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Relevant bibliographies by topics / Event Related Optical Signal

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Academic literature on the topic 'Event Related Optical Signal'

Author: Grafiati

Published: 11 March 2023

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Journal articles on the topic "Event Related Optical Signal"

1

Maclin, Edward L., Kathy A. Low, Monica Fabiani, and Gabriele Gratton. "Improving the signal-to-noise ratio of event-related optical signals." IEEE Engineering in Medicine and Biology Magazine 26, no. 4 (July 2007): 47–51. http://dx.doi.org/10.1109/memb.2007.384095.

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Tse, Chun-Yu, and Trevor B. Penney. "Preattentive change detection using the event-related optical signal." IEEE Engineering in Medicine and Biology Magazine 26, no. 4 (July 2007): 52–58. http://dx.doi.org/10.1109/memb.2007.384096.

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Gratton, Gabriele, and Monica Fabiani. "Shedding light on brain function: the event-related optical signal." Trends in Cognitive Sciences 5, no. 8 (August 2001): 357–63. http://dx.doi.org/10.1016/s1364-6613(00)01701-0.

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Maclin, Edward L., Kathy A. Low, Jeffrey J. Sable, Monica Fabiani, and Gabriele Gratton. "The event-related optical signal to electrical stimulation of the median nerve." NeuroImage 21, no. 4 (April 2004): 1798–804. http://dx.doi.org/10.1016/j.neuroimage.2003.11.019.

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Gratton, Gabriele, and Monica Fabiani. "The event-related optical signal: a new tool for studying brain function." International Journal of Psychophysiology 42, no. 2 (October 2001): 109–21. http://dx.doi.org/10.1016/s0167-8760(01)00161-1.

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Tse, C. Y., C. L. Lee, J. Sullivan, S. M. Garnsey, G. S. Dell, M. Fabiani, and G. Gratton. "Imaging cortical dynamics of language processing with the event-related optical signal." Proceedings of the National Academy of Sciences 104, no. 43 (October 17, 2007): 17157–62. http://dx.doi.org/10.1073/pnas.0707901104.

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Gratton, Gabriele, and Monica Fabiani. "The event-related optical signal (EROS) in visual cortex: Replicability, consistency, localization, and resolution." Psychophysiology 40, no. 4 (July 2003): 561–71. http://dx.doi.org/10.1111/1469-8986.00058.

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Proulx, Nicole, Ali-Akbar Samadani, and Tom Chau. "Quantifying fast optical signal and event-related potential relationships during a visual oddball task." NeuroImage 178 (September 2018): 119–28. http://dx.doi.org/10.1016/j.neuroimage.2018.05.031.

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GRATTON, GABRIELE, MONICA FABIANI, MARSHA R. GOODMAN-WOOD, and M. CATHERINE DESOTO. "Memory-driven processing in human medial occipital cortex: An event-related optical signal (EROS) study." Psychophysiology 35, no. 3 (May 1998): 348–51. http://dx.doi.org/10.1017/s0048577298001292.

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Gratton, Gabriele, and Monica Fabiani. "Dynamic brain imaging: Event-related optical signal (EROS) measures of the time course and localization of cognitive-related activity." Psychonomic Bulletin & Review 5, no. 4 (December 1998): 535–63. http://dx.doi.org/10.3758/bf03208834.

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Dissertations / Theses on the topic "Event Related Optical Signal"

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Pflieger, Mark Eugene. "A theory of optimal event-related brain signal processors applied to omitted stimulus data /." The Ohio State University, 1991. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487757723995598.

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Ting, Kin-hung. "Fast tracking and analysis of event-related potentials /." View the Table of Contents & Abstract, 2005. http://sunzi.lib.hku.hk/hkuto/record/B30268096.

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Ting, Kin-hung, and 丁建鴻. "Fast tracking and analysis of event-related potentials." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B45015016.

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Glabus, Michael Francis. "Signal processing of the auditory event-related potential in major psychotic illness." Thesis, University of Edinburgh, 1995. http://hdl.handle.net/1842/20532.

