Farrokh Ayazi

Farrokh Ayazi is the Ken Byers Professor in Microsystems in the School of Electrical and Computer Engineering at the Georgia Institute of Technology, Atlanta, GA, USA. He received the B.S. degree from the University of Tehran, Iran, in 1994, and the M.S. and Ph.D. degrees from the University of Michigan, Ann Arbor, in 1997 and 2000, respectively, all in electrical engineering. His main research interest lies in the area of integrated Micro/Nano-Electro-Mechanical-Systems (MEMS and NEMS), with a focus on high-Q acoustic resonators and advanced inertial sensors. Dr. Ayazi was the co-founder and CTO of Qualtré, a spin-out of his research laboratory that commercialized bulk acoustic wave silicon gyroscopes for high precision applications, which was acquired by Panasonic in 2016. He is currently leading StethX Microsystems in commercializing advanced wearable sensors for cardiopulmonary applications. Dr. Ayazi is a fellow of the IEEE, has authored over 300 refereed technical and scientific articles, and holds more than 60 patents. He was the general chair of the IEEE Micro-Electro-Mechanical-Systems conference in 2014, held in San Francisco, CA.

Hermetically-Sealed Acoustic Contact Microphones for Wearable Cardio-Pulmonary Devices

StethX is aiming to develop an easy-to-use low-profile wearable device for accurate detection and quantification of respiratory abnormalities and adventitious lung sounds through prolonged measurement of mechano-acoustic signals from multiple auscultation locations, without relying on the listening skills of a physician. In this talk, I will present hermetically-sealed uni-directional acoustic contact microphones and their applications for monitoring cardiopulmonary signals. The platform combines SOI-MEMS with nano-gap transducers interfaced with CMOS ASIC to create robust low-power precision accelerometer contact microphones (ACM) with wide bandwidth and high dynamic range. Using a multi-degree-of-freedom ACM on a single-chip, one can comprehensively measure heart and lung sounds, respiratory rate as well as body motion of a subject simultaneously. This can allow the physicians to remotely diagnose and track patients’ health post-treatment, while capturing body motion coupled with the auscultation data to help them correlate cardiopulmonary sounds to daily activities.