctor through cloud system. Doctor in return would prescribe and prescription will be sent back to the patient via same central system. Meanwhile, this model will do the analysis itself using AI algorithms to check for abnormality. Moreover, it will propose a treatment itself for the type of abnormality.

We will be introducing Healthy pi circuit in telemedicine, a very user friendly android app and a website for this purpose which will also have a pop up call on action button in case of emergency for a doctor or an ambulance.  

Project Objectives

The main objectives of this project are;

• To make a user friendly model that could be used by everyone in their homes for health care purpose.
• To provide accurate detection and analysis of a patient’s ECG and other health parameters in real-time.
• To provide real-time monitoring of patient’s health activity in rural areas over a telecommunication infrastructure (IoT).
• To provide a reliable, cost-effective, practical and efficient way to diagnose ECG, pulse rate, blood pressure and temperature of the patient using AI and to prevent any future mishaps. 
• To analyse for normal, partial or critical condition and to display to the patient. 
• To provide quality of care and ease of access to the patients.
• To make possible the meeting between patient and doctor in a more better way without physical interact.

Project Implementation Method

Our project certainly have double work to do.

1. Take patients data to the doctor for analysis and his prescription back to the patient.
2. Meanwhile also do self analysis using AI algorithms and display patients health parameters with abnormalities. 

This project is based on the following components.

• Sensing System
• Visualizing Component
• Central System
• Cloud Computing
• Result
• Display

NOTE:  We will be using many sensors but for time being let's talk about ECG.

1) Sensing System: This component will be responsible for detecting and capturing ECG signals of the patient's heart. The sensing system consists of a low power, single lead, heart rate monitoring sensor designed to extract, amplify and filter ECG signals in the presence of noisy conditions such as those created by motion or remote electrode placement.

2) Visualizing Component: This component will be responsible for displaying the ECG recorded from the above-mentioned system.

3) Central System: This component will send the recorded ECG to the cloud for analysis and diagnosis through WIFI sensor. The central system is where all the sensors are connected including ECG sensor, WIFI sensor, LCD Display and camera etc.

4) Cloud Computing: The central system will send the ECG signals to cloud for analysis and diagnosis which have a machine learning model running in the back-end to classify whether the signal has any abnormalities or is a normal ECG signal, if the signal has any abnormality the model will be able to predict the type of abnormality based on the trained data and will propose treatment accordingly. The proposed model will be trained on the existing publicly available data of ECG recordings to separate the normal and abnormal signals.

5) Result: The output of Machine learning model will decide the result of the ECG recording. Once any abnormality is detected the model will then propose treatment according to the type of abnormality. There are total 37 different abnormal ECG types and each has its own treatment.

6) Display: Results along with the proposed treatment in case of abnormality will then be displayed on the LCD screen. 

The whole data will also be shared to a register doctor and the doctor will have an access to the cloud through email invitation.

Benefits of the Project

This project will provide a unique and user friendly device for diagnosing ECG and other essential signals and will serve as an assisting tool for doctors and nurses all over Pakistan. Moreover distance and travel time between the patients living in the rural areas and the care providers will be eliminated as the device is designed to monitor and diagnose the patient’s health activity over telecommunication infrastructure (IOT).

Presently people are in a state of lockdown and they can’t visit doctors physically. This model will have market throughout as Telemedicine is a concept that focuses on any medical action concerning a factor of distance.

This will also reduce cost, struggle, transportation and traffic in hospitals.

Technical Details of Final Deliverable

The final deliverables of this project will be the following sub modules:

1. Sensing System
2. Visualizing Component
3. Central System
4. Cloud Computing
5. Machine Learning Algorithm

1) Sensing System:  Sensing system contains an ECG, pulse rate, blood pressure and temperature modules that will monitor the person's health activity.

2) Visualizing Component: This component contains an LCD display attached to central system.

3) Central System: All the above mentioned systems will be integrated with the central system including WIFI sensor, LCD display and camera etc.

4) Cloud Computing: The acquired signals from the central system will then be sent to the cloud for diagnostic purposes. The cloud will have a machine learning model running in the background to classify these signals into normal or abnormal ones. Once classified, the results along with the proposed treatment will be shown on the visualizing component.

Machine Learning Algorithms :

Neural network (NN) finds role in variety of applications due to combined effect of feature extraction and classification availability in deep learning algorithms. Here convolutional Neural Network (CNN) and Recursive Neural Network (RNN) will be utilized to make the device smart enough to classify different ECG signals based on the input signals. 

CNN signal classifications takes an input signal, process it and classify it under certain categories (Eg., Normal, Abnormal). Computers sees an input signal as array of sampling points and it depends on the signal resolution.

The recurrent structure of RNN makes it capable of learning and making full use of the temporal information of the input signals to make up for the deficiencies of the short-term features

Deep learning CNN and RNN models will train and test, each input signal and pass it through a series of convolution layers with filters, Pooling, fully connected layers (FC) and apply different functions to classify the given signals.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Health

Other Industries

IT , Medical , Telecommunication

Core Technology

Internet of Things (IoT)

Other Technologies

Artificial Intelligence(AI), Cloud Infrastructure, Wearables and Implantables

Sustainable Development Goals

Good Health and Well-Being for People, Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com