Wearable biosensor technology is one of the enabling technologies for digital/connected healthcare as it can enhance the efficiency and convenience of patient monitoring in many ways. This talk introduces the recent achievements in wearable biosensors for unobtrusive long-term health monitoring systems. Firstly, the speaker will discuss a novel approach for continuous cuffless blood pressure sensing technology. The novel sensor measures the speed of blood flow; then extracts the blood pressure from the flow speed using short range Doppler radar technology in concert with a machine learning algorithm. The prototype system was designed with a custom-built electronics and a 4-compartment phantom mimicking the human wrist. Preliminary experimental results show the measured speed of fluid flow ranging from 5 to 60 cm/s. Secondly, the speaker will introduce a multimodal analog front-end (AFE) IC that enables integration of multiple bio-sensors in wearable and attachable sensor systems. The AFE IC supports the most frequently used bio-sensors such as electrocardiogram (ECG), photoplethysmogram (PPG), and bio-impedance with a power consumption of less than 2 mW for all aforementioned sensing modalities. Lastly, the speaker will share ideas for future directions of bio-sensors in the digital healthcare domain.

Dr. Insoo Kim received his B.S. and the M.S. degrees in electrical engineering from Korea University, Seoul, Korea, and the Ph.D. degree in electrical engineering from The Pennsylvania State University, University Park, PA. He was with The Center for Neural Engineering at the Pennsylvania State University as a post-doctoral research associate from 2009 to 2012. He is currently Lead Research Engineer at Samsung Research America, Richardson, Texas, where he led various research projects encompassing the development and validation of mobile healthcare sensor technologies, brain computer interface, and medical imaging methods. He is passionate about developing innovative technologies to sense/process physiological signals for therapeutic/assistive and chronic disease management devices. He is a co-author of more than 40 peer-reviewed technical papers and (co-)inventor of 6 U.S. patent applications in the areas of VLSI circuits and systems, biomedical imaging systems, and wearable sensors. He is a member of the Technical Committee on Wearable Biomedical Sensors and Systems (WBSS) of the IEEE Engineering in Medicine and Biology Society (EMBS).

According to the World Health Organization, around one billion people worldwide are affected by neurological disorders, ranging from Parkinson's Disease to peripheral neuropathy. Conclusive diagnosis of many of these disorders can only be made through tests requiring use of large, expensive, time-consuming, and uncomfortable tools, which cannot be operated outside the clinic. Therefore in many cases, patients are diagnosed and receive treatment only after they visit the clinic when symptoms occur. An increasingly popular treatment option for many neurological disorders, such as sensory losses and mental problems, is electrical neuromodulation. Despite the collaborative research efforts of engineers and clinicians towards improving clinical outcomes from neuromodulation treatment, engineering challenges remain; designing energy-efficient and unobtrusive systems achieving closed-loop operation and improved-selectivity of stimulation pathways must still be tackled. This talk will focus on creating a new class of wearable and implantable sensing and neuromodulation systems that could be used by minimally-trained users in uncontrolled settings, thereby potentially enabling timely diagnosis and effective management of neurological disorders. The talk will emphasize robust, energy-efficient circuits as well as systems design approaches to address the engineering challenges of building such high-performance and smart systems and researching their translation into clinical use.

Hakan Töreyin received the B.S. degree in electrical and electronics engineering from Middle East Technical University, Ankara, Turkey, and the M.S. and the Ph.D. degrees in electrical and computer engineering from Georgia Institute of Technology, Atlanta in 2007, 2008, and 2014, respectively. Dr. Töreyin is currently a postdoctoral researcher in the School of Electrical and Computer Engineering at Georgia Institute of Technology. In 2007-2008 he was a Fulbright Fellow and in 2012 he was awarded the Chih Foundation Research Award. At the IEEE EMBC 2014 Student Paper Competition, he was recognized as the North America Finalist and awarded the third prize. Dr. Töreyin's research interests include energy-efficient circuits and systems design for wearable and prosthetic biomedical applications.