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The P300 waveform of the auditory event-related potential (ERP) was evaluated in studies which examined measurement methodology and which analysed the separate sub-components of the waveform in a group of patients with schizophrenia and manic depressive illness. Two simulation studies were carried out. One was designed to evaluate a new objective method for measuring P300 latency, the other applied the technique of latency corrected averaging to P300 measurement. A model for the P300 is described which allows the time domain behaviour of the waveform to be predicted when it is subjected to the different high-pass filters used in clinical studies. The first clinical study was a detailed investigation on the measurement methodology in clinical studies of the auditory P300. The second clinical study used novel auditory stimuli as a means of separating the sub-components of the P300 complex. Three clinical tests were used based on the standard auditory "oddball", a standard auditory oddball with additional "distracting" novel stimuli, and a passive paradigm using novel stimuli. The use of Slow Wave as an index of task difficulty was examined. Twenty-eight controls, 29 schizophrenics and 28 subjects with bipolar depression were studied. The results from these experiments showed that abnormalities of P300 sub-components in the schizophrenic group are enhanced when using distracting stimuli and that these differences are present even in passive orienting. The bipolar group also showed abnormal P300 sub-components in responses to the distraction task. These results could imply a more widespread disruption in underlying brain structures in schizophrenia than bipolar depression. Used in conjunction with brain perfusion images derived from single photon emission tomography (SPET), the paradigms described have shown great potential for locating the underlying brain structures involved in the genesis of P300, and how they are affected in abnormal pathological states.

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CISOTTO, GIULIA. "Movement-related desynchronization detection in Brain-Computer Interface applications for post-stroke motor rehabilitation." Doctoral thesis, Università di Padova, 2014. http://hdl.handle.net/10281/367531.

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Neurological degenerative diseases like stroke, Alzheimer, Amyothrophic Lateral Sclerosis (ALS), Parkinson and many others are constantly increasing their incidence in the world health statistics as far as the mean age of the global population is getting higher and higher. This leads to a general need for effective, at-home and low-cost rehabilitative and health-daily-care tools. The latter should consist either of technological devices implemented for operating in a remote way, i.e. tele-medicine is quickly spreading around the world, or very-advanced computer-based and robotic systems to realize intense and repetitive trainings. This is the challenge in which Information and Communications Technology (ICT) is asked to play a major role in order to bring medicine to reach further advancements. Indeed, no way to cope with these issues is possible outside a strong and vivid cooperation among multi-disciplinary teams of clinicians, physicians, biologists, neuropsychologists and engineers and without a resolute pushing towards a widespread interoperability between Institutes, Hospitals and Universities all over the world, as recently highlighted during the main International conferences on ICT in healthcare. The establishment of well-defined standards for gathering and sharing data will then represent a key element to enhance the efficacy of the aforementioned collaborations. Among the others, stroke is one of the most common neurological pathologies being the second or third cause of mortality in the world; moreover, it causes more than sixty percent survivors remain with severe cognitive and motor impairments that impede them in living normal lives and require a twenty-four-hours daily care. As a consequent, on one side stroke survivors experience a frustrating condition of being completely dependent on other people even to perform simple daily actions like reach and grasp an object,hold a glass of water to drink it and so on. States, by their side, have to take into account additional costs to provide stroke patients and their families with appropriate cares and supports to cope with their needs. For this reason, more and more fundings are recently made available by means of grants, European and International projects, programs to exchange different expertise among various countries with the aim to study how to accelerate and make more effective the recovery process of chronic stroke patients. The global research about this topic is conducted on several parallel aspects: as regard as the basic knowledge of brain processes, neurophysiologists, biologists and engineers are particularly interested in an in-depth understanding of the so-called neuroplastic changes that brain daily operates in order to adapt individuals to life changes, experiences and to realize more extensively their own potentialities. Neuroplasticity is indeed the corner stone for most of the trainings nowadays adopted by the standard as well as the more innovative methods in the rehabilitative programs for post-stroke recovery. Specifically speaking, motor rehabilitation usually includes longterm, repetitive and intense goal-directed exercises that promote neuroplastic mechanisms such as neural sprouting, synapto-genesis and dendritic branching. These processes are strictly related with motor improvements and their study could - one day - serve as prognostic measures of the recovery. Another aspect of this field of neuroscience research is the number of applications that it makes feasible. One of the most exciting is to connect an injured brain to a computer or a robotic device in a Brain-Computer or Brain-Machine Interface (BCI or BMI) scheme aiming at bypassing the impairments of the patient and make him/her autonomously move again or train his/her motor abilities in a more effective way. This kind of research can already count an amount of literature that provides several proofs of concept that these heterogeneous systems constituted by humans and robots can work at the purpose. A particular application of BCI for restoring or enhancing, at least, the reaching abilities of chronic stroke survivors was implemented and is still currently being improved at I.R.C.C.S. San Camillo Hospital Foundation, an Institute for the rehabilitation from neurological diseases located in Lido of Venice and partially technically supported by the Department of Information Engineering of Padua in range of an agreement signed in 2009. This specific BCI platform allows patients to train and improve their reaching movements by means of a robotic arm that provides a force that helps patients in completing the training exercise, i.e. to hit a predetermined target. This force feedback is however subject to a strict condition: during the movement, the person has to produce the expected pattern of cerebral activity. Whenever this is accomplished, a force is delivered proportionally to the entity of the latter activity, otherwise the patient is obliged to operate without any help. In this way, this platform implements the so-called operant-learning, that is one of the most effective conditioning techniques to make a subject learn or relearn a task. If, on one hand, the primary and explicit task is to improve a movement, on the other side the secondary but most important task is to deploy the perilesional part of the brain - still healthy - in becoming responsible for the control of the movement. It is a popular and widely-accepted opinion within the neuroscience community, indeed, that a healthy region of the sensorimotor area nearby the damaged one - which was previously in charge of performing the (reaching) movement - can optimally accomplish the impaired motor function substituting the original control area. Technically speaking, the main crucial feature that can ensure the effectiveness of the whole system is the precise and in real-time identification and quantification of the cerebral pattern associated with the movement, the worldwide named movement-related desynchronization (MRD). Starting from its original definition, passing through the most used techniques for its recognition, the thesis work presents a series of criticisms of the current signal processing method to detect the MRD and a complete analysis of the possible features that can better represent the movement condition and that can be more easily extracted during the on-line operations. Brain - it is well-known - learns by trials and errors and it needs a slightly-delayed (in the range of fraction of seconds) feedback of its performance to learn a task in the best way. This BCI application was born with the purpose to provide the above-mentioned feedback: however, this is only feasible if a computationally easy and contingent signal processing technique is available. This thesis work would like to cope with the lack of a well-planned real-time signal analysis in the current experimental protocol.

