서울대학교 의과대학 의료빅데이터연구센터에서 캘리포니아주립대학교 김영욱 교수를 초청해 세미나를 개최하오니 많은 관심과 참여를 부탁드립니다. 감사합니다.
○ 일시: 2021.7.29.(목) 오전 11-12시
○ 강연자: Youngwook Kim, Professor, California State University, Fresno
○ 주제: Application of Electromagnetics for Analyzing Human Motions Using Machine Learning Algorithms
○ Zoom 회의 ID: 891 6688 5973
○ 초록: This presentation discusses the applications of electromagnetics for analyzing human motion using machine learning algorithms. Radar has been employed for defense purposes for several decades, but recently, it offers a new opportunity for application to human subjects. Human motion detection has been an important research area for a wide variety of applications, including health care, human computer interface, and surveillance. This presentation covers three main topics. Firstly, it addresses human detection and monitoring problems using radio frequency sensors. To process the sensor data, machine learning algorithms, such as the support vector machine and deep convolutional neural network (DCNN), are suggested to detect humans and analyze their activities. Data augmentation using the generative adversarial networks (GANs) is also discussed. Secondly, applications to the human body for health care (on-body biometrics) are discussed. Sensing vial signals and extracting characteristics of the human body are unique and significant areas of applied electromagnetics. The movement of body parts, such as limbs, heart, eyelids, and fingers, can be readily measured by Doppler sensors. By investigating micro-Dopplers from human parts, useful information can be induced, including estimation of total energy expenditure, heart rate detection, eye-blinking detection, and hand gesture recognition. This technology offers the potential to remotely monitor human health and could be applied to health care systems, such as telemedicine and e-health. Finally, this presentation briefly discusses applications of on-body channels and antenna sensors to address human monitoring problems. Through on-body channels and antenna impedance variations, which can be readily used by hand-held devices, human activities from large motions to fine movements are analyzed using DCNN.
○ 강연자 소개: Youngwook Kim received his BS degree in Electrical Engineering at Seoul National University, Korea, in 2003. He received an M.S. and Ph.D. degree in Electrical and Computer Engineering at the University of Texas at Austin, USA in 2005 and 2008 respectively. He joined California State University at Fresno in 2008 and was early promoted to professor in 2018. He also teaches at the School of Engineering at the University of California at Merced as a visiting professor. His research interests are in the area of radar signal processing, antenna design and RF electronics. His primary topic of research lies in radar signal processing with machine learning algorithms. In particular, his expertise is the human motion analysis using an array of Deep learning algorithms. Other topics of interest include wireless power transfer, development of fast algorithms for broadband antenna design, and equivalent-circuit modeling of broadband antennas. He is a recipient of the Provost's award in research excellence, Claude Laval Jr. Award, the LCOE outstanding research award, the Provost's New Faculty Award from the California State University, the A.D. Hutchison fellowship from the University of Texas at Austin, and the National IT Fellowship from the Ministry of Information and Communication, Korea. He figured among the World's Top 2% Scientists' List compiled by Stanford University. He has published more than 90 technical papers and holds three patents.