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Annual Northeast Bioengineering Conference

作者： Gary Comtois John I. Salisbury Ying Sun Biomedical Engineering Program Department of Electrical Computer and Biomedical Engineering University of Rhode Island Kingston RI USA

The prevalence of smartphone devices lends itself to a development platform for an array of applications, including patient health tracking and physiological monitoring. This paper shows a preliminary investigation of the acquiring and processing breathing signals using a smartphone running the Android Operating System. The hardware consists of a smartphone connected to an analog electronic stethoscope. The preliminary signal analysis tool includes the Fast Fourier Transform implemented with the Android Software Development Kit (SDK).

关键词： biomedical monitoring Androids Humanoid robots Stethoscope Java Libraries Smart phones

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Force clamp and electrical stimulation on decapod appendages

Force clamp and electrical stimulation on decapod appendages

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Annual Northeast Bioengineering Conference

作者： Aleksey Gladkov Micheal Fagbote Robert Hill Ying Sun Biomedical Engineering Program Department of Electrical Computer and Biomedical Engineering University of Rhode Island Kingston RI USA

The musculature of the decapods allows for a wide variety of motion given the limited degrees of freedom of motion granted. This study focuses on a single degree of motion of a single leg segment of the crab (Menippe mercenaria) in response to electrical stimulation. A microprocessor was programmed to trigger an electrical stimulator and to provide force and length controls of the induced contraction. Digital feedback control algorithms were implemented on the microprocessor in conjunction with the Aurora Dual Mode Lever System to provide force clamp, length clamp, as well as other loading conditions. The resulting experiment setting provides a useful platform for studying the mechanics of muscle contractions.

关键词： Force Clamps Microprocessors electrical stimulation Muscles Neurons Heart

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Membrane design of vibration transducer to drive round window to increase vibration displacement

Membrane design of vibration transducer to drive round windo...

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IEEE-EMBS International Conference on biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on biomedical and Health engineering

作者： Lee, Jang Woo Lim, Hyung Gyu Jung, Eui Sung Seong, Ki Woong Lee, Jyung Hyun Kim, Jee Hyun Kim, Myoung Nam Cho, Jin Ho Graduate School of Electrical Engineering and Computer Science Kyungpook National University Daegu 702-701 Korea Republic of Institute of Biomedical Engineering Research Kyungpook National University Daegu 700-422 Korea Republic of Department of Biomedical Engineering Kyungpook National University Hospital Daegu 700-721 Korea Republic of Department of Biomedical Engineering School of Medicine Kyungpook National University Daegu 700-721 Korea Republic of School of Electronics Engineering College of IT Engineering Kyungpook National University 700-422 Korea Republic of

ISBN: (纸本)9781457721779

Many kinds of hearing aids have been developed to overcome hearing loss. Each hearing aid has their own method to improve hearing threshold level of the patient. In case of vibration transducer to drive round window, a part of implantable hearing aid, uses the vibration displacement to compensate the hearing level. However, the vibration displacement is limited by membrane size made of metal, when it has been fixed dimensions. In this paper, several form of vibration transducer membrane to drive round window to increase vibration displacement has been proposed. It is calculated using finite element analysis. It is confirmed the vibration displacement can be higher in limited size. © 2012 IEEE.

关键词： Hearing aids

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The method of masticatory movement noise reduction using the dual channel implantable microphone

The method of masticatory movement noise reduction using the...

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IET International Conference on Information Science and Control engineering 2012, ICISCE 2012

作者： Woo, S.T. Kim, D.W. Lee, S.B. Park, J.H. Seong, K.W. Lee, J.H. Cho, J.H. Graduate School of Electrical Engineering and Computer Science Kyungpook National University Korea Republic of School of Electricity New and Renewable Energy Yeungjin College Korea Republic of Department of Biomedical Engineering Kyungpook National University Hospital Korea Republic of School of Electronics Engineering College of IT Engineering Kyungpook National University Korea Republic of

ISBN: (纸本)9781849196413

The input part of fully implantable hearing devices (FIHDs) was using the implantable microphone that was implanted under the skin of the temporal bone. So, implantable microphonès characteristics can be affected by the masticatory movement and moving artifacts. In this paper, the 2-channel implantable microphone was designed for masticatory movement noise reduction. For in vivo experiment, the fabricated microphone was implanted in the rabbit. And then, the 1 kHz pure-tone sound by a speaker was applied to the rabbit, and the feeds were given simultaneously to the rabbit. The measured signal was processed using the adaptive filter with least mean square (LMS) algorithm for noise reduction. To confirm performance of proposed method, the correlation coefficient and signal to noise ratio (SNR) before and after the signal processing were calculated.