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Hoang, Thang Nam. "Analytical methods for signal separation and localisation from single-trial event related potentials to investigate brain dynamics." Thesis, Liverpool John Moores University, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.402944.

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Sable, Jeffrey J. "Electrical and optical investigations of event-related brain activity in human auditory cortex elicited by rapidly presented tones /." free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p3115587.

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Kawaguchi, Hirokazu. "Signal Extraction and Noise Removal Methods for Multichannel Electroencephalographic Data." 京都大学 (Kyoto University), 2014. http://hdl.handle.net/2433/188593.

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Kota, Srinivas. "Dimensionality Reduction and Fusion Strategies for the Design of Parametric Signal Classifiers." OpenSIUC, 2010. https://opensiuc.lib.siu.edu/dissertations/171.

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This dissertation focuses on two specific problems related to the design of parametric signal classifiers: dimensionality reduction to overcome the curse of dimensionality and information fusion to improve classification by exploiting complementary information from multiple sensors or multiple classifiers. Dimensionality reduction is achieved by introducing a strategy to rank and select a subset of principal component transform (PCT) coefficients that carry the most useful discriminatory information. The criteria considered for ranking transform coefficients include magnitude, variance, inter-class separation, and classification accuracies of individual transform coefficients. The ranking strategy not only facilitates overcoming the dimensionality curse for multivariate classifier implementation but also provides a means to further select, out of a rank-ordered set, a smaller set of features that give the best classification accuracies. Because the class-conditional densities of transform feature vectors are often assumed to be multivariate Gaussian, the dimensionality reduction strategy focuses on overcoming the specific problems encountered in the design of practical multivariate Gaussian classifiers using transform feature vectors. Through experiments with event related potentials (ERPs) and ear pressure signals, it is shown that the dimension of the feature space can be decreased quite significantly by means of the feature ranking and selection strategy. Furthermore, the resulting Gaussian classifiers yield higher classification accuracies than those reported in previous classification studies on the same signal sets. Amongst the four feature selection criteria, Gaussian classifiers using the maximum magnitude and maximum variance selection criteria gave the best classification accuracies across the two sets of classification experiments. For the multisensor case, dimensionality reduction is achieved by introducing a spatio-temporal array model to observe the signals across channels and time, simultaneously. A two-step process which uses the Kolmogrov-Smirnov test and the Lilliefors test is formulated to select the array elements which have different Gaussian densities across all signal categories. Selecting spatio-temporal elements that fit the assumed model and also statistically differ across the signal categories not only decreases the dimensionality significantly but also ensures high classification accuracies. The selection is dynamic in the sense that selecting spatio-temporal array elements corresponds to selecting samples of different sensors at different time-instants. Each selected array element is classified using a univariate Gaussian classifier and the resulting decisions are fused into a decision fusion vector which is classified using a discrete Bayes classifier. The application of the resulting dynamic channel selection-based classification strategy is demonstrated by designing and testing classifiers for multi-channel ERPs and it is shown that strategy yields high classification accuracies. Most noteworthy of the two dimensionality reduction strategies is the fact that the multivariate Gaussian signal classifiers developed can be implemented without having to collect a prohibitively large number of training signals simply to satisfy the dimensionality conditions. Consequently, the classification strategies can be beneficial for designing personalized human-machine-interface (HMI) signal classifiers for individuals from whom only a limited number of training signals can reliably be collected due to severe disabilities. The information fusion strategy introduced is aimed at improving the performance of signal classifiers by combining