Emergent behaviors in RBCs flows in micro-channels using digital particle image velocimetry.

The key points in the design of microfluidic Lab-On-a-Chips for blood tests are the simplicity of the microfluidic chip geometry, the portability of the monitoring system and the ease on-chip integration of the data analysis procedure. The majority of those, recently designed, have been used for blood separation, however their introduction, also, for pathological conditions diagnosis would be important in different biomedical contexts. To overcome this lack is necessary to establish the relation between the RBCs flow and blood viscosity changes in micro-vessels. For that, the development of methods to analyze the dynamics of the RBCs flows in networks of micro-channels becomes essential in the study of RBCs flows in micro-vascular networks. A simplification in the experimental set-up and in the approach for the data collection and analysis could contribute significantly to understand the relation between the blood non-Newtonian properties and the emergent behaviors in collective RBCs flows. In this paper, we have investigated the collective behaviors of RBCs in a micro-channel in unsteady conditions, using a simplified monitoring set-up and implementing a 2D image processing procedure based on the digital particle image velocimetry. Our experimental study consisted in the analysis of RBCs motions freely in the micro-channel and driven by an external pressure. Despite the equipment minimal complexity, the advanced signal processing method implemented has allowed a significant qualitative and quantitative classification of the RBCs behaviors and the dynamical characterization of the particles velocities along both the horizontal and vertical directions. The concurrent causes for the particles displacement as the base solution-particles interaction, particle-particle interaction, and the external force due to pressure gradient were accounted in the results interpretation. The method implemented and the results obtained represent a proof of concept toward the realization of a general-purpose microfluidic LOC device for in-vitro flow analysis of RBCs collective behaviors.

Red blood cells flows in rectilinear microfluidic chip.

The red blood cells flow in a controlled environment as a microfluidic chip with a rectilinear geometry was investigated. The optical monitoring performed by an automatic Particle Image Velocimetry procedure has allowed a quantitative analysis on flow features. Various parameters such as velocity, shear rate, strain rate, vorticity, divergence were extracted. The comparisons of the results obtained from the different experiments was used for the overall understanding of the RBC movements in different conditions and the establishment of the analysis procedure.

Automatic preprocessing of EEG signals in long time scale.

Electroencephalography (EEG) signals are highly affected by physiological artifacts. Establishing a robust and repeatable EEG pre-processing is fundamental to overcome this issue and be able to use fully EEG data especially in long time scale experiments. In this work, starting from the Independent Component Analysis (ICA) of the EEG data, a control feedback scheme aiming to manage the cleaning of the independent component signals in an automatic way avoiding cut-bind solutions is presented, both with and without co-registrations. The method implemented combines different approaches based on the residual artifact contents check, identification and cleaning. The results of this procedure are shown on a test dataset. This analysis tool is embedded as core module, in a platform that can manage the automatic clearing of EEG recordings for multiple-subjects studies.

Bio-Microfluidics Real-Time Monitoring Using CNN Technology.

A new non-invasive real-time system for the monitoring and control of microfluidodynamic phenomena involving transport of particles and two phase fluids is proposed. The general purpose design of such system is suitable for in vitro and in vivo experimental setup and, therefore, for microfluidic applications in the biomedical field, such as lab-on-chip and for research studies in the field of microcirculation. The system consists of an ad hoc optical setup for image magnification providing images suitable for acquisition and processing. The main feature of the optical system is the accessibility of the information at any point of the optical path. It was designed and developed using discrete opto-mechanic components mounted on a breadboard. The optical sensing, acquisition, and processing were all performed using an integrated vision system based on cellular nonlinear networks (CNNs) analogic (analog plus logic) technology called focal plane processor (FPP, Eye-RIS, Anafocus) that was inserted in the optical path. Ad hoc algorithms were implemented for the real-time analysis and extraction of fluidodynamic parameters in micro-channels. They were firstly tested on sequences of images recorded during in vivo microcirculation experiments on hamsters and then applied on images acquired and processed in real-time during in vitro experiments on two-phase fluid flow in a continuous microfluidic device (serpentine mixer, ThinXXS).

