A Battery-Less Wireless Respiratory Sensor Using Micro-Machined Thin-Film Piezoelectric Resonators

• Published in: Micromachines (Basel) Vol. 12; no. 4; p. 363
• Main Authors: Moradian, Sina, Akhkandi, Parvin, Huang, Junyi, Gong, Xun, Abdolvand, Reza
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 27.03.2021; MDPI
• Subjects: Antennas; Design; Fast Fourier transformations; Frequency ranges; MEMS; Microelectromechanical systems; Micromachining; Moisture content; Monitoring systems; Patients; piezoelectric; Piezoelectricity; Receivers & amplifiers; Resonance; Resonators; Respiration; respiratory; RFID; Sanitation; Sensors; wearable; wireless; wearable; RF MEMS; RFID; MEMS; wireless; respiratory; piezoelectric
• ISSN: 2072-666X; 2072-666X
• DOI: 10.3390/mi12040363

In this work, we present a battery-less wireless Micro-Electro-Mechanical (MEMS)-based respiration sensor capable of measuring the respiration profile of a human subject from up to 2 m distance from the transceiver unit for a mean excitation power of 80 µW and a measured SNR of 124.8 dB at 0.5 m measurement distance. The sensor with a footprint of ~10 cm2 is designed to be inexpensive, maximize user mobility, and cater to applications where disposability is desirable to minimize the sanitation burden. The sensing system is composed of a custom UHF RFID antenna, a low-loss piezoelectric MEMS resonator with two modes within the frequency range of interest, and a base transceiver unit. The difference in temperature and moisture content of inhaled and exhaled air modulates the resonance frequency of the MEMS resonator which in turn is used to monitor respiration. To detect changes in the resonance frequency of the MEMS devices, the sensor is excited by a pulsed sinusoidal signal received through an external antenna directly coupled to the device. The signal reflected from the device through the antenna is then analyzed via Fast Fourier Transform (FFT) to extract and monitor the resonance frequency of the resonator. By tracking the resonance frequency over time, the respiration profile of a patient is tracked. A compensation method for the removal of motion-induced artifacts and drift is proposed and implemented using the difference in the resonance frequency of two resonance modes of the same resonator.