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INTERMAG is the premier conference on all aspects of applied magnetism and provides a range of oral and poster presentations, invited talks and symposia, a tutorial session, and exhibits reviewing the latest developments in magnetism.
The conference program will consist of plenary lectures, symposia, workshops andinvitedsessions of the latest significant findings and developments in all the major fields ofbiomedical engineering.Submitted papers will be peer reviewed. Accepted high quality paperswill be presented in oral and postersessions, will appear in the Conference Proceedings and willbe indexed in PubMed/MEDLINE & IEEE Xplore
The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.
2019 IEEE 58th Conference on Decision and Control (CDC)
The CDC is recognized as the premier scientific and engineering conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, systems and control, and related areas.The 58th CDC will feature contributed and invited papers, as well as workshops and may include tutorial sessions.The IEEE CDC is hosted by the IEEE Control Systems Society (CSS) in cooperation with the Society for Industrial and Applied Mathematics (SIAM), the Institute for Operations Research and the Management Sciences (INFORMS), the Japanese Society for Instrument and Control Engineers (SICE), and the European Union Control Association (EUCA).
Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.
The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...
The IEEE Reviews in Biomedical Engineering will review the state-of-the-art and trends in the emerging field of biomedical engineering. This includes scholarly works, ranging from historic and modern development in biomedical engineering to the life sciences and medicine enabled by technologies covered by the various IEEE societies.
Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.
Serves as a compendium for papers on the technological advances in control engineering and as an archival publication which will bridge the gap between theory and practice. Papers will highlight the latest knowledge, exploratory developments, and practical applications in all aspects of the technology needed to implement control systems from analysis and design through simulation and hardware.
IEEE Signal Processing Magazine, 2008
In the above titled article (ibid, vol 25. no. 1, 69-77, Jan 08), changes were made to several equations and formulas.
2007 IEEE 33rd Annual Northeast Bioengineering Conference, 2007
The development of any implant or medical device requires extensive testing. Often in vivo testing is difficult, and sometimes-in the case of neural control devices-impossible. Phantom heads have been constructed in the past for such applications as testing the effects of cellular communication devices, but these models are limited in their utility. The current study is not only aimed at ...
6th International Conference on Signal Processing, 2002., 2002
Spatial analysis of electroencephalogram (EEG) signal sources is a technology based on the methods solving EEG inverse problem. In this field, the human brain is often considered as a quasi-static electromagnetic system. Combined with boundary element method results, the spatial distribution of EEG sources is analyzed by a hybrid weighted minimum norm solution. The simulation experiments are given to show ...
Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications, 2002
In this paper a cellular neural network (CNN) based system to perform a real- time, parallel processing of magetoencephalographic data is proposed. In particular, a nonlinear approach to blind sources separation, instead of the linear procedure performed by independent component analysis, is introduced. Moreover, the characteristic spatial distribution of the cells in the CNN system has been exploited to reproduce ...
1996 IEEE International Symposium on Circuits and Systems. Circuits and Systems Connecting the World. ISCAS 96, 1996
The lossless compression of electroencephalographic (EEG) data is of great interest to the biomedical research community. In this paper, a two-stage technique of lossless compression involving decorrelating the sample points of the EEG signal and then entropy coding the resulting signal is examined. Two alternatives are presented for performing the first task. Specifically, the first stage consists either of a ...
In the above titled article (ibid, vol 25. no. 1, 69-77, Jan 08), changes were made to several equations and formulas.
The development of any implant or medical device requires extensive testing. Often in vivo testing is difficult, and sometimes-in the case of neural control devices-impossible. Phantom heads have been constructed in the past for such applications as testing the effects of cellular communication devices, but these models are limited in their utility. The current study is not only aimed at producing a head model fit for the testing of neural control devices, but also at providing a template for future work. By providing the fundamental knowledge of and putting together the framework necessary to designing a phantom, this study generalizes the process such that this method of modeling may be useful for other applications.
Spatial analysis of electroencephalogram (EEG) signal sources is a technology based on the methods solving EEG inverse problem. In this field, the human brain is often considered as a quasi-static electromagnetic system. Combined with boundary element method results, the spatial distribution of EEG sources is analyzed by a hybrid weighted minimum norm solution. The simulation experiments are given to show the promising ability of the proposed approach.
In this paper a cellular neural network (CNN) based system to perform a real- time, parallel processing of magetoencephalographic data is proposed. In particular, a nonlinear approach to blind sources separation, instead of the linear procedure performed by independent component analysis, is introduced. Moreover, the characteristic spatial distribution of the cells in the CNN system has been exploited to reproduce the topology of the acquisition channels over the scalp.
