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Name: Omer Elghalhoud

Date: Dec 5, 2022

Time: 1:00pm

Location: EIT 3141

Supervisors: Sagar, Naik

Title: Data Balancing and Hyper-parameter Optimization for Machine Learning Algorithms for Secure IoT Networks

Abstract: 

Name: Nova Alam

Venue:  Zoom https://uwaterloo.zoom.us/j/98494013736?pwd=L3JWN0cybEo2ck1XNkZuLytHaEVaQT09

Date: Friday, Dec. 16, 2022 

Time: 2 pm

Supervisor: Prof. Alfred Yu

Title: Pressure Wave Velocity Using High-Frame-Rate Ultrasound Imaging for Urodynamic Study 

Tuesday, August 1, 2023 4:00 pm - 5:30 pm EDT (GMT -04:00)

MASc Seminar: Cardio-respiratory Health Monitoring Using a Wearable Radar System

Candidate: Serene Abu-Sardanah

Date: August 1, 2023

Time: 4:00pm

Location: EIT 3142

Supervisors: Omar Ramahi, George Shaker

Abstract: 

Cardiac and pulmonary health play a crucial role in overall well-being, as cardiovascular and respiratory diseases continue to pose significant global health challenges. However, traditional monitoring methods like ECG and spirometry have limitations, driving the need for alternative approaches. We introduce a wearable chest-worn radar system operating at 60 GHz, enabling contactless and near-field monitoring of cardio-respiratory activity. By capturing detailed displacement waveforms associated with chest movement during respiration and the cardiac cycle, the radar system provides continuous and accurate extraction of vital signs including respiratory rate (RR), heart rate (HR), and heart rate variability (HRV). To ensure effective performance in close proximity to the skin, electromagnetic simulations were conducted to assess the radar system's capabilities. Subsequently, experiments using the chest-worn radar prototype successfully extracted detailed cardiac and respiratory waveforms. The system effectively differentiated between different breathing types (labored, shallow) and detected apnea. Furthermore, functional waveforms for cardiac activity were mapped against a reference electrocardiogram (ECG), establishing a physiological basis for radar signal measurements during the cardiac cycle. This radar-based monitoring approach exhibits promising potential for accurate and continuous assessment of cardio-respiratory health. It offers advantages over traditional methods, including simplicity, continuous monitoring, and improved patient comfort.