Members: Nir Sandel, , Razi Rubanovsky

Supervisor: Anat Arzi

"This project aims to develop a novel and accurate method for detecting consciousness in patients with brain injuries, addressing the limitations of current methods. Inspired by recent studies, we propose a system that integrates respiratory monitoring with brain activity analysis to improve detection accuracy. Our approach utilizes SAFAM, a device that measures respiratory patterns, and EEG, which records brain activity. These devices are controlled and synchronized via an Android application, with data analysis conducted using Matlab. The key components of our project include:

• SAFAM: Measures breathing patterns.
• EEG: Records brain activity.
• Android App: Controls the testing process and synchronizes data.
• Arduino: Facilitates the integration and communication between devices.
• Data Analysis Software: Processes and analyzes the collected data.

The core of our testing involves an active breathing test, where patients follow specific breathing commands. The synchronization between SAFAM and EEG ensures precise data collection, enabling detailed analysis of the correlation between respiratory and brain activity. Our main challenge is ensuring accurate synchronization while maintaining the system's mobility and user comfort. We plan to conduct multiple tests on healthy controls and patients from different hospitals to validate the reliability and accuracy of our system. By enhancing the detection of consciousness, this project aims to significantly improve patient care and recovery predictions."