2026-05-21T17:55:12Zhttps://keep.lib.asu.edu/oai/requestoai:keep.lib.asu.edu:node-2012442025-05-05T15:53:02Zoai_pmh:repo_items201244
https://hdl.handle.net/2286/R.2.N.201244
http://rightsstatements.org/vocab/InC/1.0/
All Rights Reserved
2025
2027-05-01T11:18:03
118 pages
Doctoral Dissertation
Academic theses
en
Lenz, Isabella S
Bliss, Daniel W
Berisha, Visar
Rong, Yu
Spanias, Andreas
Arizona State University
Partial requirement for: Ph.D., Arizona State University, 2025
Field of study: Electrical Engineering
The market for robust privacy-preserving biosensing technologies, driven by applications in healthcare, fitness, and human authentication, is expected to double in the next 10 years. Existing biosensors, however, face significant limitations in accuracy, comfort, and privacy.
In this dissertation, I study the potentials of radar as a versatile, non-contact, safe and privacy preserving biosensing modality. I specifically employ mmWave frequency- modulated continuous-wave (FMCW) radar and present two novel applications of FMCW radar for biosensing.
I first explore contactless heart sound monitoring using radar. Unlike traditional stethoscopes and accelerometers, which require physical contact and are susceptible to environmental noise, FMCW radar demonstrates high signal quality under various test conditions marking a significant step toward practical, non-invasive cardiac health monitoring.
I then present a radar-based human speaker authentication system. I collect a 98 human subject dataset of synchronous acoustic microphones signals and radar biosignals captured during speech. I then leverage the two synchronous signals and the unique physiology of human speech to build an algorithm that verifies the speech was generated by a human. This approach offers a robust solution to Artificial Intelligence (AI) generated voice clones.
Together, these contributions highlight the potential and facilitate the adaptation of radar as a next-generation biosensors.
Electrical Engineering
AI Detection
Human Authentication
Radar
sensing
Signal Processing
Privacy Preserving Bio-Sensing in High Stakes Domains