signals from multiple sensors or by combining decisions of multiple classifiers. Fusion classifiers with diverse components (classifiers or data sets) outperform those with less diverse components. Determining component diversity, therefore, is of the utmost importance in the design of fusion classifiers which are often employed in clinical diagnostic and numerous other pattern recognition problems. A new pairwise diversity-based ranking strategy is introduced to select a subset of ensemble components, which when combined, will be more diverse than any other component subset of the same size. The strategy is unified in the sense that the components can be either polychotomous classifiers or polychotomous data sets. Classifier fusion and data fusion systems are formulated based on the diversity selection strategy and the application of the two fusion strategies are demonstrated through the classification of multi-channel ERPs. From the results it is concluded that data fusion outperforms classifier fusion. It is also shown that the diversity-based data fusion system outperforms the system using randomly selected data components. Furthermore, it is demonstrated that the combination of data components that yield the best performance, in a relative sense, can be determined through the diversity selection strategy.

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Lemaster, Richard L. "Development of an Optical Profilometer and the Related Advanced Signal Processing Methods for Monitoring Surface Quality of Wood Machining Applications." NCSU, 2004. http://www.lib.ncsu.edu/theses/available/etd-09282004-152158/.

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The research described here provides the technology and theory to quantify surface quality for a variety of wood and wood-based products. This technology provides a means of monitoring trends in surface quality which can be used to discriminate between Agood@ products and Abad@ products (the methods described in this research are not intended to provide ?grading? of individual workpieces) as well as provide information to the machine operator as to the source of poor quality machined surfaces. The analysis can be done either on-line at industrial speeds or off-line as a periodic quality control tool. Although the surface quality can be quantifiably measured, the determination of the best feature from the surface profile (root mean square, peak amplitude, average wavelength, frequency content, Joint Time and Frequency Analysis (JTFA) and Wavelet Analysis results, etc.) for the quantification of surface Adefects@ is highly dependent on the application. This research consisted of three broad areas: (1) determination of an optimal hardware configuration for both laboratory and industrial surface scans of wood products, (2) determination of the optimal set of surface descriptors as well as the development of advanced signal processing techniques such as the wavelet transform to accurately describe the quality of a surface as well as provide information to the machine operator on the cause of the loss of surface quality, and (3) development of a software interface to distill the advanced signal processing techniques into a readily obtainable and readable format for the machine operator as well as provide assistance for process decisions.

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Books on the topic "Event Related Optical Signal"

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Larkin, Helen J. Studies towards a brain-computer interface for disabled people based on digital processing of evoked & event-related potentials. Dublin: University College Dublin, 1997.

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Valenzuela, S. O., and T. Kimura. Experimental observation of the spin Hall effect using electronic nonlocal detection. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198787075.003.0014.

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This chapter shows how the spin Hall effect (SHE) has been described as a source of spin-polarized electrons for electronic applications without the need for ferromagnets or optical injection. Because spin accumulation does not produce an obvious measurable electrical signal, electronic detection of the SHE proved to be elusive and was preceded by optical demonstrations. Several experimental schemes for the electronic detection of the SHE had been originally proposed, including the use of ferromagnetic electrodes to determine the spin accumulation at the edges of the sample. However, the difficulty of sample fabrication and the presence of spin-related phenomena such as anisotropic magnetoresistance or the anomalous Hall effect in the ferromagnetic electrodes could mask or even mimic the SHE signal in the sample layouts.