The lossless compression of electroencephalographic (EEG) data is of great interest to the biomedical research community. In this paper, a two-stage technique of lossless compression involving decorrelating the sample points of the EEG signal and then entropy coding the resulting signal is examined. Two alternatives are presented for performing the first task. Specifically, the first stage consists either of a fixed coefficient filter or a recursive least squares lattice filter. The second stage employs arithmetic coding to perform the task of entropy coding the data. In the decompression stage, exact inverse filters are applied to achieve lossless compression. Simulations demonstrate the feasibility of this method for lossless EEG data compression.
Many noises are interfused into EEG signals when they are measuring. In order to remove the noises effectively, a novel method based on Hilbert Huang Transform, is shown in the thesis. The theories of empirical mode decomposition and instantaneous frequency solution which are two parts of Hilbert-Huang Transformation are discussed in the thesis. Empirical mode decomposion is used to EEG which can be decomposed into a limited number of intrinsic mode functions. Different threshold are used to treat intrinsic mode functions to achieve de-noising. Results: Hilbert-Huang Transformation is demonstrated to be effective in removing the general EEG noise. Compared with the traditional wavelet transform, Hilbert-Huang Transform for EEG de-noising has some advantages. Conclusion: Using HHT method for EEG signals denoising effective and doable.
When using low power laser in therapy and diagnostics, the knowledge about the relationship between laser wavelengths and the percentage of reflected energy in the interface air-tissue and the distribution of energy in tissue helps us to choose appropriate wavelengths. In this paper, we present some results obtained from the simulation of low power 633, 780, 850, and 940 nm laser in brain by Monte Carlo method, with the model of brain consisted of 3 mm scalp, 5 mm skull, 3 mm cerebral cortex & grey matter, and white matter. Based on these results, we fabricated devices called ldquolaser semiconductor optoacupuncture devicerdquo using 780 and 940 nm semiconductor lasers to treat some diseases such as cerebral palsy at children, and drug detoxification. In this paper we present the results of dug detoxification for 115 addicted patients using ldquolaser semiconductor optoacupuncture device".
Independent component analysis (ICA) is suggested to be useful in the analysis of signals (electroencephalography (EEG) and event-related potential (ERP)) recorded from the scalp electrodes to examine brain activity. But ICA analysis of ERP has the problem that it lacks validity across subjects. Therefore, we examined a new approach to give validity across subjects to ICA results obtained from single subjects. To do this, we combined two criteria of how much a single subject's signals contain task-related components and the similarity of the spatial patterns of those task-related components across subjects. We applied our approach to EEG data recorded in an experiment. As a result, analysis with a combination of ICA and our approach extracted significantly more task-related components from the observed signals than analysis without the combination did, although both analyses suggested that the occipital area activity was most relevant to performing the task across subjects. These results suggest that our approach is useful for extracting task-related components from the observed EEG signals and for giving validity across subjects in ICA analysis of EEG/ERP
The spatial distribution of electroencephalogram (EEG) features on the scalp surface, both in time or frequency, is of great importance in clinical applications and medical research. Traditionally, mathematical methods based on interpolation algorithms have been widely applied to obtain the EEG mappings. This paper presents an innovative approach to reconstructing the brain potential mappings from multichannel EEGs. The three-dimensional (3-D) filtering approach, differing from the numerical interpolating methods, considers the spatial distribution of brain potentials as a 3-D signal, which is processed and interpolated according to its spatial frequency characteristics. The performance of the 3-D filtering method evaluated on simulated brain potentials is shown to be comparable to the four-nearest- neighbors method. Moreover, the 3-D filtering method is superior to the spherical splines method in efficiency. Two main advantages of this method are: the prospect of developing realtime, animated EEG mappings utilizing powerful digital signal processors and its capability of processing and interpolating the brain potentials on the realistic irregular scalp surface.
Previous study has shown that the scalp electrical activity (e.g. EEG) could provide information on hypoxic-ischemic (HI) brain injury. The time dependent entropy (TDE) of EEG was applied as a means to segment the injury and recovery phases. A reduction in entropy during the injury was explained as the result of the spiking or bursting activity during the recovery of HI injury. The aim of this study is to investigate the spiking activity in the cortex during (HI) brain injury. The multiunit activity recorded from the cortex (CTX MUA) is analyzed with TDE methods. The spike sensitive TDE tracks the electric activity at the cellular level. The CTX MUA has high TDE value after the HI injury, which gradually returns to the baseline level as the brain recovers. This is the first report of cellular electrical response to global ischemic injury.
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