Radar-based Human Pulse Sensing
| dc.contributor.author | Riad, Michael | |
| dc.date.accessioned | 2024-05-10T17:38:23Z | |
| dc.date.issued | 2024-05-10 | |
| dc.date.submitted | 2024-05-01 | |
| dc.description.abstract | This thesis presents a novel approach where a superstrate is used to re-purpose a commercial off-the-shelf mm-wave 60 GHz radar by Infineon (BGT60TR13C) for near-field human pulse sensing. The superstrate is realized through low-cost printed circuit board (PCB) technology. it consists of couplers, a microstrip line, and a transverse slot in the ground plane. The superstrate was designed using full-wave electromagnetics (EM) simulations, along with a numerical-based model to predict the output of the radar in the presence of the superstrate. The superstrate was fabricated, and the combined sensor was tested on human participants. The preliminary measurement results match the expected theoretical pulse waveform. Hence, proving the feasibility of the proposed approach in near-field pulse sensing applications. In comparison to the state-of-the-art pulse radar-based wearable sensors, the proposed sensor is more compact due to the superstrate protecting the radar from the detrimental effect of direct skin contact. Moreover, the sensing mechanism changed from capturing the phase changes for the range bin to monitoring the amplitude of the intermediate frequency (IF) spectrum peak. This was possible due to the enhanced signal-to-noise ratio (SNR). The measured pulse waveforms were compared to a commercial-grade electrocardiogram (ECG) from Frontier. There was an excellent agreement, particularly in the period and timing of the pulses. Therefore, the proposed sensor is feasible for heart rate monitoring and heart rate variability. Moreover, computer-aided-design-software (CAD)-generated digital twins have shown potential in generating datasets that could be fed to machine learning algorithms for detection and classification. This thesis demonstrates the feasibility of using the Shooting and Bouncing Ray method (SBR+) simulation to model pulse sensing using a commercial mm-wave radar. The time-domain reconstructed pulse waveforms had very good agreement with the input waveform, hence, this demonstrates the feasibility of using mm-wave radars for pulse sensing and the potential of using digital twins for generating diverse datasets to train radars on the signatures of various diseases and health conditions. | en |
| dc.identifier.uri | http://hdl.handle.net/10012/20555 | |
| dc.language.iso | en | en |
| dc.pending | false | |
| dc.publisher | University of Waterloo | en |
| dc.subject | PCB microwave sensors | en |
| dc.subject | Radar-based biosensor | en |
| dc.subject | vital-signs monitoring | en |
| dc.subject | wearable pulse sensors | en |
| dc.subject | Radar superstrate | en |
| dc.subject | Digital twin | en |
| dc.subject | SBR+ modelling | en |
| dc.title | Radar-based Human Pulse Sensing | en |
| dc.type | Master Thesis | en |
| uws-etd.degree | Master of Applied Science | en |
| uws-etd.degree.department | Electrical and Computer Engineering | en |
| uws-etd.degree.discipline | Electrical and Computer Engineering | en |
| uws-etd.degree.grantor | University of Waterloo | en |
| uws-etd.embargo | 2026-05-10T17:38:23Z | |
| uws-etd.embargo.terms | 2 years | en |
| uws.contributor.advisor | Shaker, George | |
| uws.contributor.advisor | Mansour, Raafat | |
| uws.contributor.affiliation1 | Faculty of Engineering | en |
| uws.peerReviewStatus | Unreviewed | en |
| uws.published.city | Waterloo | en |
| uws.published.country | Canada | en |
| uws.published.province | Ontario | en |
| uws.scholarLevel | Graduate | en |
| uws.typeOfResource | Text | en |
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