Remote healthcare monitoring and data analysis of patients

The proposed remote healthcare monitoring system will be used to collect patient information, monitor the health of patients, diagnose diseases, and will generate alert messages in case of a medical emergency. The system will measure different health parameters of the human body such as temperature,

Project Title

Remote healthcare monitoring and data analysis of patients

Project Area of Specialization

Internet of Things

Project Summary

The proposed remote healthcare monitoring system will be used to collect patient information, monitor the health of patients, diagnose diseases, and will generate alert messages in case of a medical emergency. The system will measure different health parameters of the human body such as temperature, heart rate, ECG, EMG, accelerometer data, etc. These readings are then stored over a cloud platform where they can be used for real-time monitoring and diagnostic purposes by the caregivers. The doctors can also access the data from the cloud storage and can use this information for diagnosis.  Machine learning and cloud computing techniques are also integrated with the IoT platform for diagnostics.

Project Objectives

The project aims to achieve the following objectives:

• To provide real-time monitoring of user’s health condition
• To provide real-time remote access to data gathered by the sensors
• To generate alert messages and SOS calls in case of emergency (critical condition of the patient)
• To predict and diagnose user’s health symptoms

Project Implementation Method

The portable device makes use of 5 sensors: the temperature sensor (DS18B20), accelerometer (ADXL345), EMG, ECG, and pulse rate sensor. It continually records and measures the patient’s vitals with the help of these sensors. Using the unique identifier (UID) of the device, the network sends the data to a server connected to the internet. The communication technology used here is Wireless Fidelity (Wi-Fi) since it provides a higher transmission range (within 70ft.). Moreover, it is easily compatible with smartphones, making it ideal for use with mobile applications. The device also tracks the real-time location of the patient by making use of GPS technology. Once the data reaches the server, it can be accessed by all authorized users through a mobile-based application, provided that the patient allows them access. These may include doctors, the patient’s family, or any third-party services. The app generates alert messages in case of an emergency (critical condition of a patient). This is made possible by providing a threshold value for various vitals and ringing SOS calls when the values exceed that threshold. At the server, various ML algorithms are utilized to provide better decision-making facilities to the stakeholders. These include predicting future health conditions through currently available data, providing insightful prognoses, and aiding doctors in medical diagnosis.

Data Protection:

The protection of data of the users can be implemented using:

• Access Control

We can create different roles for different users and limit the accessibility of a patient’s data for the specified role. For instance, a doctor may only see those patient records that he has been in charge of (and given access to).

• User Agreement

If a patient visits a different doctor, he may only have access to the patient’s previous health records if the patient provides consent.

Data Security:

Since our system stores data on a remote server, we can make use of encryption technology to provide better data security.

We cannot use end-to-end encryption on our data for the following reason- In E2E encryption, records are encrypted at the end device. The user has a private key that decrypts data at the user’s end. However, our application requires original data from the server. It uses machine learning algorithms to predict the patient’s symptoms and diagnose diseases.

For storing a patient's health records, we can use record-level (application-level) encryption. Here, each individual record is encrypted with its own key. When feeding the data into an algorithm, we can successively decrypt individual records and make predictions (this adds additional computation cost). An alternative, less secure encryption would be to use database-level encryption.

Benefits of the Project

The project will have the following benefits:

• The project will ensure the well-being of its users through constant real-time monitoring of their health vitals.
• In case of a sudden heart stroke or other emergencies, the alert module will aware the user's caregivers, that the user is in critical condition.
• The mobile application module will show the health data in the form of interactive graphs which will enable the users to analyze and get insights from the measured health readings.
• The machine learning module of the project would allow the prediction and diagnosis of user's health symptoms.

Technical Details of Final Deliverable

The proposed project is expected to have the following outcomes:

• A full fledge mobile application where the user would be able to monitor and keep track of his/her daily health indicators
• An IoT-based solution for user health monitoring via the use of different medical sensors.
• A cloud-based alert system that would send SOS calls in form of emails or SMS service to the user’s selected contacts (family, relatives, etc.)

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Health

Other Industries

IT , Medical

Core Technology

Internet of Things (IoT)

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

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