FALL 2009 EEC 290C GRADUATE SEMINAR

Prof. Stephen O'Driscoll

Friday November 6, Giedt Hall 1003, 12:10-1:00pm

Title

Implantable Medical Devices: The Power-Constrained Frontier

Abstract

Electronic devices for medicine are a rapidly growing area of technology. In-vivo monitoring and treatment of key biological parameters can greatly assist in managing health and preventing disease. However excess analog power consumption and insufficient power supply prohibit the widespread deployment of implantable medical devices (IMDs) for many applications.

Biological signal channels differ considerably from human-made communications channels, generating new design challenges for IMDs. Furthermore performance requirements of analog circuits for IMDs vary as a function of patient physique, health, device placement, patient activity etc, and thus cannot be known accurately prior to deployment. This talk presents a system-configured analog design approach to address these challenges and that approach is applied to signal acquisition and power delivery for neural sensors in motor prostheses.

An analog-to-digital converter (ADC) array which digitizes the neural signals sensed by an implanted microelectrode array is described. The resolution of each ADC cell is varied according to the neural data content of the signal from the corresponding electrode. Realized in 0.13µm CMOS the ADC achieves a figure of merit of 15fJ per conversion step.

A new method of wireless power transfer is developed for implanted devices which are constrained in size. First, the optimal frequency for wireless power transmission through tissue to area constrained receivers is derived. Second, an adaptive matching scheme which increases the robustness of the link gain to inevitable dielectric, range and alignment variations associated with an IMD is presented. Third, a low voltage rectifier is presented which reduces the voltage drop per stage to considerably less than a threshold voltage. The power receiver implemented in 0.13µm CMOS delivers 120µW at 1.2V DC to the IMD from a 2mm x 2mm on-board receive antenna, through 15mm of tissue.

I will outline some of the new projects in my BioElectronics Group at UC Davis including an implant positioning system (IPS), an ingestible rumen sensor, and neuro-stimulation devices - all of which will utilize adaptive analog circuits and mm-sized implantable power receivers.

Bio

Stephen O'Driscoll received the BE in Electrical Engineering from University College Cork, Ireland in 2001. In 1999 and 2000 he worked on microwave circuits for radar at Farran Technology, Ireland. From 2001 to 2003 he was at Cypress Semiconductor, San José, where he designed clock and data recovery phase locked loops. He received the MS degree in 2005 and the PhD degree earlier this year, both in Electrical Engineering Stanford University where he worked in Prof Teresa Meng's lab. He joined the faculty at UC Davis in August of this year where he is conducting research on analog and mixed-signal circuit design, with particular focus on biomedical devices.

Prof. Michael Gastpar

Friday October 30rd, Giedt Hall 1003, 12:10-1:00pm

Title

Computation and Communication - Two sides of one tapestry?

Abstract

Networks have been studied in depth for the past several decades, but one feature has received little attention until recently: Interference.

There is, of course, a good reason for this: In classical networks such as supply chains and the wired internet, interference can be addressed in a near-optimal fashion via simple protocols that avoid it.

However, in the networks of prime interest today, such as wireless ad hoc networks, interference is often the dominant bottleneck and simply avoiding it entails major performance penalties. Therefore, the next important step is a thorough understanding of the nature of interference.

In this talk, we argue that interference can be understood as computation: Multiple input signals are garbled together to produce a certain output. This is nothing but a certain computation performed on the input signals, possibly subject to noise or other stochastic effects.

We show how this perspective inspires novel paradigms for thinking about communication in networks, including cooperation, "wireless network coding," and interference management. In particular, the computational perspective may help resolve the nagging question concerning the nature of information in networks: We have argued earlier that the "bit", a universal currency of information in single noisy channels, is inappropriate in general networks. A more appropriate currency of information could result from computational primitives, retaining algebraic structure as a fundamental property of information.

Joint work with Bobak Nazer, and in part with Jiening Zhan.

Bio

Michael Gastpar (Ph.D. EPFL, 2002, M.S. UIUC, 1999, Dipl. El-Ing, ETH,1997) is currently an Associate Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He was a visiting professor (2008/09) at the Technical University of Delft, The Netherlands. He was also a student in electrical engineering and philosophy at the Universities of Edinburgh and Lausanne, and a summer researcher in the Mathematics of Communications Department at Bell Labs, Lucent Technologies. His research interests are in network information theory and related coding and signal processing techniques, with applications to sensor networks and neuroscience. He won the 2002 EPFL Best Thesis Award, an NSF CAREER award in 2004, and an Okawa Foundation Research Grant in 2008.