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Marks II, Robert J. Handbook of Fourier Analysis & Its Applications. Oxford University Press, 2009. http://dx.doi.org/10.1093/oso/9780195335927.001.0001.

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Fourier analysis has many scientific applications - in physics, number theory, combinatorics, signal processing, probability theory, statistics, option pricing, cryptography, acoustics, oceanography, optics and diffraction, geometry, and other areas. In signal processing and related fields, Fourier analysis is typically thought of as decomposing a signal into its component frequencies and their amplitudes. This practical, applications-based professional handbook comprehensively covers the theory and applications of Fourier Analysis, spanning topics from engineering mathematics, signal processing and related multidimensional transform theory, and quantum physics to elementary deterministic finance and even the foundations of western music theory. As a definitive text on Fourier Analysis, Handbook of Fourier Analysis and Its Applications is meant to replace several less comprehensive volumes on the subject, such as Processing of Multifimensional Signals by Alexandre Smirnov, Modern Sampling Theory by John J. Benedetto and Paulo J.S.G. Ferreira, Vector Space Projections by Henry Stark and Yongyi Yang and Fourier Analysis and Imaging by Ronald N. Bracewell. In addition to being primarily used as a professional handbook, it includes sample problems and their solutions at the end of each section and thus serves as a textbook for advanced undergraduate students and beginning graduate students in courses such as: Multidimensional Signals and Systems, Signal Analysis, Introduction to Shannon Sampling and Interpolation Theory, Random Variables and Stochastic Processes, and Signals and Linear Systems.

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Advanced Signal Processing on Event-Related Potentials: Filtering Erps in Time, Frequency and Space Domains Sequentially and Simultaneously. World Scientific Publishing Co Pte Ltd, 2015.

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Brandeis, Daniel, Sandra K. Loo, Grainne McLoughlin, Hartmut Heinrich, and Tobias Banaschewski. Neurophysiology. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198739258.003.0009.

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Neurophysiology allows us to understand and modulate the neural mechanisms in ADHD with high time- and/or frequency-resolution. These non-invasive methods include electroencephalographic recordings at rest and during tasks, with spontaneous and event-related oscillations and potentials tracking covert processing and transcranial neuromodulation through magnetic or electric fields. The findings indicate consistent cognitive and neural deficits in ADHD related to impaired attention and deficient inhibition. Advanced signal processing and source imaging methods often converge with other imaging approaches. Neurophysiological findings also reveal considerable heterogeneity in ADHD regarding cognitive, affective, and genetic subtypes. This illustrates the importance of dimensional approaches and of pathophysiological mechanisms partly shared with other disorders. Although several potential neurophysiological markers of ADHD have been considered, a clinical use for individual diagnostics and classification is not supported to date. More research should clarify the clinical potential of multivariate multimodal classification and prediction of treatment outcome to advance individualized treatment.

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Vanhatalo, Sampsa, and J. Matias Palva. Infraslow EEG Activity. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0032.

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Infraslow electroencephalographic (EEG) activity refers to frequencies below the conventional clinical EEG range that starts at about 0.5 Hz. Evidence suggests that salient EEG signals in the infraslow range are essential parts of many physiological and pathological conditions. In addition, brain is known to exhibit multitude of infraslow processes, which may be observed directly as fluctuations in the EEG signal amplitude, as infraslow fluctuations or intermittency in other neurophysiological signals, or as fluctuations in behavioural performance. Both physiological and pathological EEG activity may range from 0.01 Hz to several hundred Hz. In the clinical context, infraslow activity is commonly observed in the neonatal EEG, during and prior to epileptic seizures, and during sleep and arousals. Laboratory studies have demonstrated the presence of spontaneous infraslow EEG fluctuations or very slow event-related potentials in awake and sleeping subjects. Infraslow activity may not only arise in cortical and subcortical networks but is also likely to involve non-neuronal generators such as glial networks. The full, physiologically relevant range of brain mechanisms can be readily recorded with wide dynamic range direct-current (DC)-coupled amplifiers or full-band EEG (FbEEG). Due to the different underlying mechanisms, a single FbEEG recording can even be perceived as a multimodal recording where distinct brain modalities can be studied simultaneously by performing data analysis for different frequency ranges. FbEEG is likely to become the standard approach for a wide range of applications in both basic science and in the clinic.

