NEUROCOMPUTING AND INTERFACING DIGITAL TASTING SYSTEM: RESEARCH, DESIGN, AND EVALUATION

The continuous evolution in computing and interfacing has been extended to develop multi-sensory experiences in many domains such as neurological, auditory, vision, and haptic domains. So far, only a few remarkable system approaches have been approved to be serving the taste sensation digitally. Although taste sensation is linked to the brain, there is a lack of optimal neurocomputing digital taste sensation systems. Our study provides a new neurocomputing method to digitally stimulate the sense of taste by electrical stimulation on the human tongue. We aim to link chemical stimulation and electrical stimulation in order to design an electronic interface for inducing taste digitally. The design proposes a module that is responsible for electric and stimulation to produce different taste sensations. In addition, the taste is delivered through the tongue interface by silver electrodes, coupled with a control system responsible for generating specific stimulation parameters based on user inputs selected on his mobile. A spoon for implementing the taste interface is issued in order to provide a user-friendly tool as a solution for various problems. Experimental results showed that the new model and design of the digital taste system works well and testing results showed clearly that 90% of the tested members were able to distinguish the taste. Among the taste categories, the initial results recommended that sourness and saltiness are the most probable sensations that would be induced. Besides the Biomedical importance of the new taste system for people suffering from taste problems, (no sense of taste, bad taste in the mouth, diminished sense of taste, distorted sense of taste) and for people having diabetes and hypertension, this technology shows the possibility and could be considered for sharing tastes in social networking and adapting it in virtual reality, gaming and other domains, also the sensation of tastes could be improved by involving others senses such as olfactory and sounds and increasing the population of tested members

Empirical Research On The Optimization Of The Frequency Parameters Of " Chirp " Sequences Used In Contrast Ultrasound Imaging

International audienceThe contrast medical imaging is an active research domain in which several coding techniques of the transmit have been proposed to increase the contrast. In this paper, we focus on the continuous coding of the Ultrasound transmits, such as "chirp" sequences, and their insonation on the medium under exploration. We empirically show that there are particular values for the frequency parameters of the frequency coded excitation "chirp" which optimize the contrast in contrast enhanced ultrasound images. We also show that in the nonlinear response of micro-bubbles the modulation indices are no longer symmetrical

Reducing sojourn points from recurrence plots to improve transition detection: Application to fetal heart rate transitions

International audienceThe analysis of biomedical signals demonstrating complexity through recurrence plots is challenging. Quantification of recurrences is often biased by sojourn points that hide dynamic transitions. To overcome this problem, time series have previously been embedded at high dimensions. However, no one has quantified the elimination of sojourn points and rate of detection, nor the enhancement of transition detection has been investigated. This paper reports our ongoing efforts to improve the detection of dynamic transitions from logistic maps and fetal hearts by reducing sojourn points. Three signal-based recurrence plots were developed, i.e. embedded with specific settings, derivative-based and m-time pattern. Determinism, cross-determinism and percentage of reduced sojourn points were computed to detect transitions. For logistic maps, an increase of 50% and 34.3% in sensitivity of detection over alternatives was achieved by m-time pattern and embedded recurrence plots with specific settings, respectively, and with a 100% specificity. For fetal heart rates, embedded recurrence plots with specific settings provided the best performance, followed by derivative-based recurrence plot, then unembedded recurrence plot using the determinism parameter. The relative errors between healthy and distressed fetuses were 153%, 95% and 91%, respectively. More than 50% of sojourn points were eliminated, allowing bette

Delta-Fuzzy Similarity Entropy to Discriminate Healthy from Sick Fetus

ISBN: 978-1-4799-0251-4 IEEE catalog number: CFP1392U-ARTInternational audienceThis paper deals with the discrimination between suffering and healthy fetuses, by means of a delta-fuzzy-similarity entropy. This new descriptor of complexity is based on the derivative of the fuzzy-similarity entropy. It was tested on fetal heart rate time-series and compared to the approximated and similarity entropies. The main outcome was the possibility to improve 10% the specificity and the sensitivity as compared to approximate entropy. This very good performance confirms that the new descriptor can be a valuable alternative as compared to other standard descriptors

Automatic Approach Seeking Optimal Frequency Modulation Parameters In Chirp Inversion and Chirp Reversal Ultrasound Contrast Imaging