A cellular nonlinear network: real-time technology for the analysis of microfluidic phenomena in blood vessels.

A new approach to the observation and analysis of dynamic structural and functional parameters in the microcirculation is described. The new non-invasive optical system is based on cellular nonlinear networks (CNNs), highly integrated analogue processor arrays whose processing elements, the cells, interact directly within a finite local neighbourhood. CNNs, thanks to their parallel processing feature and spatially distributed structure, are widely used to solve high-speed image processing and recognition problems and in the description and modelling of biological dynamics through the solution of time continuous partial differential equations (PDEs). They are therefore considered extremely suitable for spatial-temporal dynamic characterization of fluidic phenomena at micrometric to nanometric scales, such as blood flow in microvessels and its interaction with the cells of the vessel wall. A CNN universal machine (CNN-UM) structure was used to implement, via simulation and hardware (ACE16k), the algorithms to determine the functional capillarity density (FCD) and red blood cell velocity (RBCV) in capillaries obtained by intravital microscopy during in vivo experiments on hamsters. The system exploits the moving particles to distinguish the functional capillaries from the stationary background. This information is used to reconstruct a map and to calculate the velocity of the moving objects.

A nonlinear circuit architecture for magnetoencephalographic signal analysis.

OBJECTIVES: The objective of this paper was to face the complex spatio-temporal dynamics shown by Magnetoencephalography (MEG) data by applying a nonlinear distributed approach for the Blind Sources Separation. The effort was to characterize and differ-entiate the phases of a yogic respiratory exercise used in the treatment of obsessive compulsive disorders. METHODS: The patient performed a precise respiratory protocol, at one breath per minute for 31 minutes, with 10 minutes resting phase before and after. The two steps of classical Independent Component Approach have been performed by using a Cellular Neural Network with two sets of templates. The choice of the couple of suitable templates has been carried out using genetic algorithm optimization techniques. RESULTS: Performing BSS with a nonlinear distributed approach, the outputs of the CNN have been compared to the ICA ones. In all the protocol phases, the main components founded with CNN have similar trends compared with that ones obtained with ICA. Moreover, using this distributed approach, a spatial location has been associated to each component. CONCLUSIONS: To underline the spatio-temporal and the nonlinearly of the neural process a distributed nonlinear architecture has been proposed. This strategy has been designed in order to overcome the hypothesis of linear combination among the sources signals, that is characteristic of the ICA approach, taking advantage of the spatial information.

Real time blood flow velocity monitoring in the microcirculation.

A real-time monitoring system based on the dual slit methodology for the characterization of the red blood cell velocity at the level of microcirculation has been developed. The analog photometric signals are acquired and processed using a hybrid hardware-software system that exploits a A/D conversion and an optimized correlation algorithm on an embedded system. It is implemented exploiting the resources of a general purpose board capable to extract the useful information from the noisy photometric signals, to process them, to show and save the results and, therefore, to make the experiments reproducible. Two different approaches to the crosscorrelation algorithm have been tested and their performances have been compared to each. The system has been tested in in vivo experiments on anaesthetized hamsters. Several microvessels have been observed and the results have been compared to the output of an analog crosscorrelator to verify their coherence.

Real-time estimation of oxygen concentration in micro-hemo-vessels.

In this paper, a real-time measurement system for non-invasive evaluation of oxygen concentration (PO2) at the microcirculation level is developed. The system has been designed by exploiting the phenomenon of fluorescence quenching. The skin of an anaesthetized hamster, injected with porphyrin, is lighted with pulses; the fluorophore reacts with the oxygen in the blood, producing a fluorescence signal, and the value of the fluorescence lifetime is related to the oxygen concentration. This microcirculation-based instrumentation consists of an electro-optical system, a control circuit and signal processing procedure. The system allows the measurement of PO2 in the range of 0-700 (mmHg) with a standard deviation of 4 (mmHg). Several experiments have been performed in order to characterize and test this system.