Session S11

Session S11: Biosensing II

Time:                 Wednesday, May 14, 10:30-12:00
Chair:                 Yitshak Zohar, University of Arizona
Co-Chair:           Jeffrey M. Sieracki, SR2 Group LLC

S11-1: Human Electrocortigraphic Signature Determination by eGAD Sparse Approximation
Jeffrey M. Sieracki SR2 Group LLC, College Park MD, Nathan E. Crone The Johns Hopkins University School of Medicine, Baltimore MD, and John J. Benedetto Norbert Wiener Center, University of Maryland, College Park MD
Estimated parametric Greedy Adaptive Discrimination (eGAD)is an algorithm for signal-ensemble component analysis based on simultaneous sparse approximation. It is robust against jitter as well as additive noise. We review the algorithm and its application in the context of comparing extracted parametric Gabor atom decompositions to uncorrelated baseline data. We briefly illustrate functionality on synthetic data, before demonstrating application in analysis of multi-channel human electrocortigraphic (ECoG) data. ECoG and muscle (EMG) recordings are analyzed with the goal of identifying characteristic activity patterns associated with simple motor tasks. eGAD compares well with results from previous short time Fourier transform (STFT) based studies, resolving more detail than previous methods where activity increases over baseline and allowing time-domain reconstruction of signature activity where it was not previously possible.

S11-2: Detection of Signal Discontinuities From Noisy Fourier Data
Adityavikram Viswanathan, Douglas Cochran, Anne Gelb and Dennis Cates Arizona State University, Tempe AZ
The concentration method for identifying the locations, magnitudes, and signs of jump discontinuities in analog signals from truncated Fourier series is well established in mathematical literature. Its performance in the presence of noise on the Fourier data has only recently started to receive attention, however. This paper examines the performance of the concentration method in the presence of noise from a detection-theoretic point of view. In particular, receiver operating characteristics for the elemental problem of detecting a unit step discontinuity are developed for this method. Additionally, the problem of optimally combining data obtained from multiple concentration factors is addressed.

S11-3: Low Power Bio-implantable Signal Acquisition and Processing Unit for Neural Recording
Mirembe Musisi-Nkambwe, Najad Anabtawi, Bahar Jalali Farahani and Antonia Papandreou-Suppappola Arizona State University, Tempe AZ
This paper presents a low power bio-implantable system-on-a-chip solution for reading and processing of signals from multiple neurons. Conventional Electroencephalography (EEG) uses hundreds of metal electrodes mounted on the patient’s head to collect the electrical activity of thousands of neurons. Wireless implantable EEG provides ease of movement and comfort for the patient and enables long term monitoring. In order to be competitive with conventional EEG, wireless bio-implantable EEG needs to collect and stream large amount of data outside the patient’s body. Power consumption as well as the required carrier frequency for the wireless transmission will be prohibitive. Using novel techniques in the design of the data acquisition and signal processing unit, power consumption can be reduced significantly compared to prior work.

S11-4: Capture of Breast Cancer Cells in a Microfluidic System
Luthur S. L. Cheung, Xiangjun Zheng, Ashley Stopa, Joyce Schroeder, Ronald L. Heimark, James C. Baygents, Roberto Guzman and Yitshak Zohar University of Arizona, Tucson AZ
Circulating tumor cells represent an alternative to invasive biopsies for cancer detection and characterization. Current techniques for isolating these cells are limited to complex analytic approaches with poor results. Here, selective binding of breast cancer cells to a biologically derivatized surface, utilizing a microfluidic system, has experimentally been studied under both static (no-flow) and dynamic (flow) conditions. Silicon-to-glass bonding is used to fabricate a microchannel device followed by immobilization of anti-E-cadherin molecules on the channel surface. This bio-active coating is indeed highly specific in capturing BT20 breast cancer cells. Furthermore, the number of capture cells increases almost linearly with incubation time within the first 15 min. The effect of flow velocity on capturing cancer cells has also been investigated.

S11-5: Use of Transfer of Entropy for Focus Localization in the Epileptic Brain
Shivkumar Sabesan, Konstantinos Tsakalis, Andreas Spanias Arizona State University, Tempe AZ, David Treiman Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix AZ and Leon Iasemidis Arizona State University
Transfer Entropy (TE) is a recently proposed measure of the information flow between coupled linear or nonlinear systems. In this study, we show the retrospective application of the improved TE method to long (in the order of days), continuous, intracranial electroencephalograms (EEG) recorded from 4 patients with focal temporal lobe epilepsy (TLE) for localization of their foci. All patients underwent successful ablative surgery of their clinically assessed foci. Based on statistical analysis of the TE results, it is shown that the identified potential focal sites through the suggested analysis were in agreement with the clinically assessed sites of the epileptogenic focus in all patients analyzed. It is noteworthy that the analysis was conducted on the whole available multi-electrode EEG, that is, without any subjective selection of EEG segments or electrodes for analysis. The above, in conjunction with the use of surrogate data, make the results of this analysis robust. These findings also suggest a critical role TE may play in epilepsy research in general, and as a tool for a robust localization of the epileptogenic focus/foci in patients with focal epilepsy in particular.