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Book chapters on the topic "Event Related Optical Signal"

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Sanei, Saeid, and J. A. Chambers. "Event-Related Potentials." In EEG Signal Processing, 127–59. West Sussex, England: John Wiley & Sons Ltd,, 2013. http://dx.doi.org/10.1002/9780470511923.ch3.

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LaCaille, Lara, Anna Maria Patino-Fernandez, Jane Monaco, Ding Ding, C. Renn Upchurch Sweeney, Colin D. Butler, Colin L. Soskolne, et al. "Event-Related Optical Imaging (EROI)." In Encyclopedia of Behavioral Medicine, 718. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_100585.

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Karp, Elina, Lauri Parkkonen, and Ricardo Vigário. "Denoising Single Trial Event Related Magnetoencephalographic Recordings." In Independent Component Analysis and Signal Separation, 427–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00599-2_54.

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Lu, Xuejing, and Li Hu. "Electroencephalography, Evoked Potentials, and Event-Related Potentials." In EEG Signal Processing and Feature Extraction, 23–42. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9113-2_3.

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Ferreira, Danton Diego, Antônio Maurício Ferreira Leite Mir de Sá, Augusto Santiago Cerqueira, and José Manoel de Seixas. "ICA-Based Method for Quantifying EEG Event-Related Desynchronization." In Independent Component Analysis and Signal Separation, 403–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00599-2_51.

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Wu, Zhen, Junsong Wang, Deli Shen, and Xuejun Bai. "Denoising of Event-Related Potential Signal Based on Wavelet Method." In Lecture Notes in Computer Science, 165–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15615-1_20.

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Fang, Chunying, Haifeng Li, and Lin Ma. "EEG Signal Classification Using the Event-Related Coherence and Genetic Algorithm." In Advances in Brain Inspired Cognitive Systems, 92–100. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38786-9_11.

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Rodríguez-León, Ingrid G., Luz María Alonso-Valerdi, Ricardo A. Salido-Ruiz, Israel Román-Godínez, David I. Ibarra-Zarate, and Sulema Torres-Ramos. "Monitoring of Auditory Discrimination Therapy for Tinnitus Treatment Based on Event-Related (De-) Synchronization Maps." In Signal Processing in Medicine and Biology, 29–59. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-21236-9_2.

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Abou-Abbas, Lina, Stefon van Noordt, and Mayada Elsabbagh. "Event Related Potential Analysis Using Machine Learning to Predict Diagnostic Outcome of Autism Spectrum Disorder." In Bioengineering and Biomedical Signal and Image Processing, 71–79. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88163-4_7.

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Tsytsarev, Vassiliy, and Dmitri B. Papkovsky. "CHAPTER 16. In vivo Brain Functional Imaging Using Oxygenation-related Optical Signal." In Quenched-phosphorescence Detection of Molecular Oxygen, 319–34. Cambridge: Royal Society of Chemistry, 2018. http://dx.doi.org/10.1039/9781788013451-00319.

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Conference papers on the topic "Event Related Optical Signal"

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Gratton, G., K. A. Low, E. L. Maclin, C. R. Brumback, B. Gordon, and M. Fabiani. "Time course of activation of human occipital cortex measured with the event-related optical signal (EROS)." In Biomedical Topical Meeting. Washington, D.C.: OSA, 2006. http://dx.doi.org/10.1364/bio.2006.md4.

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Dong, Sunghee, Jaeyoung Shin, and Jichae Jeong. "Detection of event related optical signal (EROS) in episodic memory retrieval task using ICA-based Kalman filter." In 2015 15th International Conference on Control, Automation and Systems (ICCAS). IEEE, 2015. http://dx.doi.org/10.1109/iccas.2015.7364943.

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Palm, Stephen P., and James D. Spinhirne. "Optimization of Lidar Boundary Layer Height Retrieval." In Laser and Optical Remote Sensing: Instrumentation and Techniques. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/lors.1987.mc7.

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A highly significant application for lidar sounding of the atmosphere is the retrieval of the height of the planetary boundary layer (PBL). The PBL height is an important factor in the transport of energy from the surface to the free troposphere and is directly related to the initiation and development of mesoscale events. Thus PBL height is a very useful input and validation parameter for Global Circulation Models. Currently there is no effective passive retrieval technique for PBL height. However the detection of PBL height from lidar aerosol scattering has been widely demonstrated. A primary consideration for lidar PBL height retrieval is the minimal detectability in terms of either atmospheric scattering structure or lidar system signal to noise sensitivity. Global measurements of PBL height from space borne lidar systems are envisioned. A primary consideration is how reliably PBL height may be detected for given lidar system parameters. The cost of a space borne system may be significantly reduced by minimizing telescope size and transmitted laser power.

