Device free breath rate detector

Project Title

Device free breath rate detector

Project Area of Specialization Information & Communication TechnologyProject Summary

Lungs diseases are one of the world’s major diseases that affect the populace in huge numbers. They occur in all societies, regardless of their level of hierarchy in society and age. Moreso the increasing pollution in the world is contributing generously to give rise to a huge number of respiratory diseases. We will provide a DFWS device in comparison to mounting devices and hopefully achieve a better result than existing devices. We will use ESP32 as the CSI tool which is will capture the state of the test object. We will be using the CSI (channel state information) from the Wi-Fi packets which are used for describing the state of the path from where the signal propagated towards the receiver. The CSI gives an extremely fine value from the physical environment that provides amplitude and phase on each subcarrier in the RF domain. ESP32 can be distinguished for its 52 subcarriers usage in CSI gathering. Using its subcarriers we will filter the signal from multipath propagation and will process those which come through the test subject. The breath rate will be estimated after applying the fresnel zone/PSD method, which uses big data analysis. The result is expected to be more than 90-98% accurate.

Project Objectives

We aim to early detect pneumonia to decrease the death rate that is caused by fluctuations in respiratory rate. Nowadays, pneumonia can only be detected when a machine is attached to the human body through wires. We are providing a new modern way to detect pneumonia wirelessly by using the Device-Free Wi-Fi sensing (DFWS) technique through which we can early detect the disease. We will use it on elderly people and infants to monitor their breath rate without any intrusion as it is non-intrusive in nature. It's cheap, portable, consumes less space moreover it’s a standalone device.

Project Implementation Method

1. The test subject shall be placed on a bed where the transmitter will be placed above the bed while the receiver will be placed below the bed. We will develop a Wi-Fi network among 5 sets of ESP-32 at different angles for deviations and error rectification as well as calibrations. The three raspberry pi 4s will be used as the host server of these esp32s for communication. Every raspberry pi 4 will use a different channel to prevent intervention in the signals.
2. We will acquire the packets from the transmitter and extract CSI information from the packets. The MAC address of the receiver will be selected while the rest will be rejected.
3. We will transmit the CSI information over to the PC for signal conditioning on MATLAB, where we will convert the complex CSI values to amplitude and phase and perform outlier rejection and subcarrier selection.
4. We will implement PSD/Fresnel zone method to achieve accurate results and plot them in real-time to measure breath rate.
5. We will implement the whole MATLAB processing over to Raspberry pi 4 using python to make it portable.

Benefits of the Project

• It is sensor-less as it uses only Wi-Fi signals instead of lasers and extensive and expensive equipment.
• It is Non-intrusive, replacing every wearable which is attached to the body.
• General setup could be used anywhere.
• Provides extremely accurate measurements when compared to cheap wearable gadgets.
• Specially designed for monitoring mentally ill people, elders, and infants.

Technical Details of Final Deliverable

• 3 Raspberry Pi 4s as a server host.
• 5 sets of ESP32 working as individual networks.
• TFT monitor display for visualizing breath rate.

Final Deliverable of the Project HW/SW integrated systemCore Industry HealthOther Industries Telecommunication Core Technology Big DataOther Technologies Internet of Things (IoT)Sustainable Development Goals Good Health and Well-Being for People, Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	79950
Raspberry Pi 4 4GB	Equipment	3	17000	51000
TFT monitor	Equipment	3	3000	9000
ESP32	Equipment	10	1000	10000
Fittings of Esp32s	Miscellaneous	10	800	8000
Raspberry Pi casing + holder	Miscellaneous	3	650	1950