关键词： Adaptive filters

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Configurable clutter models for radar simulation

Configurable clutter models for radar simulation

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International Waveform Diversity and Design Conference

作者： Joseph A. Jezak Guy Gadola Charles Berdanier Steven P. Levitan Donald M. Chiarulli Computer Engineering Graduate Program University of Pittsburgh Department of Electrical Engineering Wright State University Department of Electrical and Computer Engineering University of Pittsburgh Department of Computer Science University of Pittsburgh

In this paper we describe an extension to the MATLAB Phased Array Toolkit that adds a configurable clutter object to model clutter signals returned along a specified signal path. The clutter model is based on the Simkins Unified Clutter Model[1]. The current implementation supports sea clutter in any of five sea states with configurable polarization, grazing angle, and beam width. We describe the implementation and give examples of modeled clutter returns.

关键词： Clutter Object oriented modeling Mathematical model Reflectivity Radar Computational modeling Arrays

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rTMS as a Treatment of Alzheimer's Disease with and without Comorbidity of Depression: A Review

Neuroscience journal

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Neuroscience journal 2013年第1期2013卷 679389页

作者： Grant Rutherford Rebecca Gole Zahra Moussavi Department of Electrical and Computer Engineering University of Manitoba Winnipeg MB Canada R3T 5V6 Graduate Program in Biomedical Engineering Faculty of Engineering University of Manitoba Winnipeg MB Canada R3T 5V6. Department of Electrical and Computer Engineering University of Manitoba Winnipeg MB Canada R3T 5V6. Graduate Program in Biomedical Engineering Faculty of Engineering University of Manitoba Winnipeg MB Canada R3T 5V6 Riverview Health Center 1 Morley Avenue Winnipeg MB Canada R3L 2P4.

With an ever-increasing population of Alzheimer's disease (AD) patients worldwide, a noninvasive treatment for AD is needed. In this paper, the application of repetitive transcranial magnetic stimulus (rTMS) as a treatment for patients with probable AD is compared to the application of rTMS as a treatment for depression. Comorbidity of depression and dementia is discussed, as well as possible links between the two diseases. The possible confounding antidepressant effects of rTMS on cognitive improvements in AD patients are discussed.

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Finding optimal random boolean networks for reservoir computing

Finding optimal random boolean networks for reservoir comput...

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13th International Conference on the Simulation and Synthesis of Living Systems: Artificial Life 13, ALIFE 2012

作者： Snyder, David Goudarzi, Alireza Teuscher, Christof Department of Computer Science Portland State University Portland OR 97201 United States Systems Science Graduate Program Portland State University Portland OR 97201 United States Department of Electrical and Computer Engineering Portland State University Portland OR 97201 United States

ISBN: (纸本)9780262310505

Reservoir Computing (RC) is a computational model in which a trained readout layer interprets the dynamics of a component called a reservoir that is excited by external input stimuli. The reservoir is often constructed using homogeneous neural networks in which a neuron's in-degree distributions as well as its functions are uniform. RC lends itself to computing with physical and biological systems. However, most such systems are not homogeneous. In this paper, we use Random Boolean Networks (RBN) to build the reservoir. We explore the computational capabilities of such a RC device using the temporal parity task and the temporal density classification. We study the sufficient dynamics of RBNs using kernel quality and generalization rank measures. We verify findings by Lizier et al. (2008) that the critical connectivity of RBNs optimizes the balance between the high memory capacity of RBNs with (K) 2. We show that in a RBN-based RC system, the optimal connectivity for the parity task, a processing intensive task, and the density classification task, a memory intensive task, agree with Lizier et al.'s theoretical results. Our findings may contribute to the development of optimal selfassembled nanoelectronic computer architectures and biologically-inspired computing paradigms. © 2012 Massachusetts Institute of Technology.