Kit S. Lam M.D., Ph.D.
Professor of Medicine, Chief, Division of Hematology & Oncology, University of California, Davis

Friday October 23rd, Giedt Hall 1003, 12:10-1:00pm

Title

From combinatorial chemistry to cancer targeting to nanotherapeutics

Abstract

The one-bead-one-compound (OBOC) combinatorial library technology [1] enables us to generate millions of compound-beads, each with unique chemical compound displayed on the bead surface. When mixed with live cancer cells, compound-beads that bind to cancer cell surface receptors are coated with a monolayer of cancer cells. These cell-bound beads are then isolated for structure analysis, through either direct Edman sequencing or via chemical decoding. With this approach, peptide leads that interact with a number of different cancer cells and normal cells were identified.

We have recently developed a number of amphiphilic polymers, comprised of a cluster of cholic acids (4 to 10) linked by a series of lysines and attached to one end of a linear polyethylene glycol chain (PEG, 2000-5000 Dalton). Under aqueous condition, such telodendrimers can self-assemble to form highly stable nanomicelles [2]. This nanoplatform is multifunctional and highly versatile. We can readily load hydrophobic drugs, radionuclides, fluorochromes, quantum dots, and iron nanoparticles into the hydrophobic core of these nanomicelles. We can also conjugate cancer-targeting peptides to the distal end of the telodendrimer such that these peptides will be displayed on the surface of the final drug-loaded nanoparticles. The size of the final nanocarriers (15-150 nm diameter) and their drug loading capacity are tunable depending on the size of the PEG chain and the number and arrangement of cholic acid molecules in the dendrimer. We have also compared the therapeutic efficacy and toxicity profile of our paclitaxel-loaded nanomicelles with the two FDA approved formulations of paclitaxel (Taxol® and Abraxane®) in nude mice bearing ovarian cancer xenograft, and determined that the nanomicelles had superior anti-tumor effects and toxicity profile. Nanomicelles smaller than 64nm preferentially targeted xenografts with high efficiency and with low liver and lung uptake, whereas those nanomicelles at 154nm targeted the tumor poorly but with very high liver and lung uptake. When decorated with cancer targeting ligands identified from the one-bead-one-compound (OBOC) combinatorial library methods the drug-loaded nanoparticles were rapidly taken up by the target tumor cells causing cell death. These ligands include LLP2A, LXY3 and LXW7 that target the a4b1, a3b1, and avb3 integrins, respectively. In vivo near infra-red optical imaging studies with hydrophobic fluorescent dye demonstrated that xenograft uptake of the nanomicelles was greatly enhanced by the cancer targeting peptide. Confocal microscopy revealed that the targeted nanomicelles, unlike the naked nanomicelles, were distributed throughout the entire tumor mass and not just in the perivascular space.

[1] Lam KS, Salmon SE, Hersh EM, Hruby V, Kazmierski WM, Knapp RJ: A new type of synthetic peptide library for identifying ligand-binding activity. Nature 354(7):82-84, 1991.

[2] Xiao K, Luo J, Fowler W, Li Y, Lee JS, Xing L, Cheng RH, Wang L and Lam KS. A self-assembling nanoparticle for paclitaxel delivery in ovarian cancer. Biomaterial. 30:6006-6016, 2009.

Bio

Dr. Kit Lam was born in Hong Kong, obtained his B.A. in Microbiology in 1975 at the University of Texas at Austin. He obtained his Ph.D. in Oncology in 1980 from McArdle Laboratory for Cancer Research, University of Wisconsin, and his M.D. in 1984 from Stanford University School of Medicine. He completed his Internal Medicine residency training and Medical Oncology Fellowship training at the University of Arizona. He is board certified in both Internal Medicine and Medical Oncology. He was on the faculty of the University of Arizona until June 1999, when he joined UC Davis School of Medicine as the Division Chief of Hematology/Oncology, a position he continues to hold today. He is both a practicing medical oncologist and a laboratory investigator.

Dr. Lam invented the "one-bead one-compound" (OBOC) combinatorial library method, which was first published in Nature in 1991. The article has since been cited over 1,100 times. He is a founding scientist of the Selectide Corporation, one of the first start-up companies to specialize in combinatorial chemistry. He has published over 238 scientific publications and is an inventor on 12 patents.