In the cancer surgery, the complete resection of cancers is the single most essential predictor of the prognosis of patient. However, even in US, local recurrence rate at 5 years approaches 40% following tumor resection, due to the failure of completely removing cancerous tissues. Surgeons rely on presurgical imaging, intraoperative visualization/palpation, and experience to optimize tumor removal. I developed a biomedical instrument system for intraoperative cancer identification: 1) a portable visible/near-infrared (VIS/NIR) camera system, to help the surgeons to visualize the cancer location; 2) a hand-held spectroscopic device, together with indocyanine green (ICG) as imaging contrast agent, for quantitative analysis of tissue properties; 3) a set of miniaturized devices, for cancer diagnosis in the minimally invasive surgery. The intensity of fluorescence on tissues helps to distinguish cancers, normal tissues, positive and negative margins, in less than 1 sec. Clinical trials with my biomedical instruments were conducted on human patients, primarily with pancreatic cancers and breast cancers; high sensitivity (94.8%) and specificity (95.0%) of diagnosis were achieved. The quantitative spectral analysis reveals that the majority (>95%) of the NIR fluorescence comes from the fluorescence of imaging contrast agents, other than tissue autofluorescence. Detailed spectral features, e. g. peak positions and widths, helps to differentiate tissue types that the camera imaging systems cannot distinguish. Fundamental study indicates that this spectral difference originates from the different ICG fluorescence under various environments.

Dr. Jian Xu received a B.S. and a M.S. degree in Physics at Nanjing University, China; he received the M.S., M.Phil., Ph.D. degrees in Electrical Engineering at Yale University. Now he conducts interdisciplinary research on biomedical instrumentation for image-guided cancer surgery in the department of biomedical engineering at Emory University and Georgia Tech. He designs and optimizes medical camera systems to facilitate the visualization of cancer locations and spectroscopic devices to help surgeons to distinguish cancerous tissues from normal tissues intraoperatively. His medical devices have been put into clinical trials in several major hospitals, including Emory University Hospital and Saint Joseph's Hospital at Atlanta. His device demonstrates high diagnosis accuracy (94.9%) on pancreatic cancer (the most deadly cancer) and breast cancer (the most common female cancer). His work is the core part of an ongoing TR01 funding (“Contrast-enhanced and Image-guided Surgery”) from NIH.

Wireless nodes in the same network often have link gains with different coherence time or coherence bandwidth due to differences in mobility and local scattering. The coherence time and its effect on acquiring channel state information (CSI) will become ever more important because 5G wireless communication is expected to move into the millimeter wave bands, where Doppler spread is larger compared with previous generations of cellular wireless, therefore the issues of training and CSI acquisition will become more acute. In this talk, a newly discovered diversity phenomenon will be discussed that has a direct impact on the problem mentioned above. Diversity is a well-known principle that leverages differences in channel gains at different times, spatial locations, or different users, to harness gains in wireless communication. Coherence diversity is a new mechanism in the downlink that leverages the disparity between the coherence time or coherence bandwidth of different nodes in a wireless network to arrive at significant gains. In order to harness coherence diversity, a method called product superposition is presented whose main feature is to allow the signal of one user to disappear into the equivalent channel for another user, thus removing interference in one direction. The application of product superposition is demonstrated in two-user channels with disparity in coherence time (slow and fast users), in coherence frequency, or both. Time permitting, extensions to multi-user scenario will be discussed.