National audienceState-of-the art applications involving frequency coded excitations known as chirp excitations, are cutting edge in contrast ultrasound imaging. A question may arise: How does the manufacturer select the frequency modulation parameters of chirp excitations in clinical practice? The present study aims to select, automatically, the optimal frequency modulation parameters of chirp excitations by maximizing the backscattered power using two post-processing techniques: chirp inversion and chirp reversal imaging. Our simulation setup consisted of a transducer (central frequency 2.25 MHz), microbubble with diameter 5 μm reception phase and optimization feedback. Fifty iterations were carried out, during each, the medium was insonified with two either out-of-phase to time reversed chirp excitations having a linear frequency modulation law and a driving pressure 100 kPa. Simulations revealed that optimal command was advantageous over the standard technique in both chirp inversion and reversal techniques. In chirp inversion, the gain reached 7.2 dB, and the maximum backscattered power was achieved after 24 iterations. The transmitted frequency has decreased by 0.73 MHz, and the second modulation index increased by 0.13 MHz/s compared to the standard optimization. In chirp reversal, the gain has reached 17.4 dB, the transmitted frequency decreased by 0.8 MHz and the frequency modulation index increased by 0.03 MHz/s compared to the standard optimization. Our chirp reversal pre-processing optimization approach paves the way for improved ultrasound contrast images. As a future progress we tend to validate our findings in vitro

Coarse-Grained Multifractality Analysis Based on Structure Function Measurements to Discriminate Healthy from Distressed Foetuses

International audienceThis paper proposes a combined coarse-grained multifractal method to discriminate between dis-tressed and normal foetuses. The coarse-graining operation was performed by means of a coarse-grained procedure and the multifractal operation was based on a structure function. The proposed method was evaluated by one hundred recordings including eighty normal foetuses and twenty dis-tressed foetuses. We found that it was possible to discriminate between distressed and normal foetuses using the Hurst exponent, singularity and Holder spectra

Automatic Optimization of Chirp Setting Parameters In Medical Ultrasound Contrast Imaging

International audienceMedical ultrasound contrast imaging is a powerful modality undergoing successive developments in the last decade to date. Lately, pulse inversion has been used in both ultrasound tissue harmonic and contrast imaging. However, there was a tradeoff between resolution and penetration. Chirp excitations partially solved the tradeoff, but the chirp setting parameters were not optimized. The present work proposes for the first time combining chirp inversion with ultrasound contrast imaging, with the motivation to improve the contrast, by automatically optimizing the setting parameters of chirp excitation, it is thus an optimal command problem. Linear chirps, 5 ?m diameter microbubbles and gradient ascent algorithm were simulated to optimize the chirp setting parameters. Simulations exhibited a gain of 5 dB by automatic optimization of chirp inversion relative to pulse inversion. The automatic optimization process was quite fast. Combining chirp inversion with ultrasound contrast imaging led to a maximum backscattered power permitting high contrast outcomes and optimum parameters

Cascade of Nonlinear Entropy and Statistics to Discriminate Fetal Heart Rates

International audience—Fetal heart rate discrimination is an evolving field in biomedical engineering with many efforts dedicated to avoid preterm deliveries by way of improving fetus monitoring methods and devices. Entropy analysis is a nonlinear signal analysis technique that has been progressively developed to improve the discriminability of a several physiological signals, with Kernel based entropy parameters (KBEPs) found advantageous over standard techniques. This study is the first to apply KBEPs to analyze fetal heart rates. Specifically, it explores the usability of the cutting-edge nonlinear KBEPs in discriminating between healthy fetuses and fetuses under distress. The database used in this study comprises 50 healthy and 50 distressed fetal heart rate signals with severe intrauterine growth restriction. The Cascade analysis investigates six kernel based entropy measures on fetal heart rates discrimination, and compares them to four standard entropies. The study presents a statistical evaluation of the discrimination power of each parameter (paired t-test statistics and distribution spread). Simulation results showed that the distribution ranges in 80% of the entropy parameters in the distressed heart group are higher than those in the healthy control group. Moreover, the results show that it is advantageous to choose Circular entropy then Cauchy entropy (p < 0.001) over the standard techniques, in order to discriminate fetal heart rates

Comparison between fresh and fixed human biopsies using spectral and lifetime measurements: Fluorescence analysis using one and two photon excitations

