SENSITIVE AND NOISE-ROBUST WIRELESS BIOSENSORS BASED ON EXCEPTIONAL POINTS

Abstract

Wireless biosensors to track human physiological signals during daily life are important for disease diagnosis and personalized healthcare. Effective interrogation of wearable or implantable biosensors in noisy environment during daily activities, however, are limited by conventional wireless sensing schemes. This thesis proposes sensitive and noise-robust wireless biosensors based on exceptional points (EPs) for wireless and continuous physiological monitoring. In the first study, wireless implantable biosensors based on EPs show amplified responses benefiting from abrupt phase transitions near the EPs, but these sensors suffer from high intrinsic noise near the EPs. Two distinct wireless sensing schemes are further proposed to suppress noise based on bistable mode switching and turn detrimental noise into a beneficial role through stochastic resonance. We also demonstrate the utilities of EP-based wearable biosensors for increasing the fidelity of continuous respiration monitoring during exercise. These results could lead to the new design of noise-robust wireless devices for ambulatory monitoring of physiological states during daily life.