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Tietche B.H.,University Pierre and Marie Curie | Tietche B.H.,Cergy-Pontoise University | Romain O.,ETIS Laboratory | Denby B.,SIGMA Laboratory | De Dieuleveult F.,French Atomic Energy Commission
IEEE Transactions on Consumer Electronics | Year: 2012

The paper describes a Software Defined Radio architecture that simultaneously demodulates all radio stations in the Frequency Modulated (FM) band, and is intended as a preprocessor for content and metadata indexing applications. The system, which contains an overlap-add type channelizing filterbank and a massively parallel frequency demodulation block, is implemented in a single Field- Programmable Gate Array, thus offering the possibility of replacing more traditional media indexing installations containing tens of individual receivers. It is believed to be the first single chip full-band channelization system intended for consumer broadcast media indexing applications. Chip resource utilization details and experimental results from the developed system are also presented. © 2011 IEEE.


Tomita Y.,Foster Electrical Co. | Vialatte F.-B.,SIGMA Laboratory | Dreyfus G.,SIGMA Laboratory | Mitsukura Y.,Keio University | And 2 more authors.
IEEE Transactions on Biomedical Engineering | Year: 2014

Although noninvasive brain-computer interfaces (BCI) based on electroencephalographic (EEG) signals have been studied increasingly over the recent decades, their performance is still limited in two important aspects. First, the difficulty of performing a reliable detection of BCI commands increases when EEG epoch length decreases, which makes high information transfer rates difficult to achieve. Second, the BCI system often misclassifies the EEG signals as commands, although the subject is not performing any task. In order to circumvent these limitations, the hemodynamic fluctuations in the brain during stimulation with steady-state visual evoked potentials (SSVEP) were measured using near-infrared spectroscopy (NIRS) simultaneously with EEG. BCI commands were estimated based on responses to a flickering checkerboard (ON-period). Furthermore, an 'idle' command was generated from the signal recorded by the NIRS system when the checkerboard was not flickering (OFF-period). The joint use of EEG and NIRS was shown to improve the SSVEP classification. For 13 subjects, the relative improvement in error rates obtained by using the NIRS signal, for nine classes including the 'idle' mode, ranged from 85% to 53%, when the epoch length increase from 3 to 12 s. These results were obtained from only one EEG and one NIRS channel. The proposed bimodal NIRS-EEG approach, including detection of the idle mode, may make current BCI systems faster and more reliable. © 1964-2012 IEEE.


Dubois R.,University of Bordeaux 1 | Dubois R.,SIGMA Laboratory | Extramiana F.,Hopital Bichat | Denjoy I.,Hopital Bichat | And 5 more authors.
Computing in Cardiology | Year: 2012

Long QT syndrome (LQT) is a congenital disease caused by a mutation of genes that leads to a distortion and a prolongation of the T-wave on standard ECG. The present study proposes an algorithm to automatically discriminate between patients with type 1 or type 2 LQT syndrom. The core of the method is the modeling of the T-wave recomputed on its principal lead by a single parameterized function named Bi-Gaussian Function (BGF). From all the features computed from this model, a statistical analysis was performed to select only the most relevant ones for the discrimination. A classifier was then designed through a Linear Discriminant Analysis (LDA). A database composed of 410 LQTS patients whose genotype is known was used to train the classifier and evaluate its performances. © 2012 CCAL.

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