His research encompasses the development and applications of combinatorial chemistry to basic research and drug development. On-going projects in his laboratory include the development of novel encoding techniques and screening methods for OBOC combinatorial libraries, development of cancer cell surface targeting agents for cancer therapy and in vivo imaging, development of novel nanotherapeutics, identification of substrates and development of inhibitors for protein kinases, protein tyrosine sulfotransferases and proteases, applications of OBOC combinatorial library methods and chemical microarrays for cancer proteomics and enzyme profiling, development of novel glyco-markers for cancer diagnosis, development of imaging and therapeutic agents for Alzheimer’s disease, and development of antiviral agents.

Dr. Payam Pakzad
Qualcomm, Silicon Valley Research Center

Friday October 9nd, Giedt Hall 1003, 12:10-1:00pm

Title

On the Theory and Practice of Fountain Codes

Abstract

This talk will cover the basic concepts of fountain coding, including the theory and design of LT and Raptor codes. We will also give an overview of several related intuitions and results, including connection with the satisfiability and other problems in random graph theory.

Bio

Dr. Payam Pakzad is a staff engineer at Qualcomm's Silicon Valley Research Center. His research interests include error correcting codes, message passing algorithms, estimation and control theory and network coding, among others. Dr. Pakzad received B.S. degrees in Electrical Engineering and Applied Mathematics from Caltech in 1998, and a Ph.D. in Electrical Engineering from U.C. Berkeley in 2004. He was a post-doctoral research fellow at EPFL in Switzerland from 2004 up until 2006, when he joined Digital Fountain, Inc. as a senior researcher. He has been with Qualcomm Research since February 2009.

Professor Ali H. Sayed
Chair of Electrical Engineering
UCLA

Friday October 2nd, Giedt Hall 1003, 12:10-1:00pm

Title

Adaptive Networks

Abstract

Distributed networks linking sensors and actuators will form the backbone of future data communication and control networks. Applications will range from sensor networks to precision agriculture, environment monitoring, disaster relief management, smart spaces, target localization, as well as medical applications. In all these cases, the distribution of the nodes in the field yields spatial diversity, which should be exploited alongside the temporal dimension in order to enhance the robustness of the processing tasks and improve the probability of signal and event detection. Distributed processing techniques allow for the efficient extraction of temporal and spatial information from data collected at such distributed nodes by relying on local cooperation and data processing.

This talk describes recent developments in distributed processing over adaptive networks. The presentation covers adaptive algorithms that allow neighboring nodes to communicate with each other. At each node, estimates exchanged with neighboring nodes are fused and promptly fed into the local adaptation rules. In this way, an adaptive network is obtained where the structure as a whole is able to respond in real-time to the temporal and spatial variations in the statistical profile of the data. Different adaptation or learning rules at the nodes, allied with different cooperation protocols, give rise to adaptive networks of various complexities and potential. The ideas are illustrated by considering algorithms of the least-mean-squares type, although more general adaptation rules are also possible including least-squares rules and Kalman-type rules. Both incremental and diffusion collaboration strategies are considered.

Bio

Ali H. Sayed is Professor and Chairman of Electrical Engineering at UCLA where he directs the Adaptive Systems Laboratory (www.ee.ucla.edu/asl). He has published widely in the areas of adaptive filtering, estimation theory, and signal processing for communications with over 300 articles and 5 books. He is the author of the textbooks Fundamentals of Adaptive Filtering (Wiley, NJ, 2003), and Adaptive Filters (Wiley, NJ, 2008). He is a Fellow of IEEE and has served as Editor-in-Chief of the IEEE Transactions on Signal Processing(2003-2005) and the EURASIP J. Advances in Signal Processing (2006-2007). His research has received several recognitions including the 1996 IEEE D. G. Fink Prize, a 2002 Best Paper Award from the IEEE Signal Processing Society, the 2003 Kuwait Prize, the 2005 Terman Award, a 2005 Young Author Best Paper Award from the IEEE Signal Processing Society, and two Best Student Paper Awards at international meetings (1999,2001). He served as a Distinguished Lecturer of the IEEE Signal Processing Society during 2005. He has been a member of the Publications (2003-2005), Awards (2005), and Conference (2007-present) Boards of the IEEE Signal Processing Society. He served as General Chairman of ICASSP 2008, a member of the Board of Governors (2007-2008) of the IEEE Signal Processing Society, and is now serving as Vice-President (Publications) of the same society.