Radar Near-Field Sensing For Biomedical Applications
| dc.contributor.author | Bagheri, Omid | |
| dc.date.accessioned | 2025-06-16T17:58:18Z | |
| dc.date.available | 2025-06-16T17:58:18Z | |
| dc.date.issued | 2025-06-16 | |
| dc.date.submitted | 2025-06-09 | |
| dc.description.abstract | Biomedical sensing technologies are essential for real-time health monitoring and disease management. Among their applications, blood glucose monitoring is of particular importance due to the global prevalence of diabetes that demands early detection and continuous management. Although clinically approved invasive methods exist, they are often inconvenient and unsuitable for continuous monitoring. Despite extensive research, non-invasive glucose monitoring, whether through wearables or smartwatches, remains an unsolved challenge, with no commercially or clinically validated solutions available. Radar-based biomedical sensing offers a promising non-invasive, continuous monitoring approach with tissue penetration capabilities. However, challenges such as suboptimal antenna design, near-field limitations, air-skin impedance mismatch, and poor depth resolution persist. A key objective in improving radar sensing performance is to maximize the transmitted power density from the radar's transmit (TX) antenna into the target medium while simultaneously enhancing the reflected power received by the receive (RX) antenna. This dual enhancement significantly improves the radar’s signal-to-noise ratio (SNR). Integrating advanced lenses and metasurfaces addresses these limitations, enabling efficient, practical deployment without major redesigns. This research introduces the development and implementation of novel radar-based methodologies tailored for biomedical sensing applications. Through innovative system design, advanced signal processing, and rigorous experimental validation, the proposed solutions address key challenges in on-body sensing. The first contribution focuses on advanced lens designs, such as dielectric rod arrays and modified gradient-index (GRIN) Luneburg lenses, aimed at enhancing radar-based external health monitoring at 10 GHz. The second contribution advances metasurface technologies for internal biomarker monitoring, enabling compact, skin-contact wearable systems with enhanced sensitivity and spatial resolution, with a specific emphasis on non-invasive blood glucose detection. Operating in the 58–63 GHz millimeter-wave band, the proposed metasurface-enhanced radar system integrates the BGT60TR13C sensor from Infineon Technologies with a planar, phase-synthesized metasurface for near-field focusing within the skin dermis layer, achieving over 11-fold improvement in SNR by enhancing both transmitted and reflected power. Four progressively objectives are presented, each expanding upon the foundation of the previous stage: single-band, single-focus metasurface, a preliminary design serving as proof of concept; metasurface-enhanced multi-radar fusion for distributed sensing; dual-band, dual-focus metasurface for depth-selective monitoring; and a multi-band, multi-focus non-interleaved metasurface for combined spatial and depth resolution. These innovations have the potential to revolutionize non-invasive, continuous health monitoring. | |
| dc.identifier.uri | https://hdl.handle.net/10012/21863 | |
| dc.language.iso | en | |
| dc.pending | false | |
| dc.publisher | University of Waterloo | en |
| dc.subject | radar | |
| dc.subject | biomedical | |
| dc.subject | antenna | |
| dc.subject | lens | |
| dc.subject | metasurface | |
| dc.subject | glucose monitoring | |
| dc.subject | near-field radiation | |
| dc.subject | TECHNOLOGY::Information technology::Signal processing | |
| dc.subject | electromagnetics | |
| dc.subject | wearable devices | |
| dc.subject | MEDICINE::Social medicine::Public health medicine research areas::Public health science | |
| dc.subject | FORESTRY, AGRICULTURAL SCIENCES and LANDSCAPE PLANNING::Area technology::Remote sensing | |
| dc.subject | fusion sensing | |
| dc.subject | healthcare monitoring | |
| dc.title | Radar Near-Field Sensing For Biomedical Applications | |
| dc.type | Doctoral Thesis | |
| uws-etd.degree | Doctor of Philosophy | |
| uws-etd.degree.department | Electrical and Computer Engineering | |
| uws-etd.degree.discipline | Electrical and Computer Engineering | |
| uws-etd.degree.grantor | University of Waterloo | en |
| uws-etd.embargo.terms | 0 | |
| uws.contributor.advisor | Shaker, George | |
| uws.contributor.advisor | Ramahi, Omar | |
| uws.contributor.affiliation1 | Faculty of Engineering | |
| 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 |