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Leistritz, Lutz, and Carolin Ligges. "Signal-Adaptive Denoising Of Event-Related Potentials." In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2018. http://dx.doi.org/10.1109/embc.2018.8512940.

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Britton, J. "Extracting single trial event related potentials." In First International Conference on Advances in Medical Signal and Information Processing. IEE, 2000. http://dx.doi.org/10.1049/cp:20000329.

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Srinidhi, R., Vishal Sharma, M. Sukumar, and C. S. Venkatesha. "Correlative Flank Wear Analysis of Single Point Turning Inserts Using Acoustic Emission and Artificial Intelligence Techniques." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-67543.

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Wear mechanism of a cutting tool is highly complex in that the processes of tool wear results from interacting effect of machining configurations. Various output generated by the study and analysis of each tool is extremely useful in analyzing the tool characteristics in general and to make efforts to obtain the estimated tool life in particular. The gradual process of tool wear has adverse influence on the quality of the surface generated and on the design specifications in the work piece dimensions and geometry, and causes, at the worst case, machine breakdown. Advanced manufacturing demands proper use of the right tool and emphasizes the need to check the wear rate. A scientific method of obtaining conditions for an optimal machining process with proper tools and control of machining parameters is essential in the present day manufacturing processes. Many problems that affect optimization are related to the diminished machine performance caused by worn out tools. One of the indirect methods of tool wear analysis and monitoring is based on the acoustic emission (AE) signals. The generation of the AE signals directly in the cutting zone makes them very sensitive to changes in the cutting process and provides a means of evaluating the wear of cutting tools. Wear parameters obtained in the process are analyzed with the output generated by using Multi Layer Perceptron (MLP) based back propagation technique and Adaptive Neuro Fuzzy Interference System (ANFIS). The results obtained from these methods are correlated for the actual and predicted wear. Experiments have been conducted on EN8 and, EN24 using Uncoated Carbide, Coated carbide and Ceramic inserts (Kennametal, India make) on a high speed lathe for the most appropriate cutting conditions. The AE signal analysis (considering signal parameters such as, ring down count (RDC), rise time (RTT), event duration (ED) and energy (EG). Flank wear in tools and corresponding cutting forces for each of the trials are measured and are correlated for various combinations of tools and materials of work piece.

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Bigdely-Shamlo, Nima, Kenneth Kreutz-Delgado, Kay Robbins, Makoto Miyakoshi, Marissa Westerfield, Tarik Bel-Bahar, Christian Kothe, Jessica Hsi, and Scott Makeig. "Hierarchical Event Descriptor (HED) tags for analysis of event-related EEG studies." In 2013 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2013. http://dx.doi.org/10.1109/globalsip.2013.6736796.

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"CLASSIFYING EVENT RELATED POTENTIALS FOR VALID AND PARADOX REASONING." In International Conference on Bio-inspired Systems and Signal Processing. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003767702180225.

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Mestre, Maria Rosario, Simon J. Godsill, and William J. Fitzgerald. "Bayesian detection of single-trial event-related potentials." In ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2014. http://dx.doi.org/10.1109/icassp.2014.6854492.

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Boudiaf, M., M. Benkherrat, and M. A. Boudiaf. "Partial-Update Adaptive Filters for Event-Related Potentials Denoising." In IET 3rd International Conference on Intelligent Signal Processing (ISP 2017). Institution of Engineering and Technology, 2017. http://dx.doi.org/10.1049/cp.2017.0356.

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Reports on the topic "Event Related Optical Signal"

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Speed, Ann Elizabeth, Olga Blum Spahn, and Alan Yuan-Chun Hsu. Final Report on LDRD project 130784 : functional brain imaging by tunable multi-spectral Event-Related Optical Signal (EROS). Office of Scientific and Technical Information (OSTI), September 2009. http://dx.doi.org/10.2172/993885.

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Philosoph-Hadas, Sonia, Richard Crain, Shimon Meir, Nehemia Aharoni, and Susan Lurie. Calcium-Mediated Signal Transduction during Leaf Senescence. United States Department of Agriculture, November 1995. http://dx.doi.org/10.32747/1995.7604925.bard.

