The University of Arizona

Events & News

ECE Colloquium

DateThursday, April 24, 2014
Time2:00 pm
LocationECE 530
SpeakerDr. Keshab K. Parhi
AffiliationDepartment of Electrical & Computer Engineering, University of Minnesota

Biomarkers & Brain Connectivity for Neurological & Psychiatric Disorders

Reverse engineering the brain has been identified as one of the grand challenge problems by the National Academies. Advances in sensor technologies and imaging modalities such as (scalp) electroencephalogram (EEG), intra-cranial electroencephalogram (iEEG), magnetoencephalogram (MEG), and magnetic resonance imaging (MRI) allow us to collect data from hundreds of electrodes from the brain at sample rates ranging from 256 Hz to 15kHz. These data can be key to not only understanding brain functioning and brain connectivity at macro and micro levels in healthy subjects but also in identifying patients with neurological and mental disorders. Extracting the appropriate biomarkers using spectral-temporal-spatial signal processing approaches and classifying states using machine learning approaches can assist clinicians in predicting and detecting seizures in epileptic patients, and in identifying patients with mental disorder such as schizophrenia, depression and personality disorder. The biomarkers can be tracked to design personalized therapy and effectiveness of therapy by closed loop drug delivery or closed loop neuromodulation, i.e., brain stimulation either by invasive or non-invasive means using electrical or magnetic stimulation. I will describe approaches that combine signal processing and machine learning to extract biomarkers for epilepsy, schizophrenia and borderline personality disorder. I will also describe how connectivity from EEG, MEG and functional and structural MRI can be used as biomarkers. I will present some results on VLSI design of feature extractors such as power spectral density (PSD) and classifiers such as support vector machines (SVMs).


Keshab K. Parhi received the B.Tech. degree from the Indian Institute of Technology (IIT), Kharagpur, in 1982, the M.S.E.E. degree from the University of Pennsylvania, Philadelphia, in 1984, and the Ph.D. degree from the University of California, Berkeley, in 1988. He has been with the University of Minnesota, Minneapolis, since 1988, where he is currently Distinguished McKnight University Professor and Edgar F. Johnson Professor in the Department of Electrical and Computer Engineering. He has published over 500 papers, has authored the textbook VLSI Digital Signal Processing Systems (Wiley, 1999) and coedited the reference book Digital Signal Processing for Multimedia Systems (Marcel Dekker, 1999). Dr. Parhi is widely recognized for his work on high-level transformations of iterative data-flow computations and for developing a formal theory of computing for design of digital signal processing systems. His current research addresses VLSI architecture design and implementation of signal processing, communications and biomedical systems, error control coders and cryptography architectures, high-speed transceivers, stochastic computing, secure computing, and molecular computing. He is also currently working on intelligent classification of biomedical signals and images, for applications such as seizure prediction and detection, schizophrenia classification, biomarkers for mental disorder, brain connectivity, and diabetic retinopathy screening. Dr. Parhi is the recipient of numerous awards including the 2012 Charles A. Desoer Technical Achievement award from the IEEE Circuits and Systems Society, the 2004 F. E. Terman award from the American Society of Engineering Education, the 2003 IEEE Kiyo Tomiyasu Technical Field Award, the 2001 IEEE W. R. G. Baker prize paper award, and a Golden Jubilee medal from the IEEE Circuits and Systems Society in 2000. He was elected a Fellow of IEEE in 1996. He served as the Editor-in-Chief of the IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS —PART I (2004-2005 term), as technical program cochair of the 1995 IEEE VLSI Signal Processing workshop and the 1996 ASAP conference, and as the general chair of the 2002 IEEE Workshop on Signal Processing Systems. He was a distinguished lecturer for the IEEE Circuits and Systems society during 1996-1998. He served as an elected member of the Board of Governors of the IEEE Circuits and Systems society from 2005 to 2007.