Candidate: Aaron Propp
Date: August 3, 2023
Time: 1:00pm
Location: remote attendance
Supervisor(s): Sebastian Fischmeister
You are invited by the Department of Electrical and Computer Engineering and the IEEE Electronics Packaging Society (EPS) Student Chapter at University of Waterloo to attend a distinguished lecture:
Speaker: Professor John A. Rogers, McCormick School of Engineering, Northwestern University
Date: September 13, 2023
Time: 12:00pm
Location: E7-7303/7363
Candidate: Serene Abu-Sardanah
Date: August 1, 2023
Time: 4:00pm
Location: EIT 3142
Supervisors: Omar Ramahi, George Shaker
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.
Name: Zhiping Cai
Date: Monday April 3rd 2023
Time: 3:00pm - 4:00pm (EST)
Location: EIT 3145
Supervisor: Prof. Werner Dietl
Attending faculty members: Prof. Arie Gurfinkel, and Prof. Mahesh Tripunitara
Title: UniFlow: A CFG-based Framework for Pluggable Type Checking andType Inference
Abstract:
Name: Huixin Jin
Date: Thursday 23rd of March 2023
Time: 4:00pm to 5:00pm (EST)
Location: E5-4047
Supervisor: Slim Boumaiza
Attending faculty member: Prof. Raafat Mansour
Title: Millimeter-wave 39 GHz 4x4 Phased Antenna Array with Embedded Near-field Probing Antenna for Performance Enhancement
Abstract:
Name: Sheikh Nooruddin
Date: Wednesday, March 22nd 2023
Time: 10AM - 11AM
Location: online
Supervisor(s): Fakhri Karray, Ali Elkamel, Mark Crowley
Title: On the Design of Efficient Deep Learning Methods for Human Activity Recognition in Resource Constrained Devices
Abstract:
Name: Youssef Fathi
Date: Thursday 23rd of March 2023
Time: 9:00 am : 10:00 am (EST)
Location: online
Supervisor: Prof. Fakhri Karray
Title: Scene Representations for Generalizable Novel View Synthesis
Abstract:
Title: Biocompatible Piezoelectric Materials and Composites for Biomedical Applications
Speaker: Professor Xudong Wang
Date: Monday March 13, 2023
Time: 02:30pm
Location: EIT 3142
Abstract
Title: Multimedia Quality-of-Experience: Progress in Research and Industry Applications
Speaker: Dr. Zhou Wang
Date: Friday March 24, 2023
Time: 01:00pm
Location: EIT 3142
Alumni, students, employers, industry partners, media, and members of the general public are invited to join us in Engineering 7 for the Electrical and Computer Engineering Capstone Design event