Aria Nosratinia is Erik Jonsson Distinguished Professor and associate head of the electrical engineering department at the University of Texas at Dallas. He received his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign in 1996. He has held visiting appointments at Princeton University, Rice University, and UCLA. His interests lie in the broad area of information theory and signal processing, with applications in communication theory and wireless communications. Dr. Nosratinia is a fellow of IEEE for contributions to multimedia and wireless communications. He is area editor for the IEEE Transactions on Wireless Communications. He has been an editor for the IEEE Transactions on Information Theory, IEEE Transactions on Image Processing, IEEE Signal Processing Letters, IEEE Wireless Communications (Magazine), and Journal of Circuits, Systems, and Computers. He has received the National Science Foundation career award, and the outstanding service award from the IEEE Signal Processing Society, Dallas Chapter. He has served as the secretary of the IEEE information theory society, treasurer for ISIT, publications chair for the IEEE Signal Processing Workshop, as well as member of the technical committee for numerous conferences. Dr. Nosratinia is a registered professional engineer in the state of Texas.

For individuals with a motor skill disorder, repetition of recommended therapy exercises is essential for motor improvement. Moreover, external feedback of performance is an important component of therapy such that individuals can correct their exercises and improve their performance. However, direct feedback is typically only provided by an expert therapist during weekly or monthly therapy sessions, which limits improvement on a daily basis. In order to promote the repetition of recommended exercises in a home setting, several serious games have been developed to promote compliance with therapy interventions. To advance this work, we have developed a novel framework to couple serious games with a robot playmate that provides various feedback during interaction. The playmate continuously tracks the user's kinematic performance and autonomously provides objective verbal and nonverbal cues in order to increase the efficacy of the intervention. To determine how various instruction, motivation, and correction cues affect an individual's kinematic performance, we have tested the complete system with 59 able-bodied adults. We conclude that the developed system is able to provide a combination of feedback (motivation, instruction, correction) throughout the therapy session that enabled 100% of individuals to reach their performance goals.

Dr. Brown is a recent (Dec. 2015) graduate of Georgia Institute of Technology in Atlanta, GA where she received her Ph.D. in Electrical Engineering with a focus in Robotics. Dr. Brown also received her Master's in Electrical Engineering from Georgia Tech in 2012 and her Bachelor's in Electronics Engineering from Norfolk State University in Norfolk, VA in 2010. While at Georgia Tech, Dr. Brown was the recipient of the NSF Graduate Research Fellowship, the Presidential Fellowship, and the Texas Instrument Fellowship. Her research has been published in the proceedings of IEEE International Conference of Systems, Man, and Cybernetics, IEEE Integrated STEM Education Conference, IEEE-RAS International Conference on Humanoid Robots, IEEE Symposium on Robot and Human Interactive Communication, and the ASEE Annual Conference. As a product of her work, Dr. Brown has received two best paper awards and a paper invitation to the ASEE Computers in Education Journal. Dr. Brown currently resides in Atlanta, GA where she is assisting Emory University in their Alzheimer's Disease Research Center as a research scientist.

Optimal mass transportation map from a Riemannian manifold to itself transforms one probability measure to the other in the most economical way, the transportation cost is the so-called Wasserstein distance between the two measures. Wasserstein distance is a Riemannian metric in the space of all probability measures on the Riemannian manifold. Finding the optimal mass transportation map is equivalent to solve the Monge-Ampere equation, which has intrinsic relations with Minkowski and Alexandrov problems in convex geometry. In this talk, we introduce a variational approach to solve the optimal mass transportation problem, which gives a constructive proof for the classical Alexdrov theorem and leads to a practical algorithm. We also cover some direct applications of optimal mass transportation, such as surface and volume measure-preserving parameterization, and shape classification based on Wasserstein distance and so on.

David Gu got his bachelor degree from Tsinghua University and his Ph.D. from Harvard University in 2003, supervised by a Fields medalist Prof. S-T Yau. He is an associated professor in the Computer Science department and an adjunct in the Applied Mathematics Science department in SUNY at Stony Brook. His research focuses on developing discrete geometric theories and apply them in engineering and medicine fields. He is one of the major founders of an emerging inter-disciplinary field—Computational Conformal Geometry. Recently, he won Morning Side Gold Medal in Applied Mathematics in 2013.