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We have examined the possibility that modulation of [Ca2+]cyt may represent a signal which induces senescence processes in leaves, through triggering of lipid hydrolysis leading to the cascade of detriorative events. Characterization of the signal transduction components operating during leaf senescence was gained by studying various Ca2+-dependent activities of parsley and chrysanthemum leaves, in relation to several senescence functions, and in response to senescence-modulating hormones (ethylene,ABA, BA and IAA). Some innovative findings regarding the control of senescence processes by [Ca2+]cyt were established: Several Ca2+-or CaM-related compounds were shown to modulate [Ca2+]cyt and action, thereby affecting whole leaf senescence. The involvement of [Ca2+]cyt in mediating the effects of senescence-modulating hormones has been demonstrated. Loss of energized Ca2+-transport capability of PM was found to an early event in leaf senescence, which occurs before changes in senescence parameters are observed, and while other PM ATPase enzymes still retain about 50% of their activities. A general pattern of increased phosphorylation of PM proteins with advanced senescence, which could be modified by plant hormones applied in vivo (BA) or in vitro (ABA), sa found. Taken together, all this indirect evidence indicate that [Ca2+]cyt is elevated due to the senescence-induced decrease in the ability to extrude Ca2+, which results particularly from reduced PM Ca2++-transport capability rather than increased operation of Ca2+ channels or elevated Ins(1,4,5)P3 levels. The direct proof for such a senescence-related elevation in [Ca2+]cyt was provided for the first time by the Ca2+ imaging measures with fura-2, showing a rise in [Ca2+]cyt of mesophyll cells upon senescence induction, which preceeded changes in typical senescence characteristics. This research provides strong evidence for regarding the rise in [Ca2+]cyt as a primary event in induction of the senescence syndrome in detached leaves. The findings have also broad implications for postharvest handling of leafy crops and ornamentals, and open new avenues for employing Ca2+-related inhibitors to delay leaf senescence.

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Delmer, Deborah P., Douglas Johnson, and Alex Levine. The Role of Small Signal Transducing Gtpases in the Regulation of Cell Wall Deposition Patterns in Plants. United States Department of Agriculture, August 1995. http://dx.doi.org/10.32747/1995.7570571.bard.

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The combined research of the groups of Delmer, Levine and Johnson has led to a number of interesting findings with respect to the function of the small GTPase Rac in plants and also opened up new leads for future research. The results have shown: 1) The Rac13 protein undergoes geranylgeranlyation and is also translocated to the plasma membrane as found for Rac in mammals; 2) When cotton Rac13 is highly- expressed in yeast, it leads to an aberrant phenotype reminiscent of mutants impaired in actin function, supporting a role for Rac13 in cytoskeletal organization; 3) From our searches, there is no strong evidence that plants contain homologs of the related CDC42 genes found in yeast and mammals; 4) We have identified a rather unique Rac gene in Arabidopsis that has unusual extensions at both the N- and C-terminal portions of the protein; 5) New evidence was obtained that an oxidative burst characterized by substantial and sustained production of H202 occurs coincident with the onset of secondary wall synthesis in cotton fibers. Further work indicates that the H202 produced may be a signal for the onset of this phase of development and also strongly suggests that Rac plays an important role in signaling for event. Since the secondary walls of plants that contain high levels of lignin and cellulose are the major source of biomass on earth, understanding what signals control this process may well in the future have important implications for manipulating the timing and extent of secondary wall deposition. 6) When the cotton Rac13 promoter is fused to the reporter gene GUS, expression patterns in Arabidopsis indicate very strong and specific expression in developing trichomes and in developing xyelm. Since both of these cell types are engaged in secondary wall synthesis, this further supports a role for Rac in signaling for onset of this process. Since cotton fibers are anatomically defined as trichomes, these data may also be quite useful for future studies in which the trichomes of Arabidopsis may serve as a model for cotton fiber development; the Rac promoter can therefore be useful to drive expression of other genes proposed to affect fiber development and study the effects on the process; 7) The Rac promoter has also been shown to be the best so far tested for use in development of a system for transient transformation of developing cotton fibers, a technique that should have many applications in the field of cotton biotechnology; 8) One candidate protein that may interact with Rac13 to be characterized further in the future is a protein kinase that may be analogous to the PAK kinase that is known to interact with Rac in mammals.

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