ICSIP 2018 Invited Speakers
Prof. Wei-Lun Lin, Feng Chia
Speech Title: A Unified Orthogonally Multiplexed Modulation System for SDR Implementation
Abstract°™Orthogonal time-multiplexed modulation (OTMM) is proposed as several new single-carrier modulation families originated from the orthogonal multiplexed modulation (OMM) families to provide low peak-to-average power ratio and versatile modulations with different degrees in power and bandwidth efficiencies. To further facilitate a software de?ned radio (SDR) implementation, the proposed OTMM families are incorporated into the original OMM family in a unified signal structure. Typical basis sets are also unified to suit an SDR implementation. The resulting structure supports both time multiplexing and frequency multiplexing, and therefore offers greater flexibility in improving the power and bandwidth ef?ciencies of the LTE system. The proposed structure thus attends throughput and signal robustness simultaneously in hostile environments and also provides versatile choices in modulations with low peak-to-average power ratio.
Biography: Dr. Lin received the Ph.D. degree in electrical engineering from National Central University, Taiwan, in 2008. From 2008 to 2011, he was with National Taiwan University as a postdoc. From 2011 to 2012, he joined Institute for Information Industry, Taiwan, where he developed matlab simulations for 4G LTE systems. He is currently with the Department of Communications Engineering, Feng Chia University, Taiwan, from 2012. Dr. Lin's research interests are in digital modulation theory and wireless communication systems.
Prof. Yannick Benezeth, University
Bourgogne Franche-Comte, France
Speech Title: Emotional State Monitoring Using Camera-Based Heart Rate Variability
Abstract°™In recent years, various modalities have been used to recognize emotions. Among all these modalities, physiological signals are especially interesting because they are mainly controlled by the autonomic nervous system. It has been shown for example that there is an undeniable relationship between emotional state and Heart Rate Variability (HRV). We present a methodology to monitor emotional state from physiological signals acquired remotely. The method is based on a remote photoplethysmography (rPPG) algorithm that estimates remote Heart Rate Variability (rHRV) using a simple camera. We first show that the rHRV signal can be estimated with a high accuracy. Then, frequency features of rHRV are calculated and we show that there is a strong correlation between the rHRV features and different emotional states.
Biography: Yannick Benezeth is associate professor at Univ. Bourgogne Franche-Comt®¶ (France). He obtained his PhD in computer science from the University of Orl®¶ans in 2009. He also received the engineer degree from the ENSI de Bourges and the MS degree from the University of Versailles-Saint-Quentin-en-Yvelines in 2006. His research interests include biomedical engineering, image processing and video analytics. He has published 15 international journals and more than 30 international conferences since 2009. His paper has been cited more than 1500 times according to Google Scholar.