关键词： computer architecture

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A method to validate quantitative high-frequency power Doppler ultrasound with fluorescence in vivo video microscopy

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Proceedings of Meetings on Acoustics 2013年第1期19卷

作者： James Lacefield Stephen Z. Pinter Dae-Ro Kim M. N. Hague Ann F. Chambers Ian C. MacDonald Electrical & Computer Engineering and Medical Biophysics Western University Thompson Engineering Bldg Rm 279 London Ontario N6A 5B9 Canada Biomedical Engineering Graduate Program Western University London Ontario Canada Medical Biophysics Western University London Ontario Canada London Regional Cancer Program London Ontario Canada

Flow quantification with high-frequency power Doppler ultrasound can be performed using the wall-filter selection curve (WFSC) method [M. Elfarnawany et al., Ultrasound Med. Biol. 38, 1429-1439 (2012)]. The WFSC method plots color pixel density (CPD) as a function of wall filter cut-off velocity as a means of objectively selecting an operating point cut-off velocity. In this study, an in vivo video microscopy (IVVM) system was used to measure the size of small (140-400 μm diameter) mouse testicular vessels immediately after the vessels were imaged with 30 MHz power Doppler. The mouse remained on the same platform throughout ultrasound and IVVM imaging. Measurements in four image planes from three mice demonstrated that, similar to previously reported flow-phantom data, in vivo WFSCs exhibit distinct, sloped "characteristic intervals" at cut-off velocities where the CPD approaches the gold-standard IVVM estimate of vascular volume fraction. A wide range of operating point cut-off velocities (4.5 to 12 mm/s) was obtained, which indicates that use of a predetermined cut-off can produce substantial errors in cross-sectional studies that employ power Doppler to quantify vascularity. The WFSC method is a promising strategy for adapting the cut-off velocity to intersubject and longitudinal variations in blood flow during microvascular imaging experiments.

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Gene regulation, modulation, and their applications in gene expression data analysis

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Advances in Bioinformatics 2013年第unknown期2013卷 360678页

作者： Flores, Mario Hsiao, Tzu-Hung Chiu, Yu-Chiao Chuang, Eric Y. Huang, Yufei Chen, Yidong Department of Electrical and Computer Engineering University of Texas at San Antonio San Antonio TX 78249 United States Greehey Children's Cancer Research Institute University of Texas Health Science Center at San Antonio San Antonio TX 78229 United States Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Epidemiology and Biostatistics University of Texas Health Science Center at San Antonio San Antonio TX 78229 United States

Common microarray and next-generation sequencing data analysis concentrate on tumor subtype classification, marker detection, and transcriptional regulation discovery during biological processes by exploring the correlated gene expression patterns and their shared functions. Genetic regulatory network (GRN) based approaches have been employed in many large studies in order to scrutinize for dysregulation and potential treatment controls. In addition to gene regulation and network construction, the concept of the network modulator that has significant systemic impact has been proposed, and detection algorithms have been developed in past years. Here we provide a unified mathematic description of these methods, followed with a brief survey of these modulator identification algorithms. As an early attempt to extend the concept to new RNA regulation mechanism, competitive endogenous RNA (ceRNA), into a modulator framework, we provide two applications to illustrate the network construction, modulation effect, and the preliminary finding from these networks. Those methods we surveyed and developed are used to dissect the regulated network under different modulators. Not limit to these, the concept of "modulation" can adapt to various biological mechanisms to discover the novel gene regulation mechanisms. © 2013 Mario Flores et al.

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Evolving granular neural network for fuzzy time series forecasting

Evolving granular neural network for fuzzy time series forec...

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International Joint Conference on Neural Networks (IJCNN)

作者： Daniel Leite Pyramo Costa Fernando Gomide Department of Computer Engineering and Automation School of Electrical and Computer Engineering University of Campinas Brazil Graduate Program in Electrical Engineering Pontifical Catholic University of Minas Gerais Brazil

A primary requirement of a broad class of evolving intelligent systems is to process a sequence of numeric data over time. This paper introduces a granular neural network framework for evolving fuzzy system modeling from fuzzy data streams. The evolving granular neural network (eGNN) efficiently handles concept changes, distinctive events of nonstationary environments. eGNN constructs interpretable multi-sized local models using fuzzy neural information fusion. An incremental learning algorithm builds the neural network topology from the information contained in data streams. Here we emphasize fuzzy intervals and objects with trapezoidal membership functions. Triangular fuzzy numbers, intervals, and numeric data are particular instances of trapezoids. An example concerning weather time series forecasting illustrates the neural network performance. The goal is to extract, from monthly temperature data, information of interest to attain accurate one-step forecasts and better rapport with reality. Simulation results suggest that eGNN learns from fuzzy data successfully and is competitive with state-of-the-art approaches.

关键词： Neurons Fuzzy sets Approximation methods Data models Neural networks Pragmatics Time series analysis

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