International audienceThe purpose of this study is to make a comparison between the fluorescence emissions of fresh extracted human biopsies and fixed human biopsies, in order to evaluate the impact of fixation on autofluoresence signal. Our group is developing an endo-microscope to image brain tissues in-vivo, however to date, in order to validate our technology the easiest type of samples we can access are fixed samples. However, the fixation is still challenging. For that, we aim through this study to determine whether we should pursue to work on fixed samples or we should shift to work on fresh biopsies. Data were collected on spectroscopic, lifetime measurement and fluorescence imaging setups with visible and two-photon excitations wavelengths. Five fresh and five fixed samples are involved in the experiment. Endogenous fluorescence of fixed biopsies were calculated. Experimental results reveal that at 405 nm and 810 nm, the fresh samples have an intensity of fluorescence two times higher than that of fixed samples. However, for each fluorophore and each excitation wavelength, the lifetime for fresh samples is shorter than that for fixed samples. Still, further studies and investigations involving the comparison between different samples are required to strengthen our findings

Analysis and extraction of complexity parameters of biomedical signals

L'analyse de séries temporelles biomédicales chaotiques tirées de systèmes dynamiques non-linéaires est toujours un challenge difficile à relever puisque dans certains cas bien spécifiques les techniques existantes basées sur les multi-fractales, les entropies et les graphes de récurrence échouent. Pour contourner les limitations des invariants précédents, de nouveaux descripteurs peuvent être proposés. Dans ce travail de recherche nos contributions ont porté à la fois sur l’amélioration d’indicateurs multifractaux (basés sur une fonction de structure) et entropiques (approchées) mais aussi sur des indicateurs de récurrences (non biaisés). Ces différents indicateurs ont été développés avec pour objectif majeur d’améliorer la discrimination entre des signaux de complexité différente ou d’améliorer la détection de transitions ou de changements de régime du système étudié. Ces changements agissant directement sur l’irrégularité du signal, des mouvements browniens fractionnaires et des signaux tirés du système du Lorenz ont été testés. Ces nouveaux descripteurs ont aussi été validés pour discriminer des fœtus en souffrance de fœtus sains durant le troisième trimestre de grossesse. Des mesures statistiques telles que l’erreur relative, l’écart type, la spécificité, la sensibilité ou la précision ont été utilisées pour évaluer les performances de la détection ou de la classification. Le fort potentiel de ces nouveaux invariants nous laisse penser qu’ils pourraient constituer une forte valeur ajoutée dans l’aide au diagnostic s’ils étaient implémentés dans des logiciels de post-traitement ou dans des dispositifs biomédicaux. Enfin, bien que ces différentes méthodes aient été validées exclusivement sur des signaux fœtaux, une future étude incluant des signaux tirés d’autres systèmes dynamiques nonlinéaires sera réalisée pour confirmer leurs bonnes performances.The analysis of biomedical time series derived from nonlinear dynamic systems is challenging due to the chaotic nature of these time series. Only few classical parameters can be detected by clinicians to opt the state of patients and fetuses. Though there exist valuable complexity invariants such as multi-fractal parameters, entropies and recurrence plot, they were unsatisfactory in certain cases. To overcome this limitation, we propose in this dissertation new entropy invariants, we contributed to multi-fractal analysis and we developed signal-based (unbiased) recurrence plots based on the dynamic transitions of time series. Principally, we aim to improve the discrimination between healthy and distressed biomedical systems, particularly fetuses by processing the time series using our techniques. These techniques were either validated on Lorenz system, logistic maps or fractional Brownian motions modeling chaotic and random time series. Then the techniques were applied to real fetus heart rate signals recorded in the third trimester of pregnancy. Statistical measures comprising the relative errors, standard deviation, sensitivity, specificity, precision or accuracy were employed to evaluate the performance of detection. Elevated discernment outcomes were realized by the high-order entropy invariants. Multi-fractal analysis using a structure function enhances the detection of medical fetal states. Unbiased cross-determinism invariant amended the discrimination process. The significance of our techniques lies behind their post-processing codes which could build up cutting-edge portable machines offering advanced discrimination and detection of Intrauterine Growth Restriction prior to fetal death. This work was devoted to Fetal Heart Rates but time series generated by alternative nonlinear dynamic systems should be further considered