Bio-Microfluidics Real-Time Monitoring Using CNN Technology

A 3D-Printed Micro-Optofluidic Chamber for Fluid Characterization and Microparticle Velocity Detection

This work proposes a multi-objective polydimethylsiloxane (PDMS) micro-optofluidic (MoF) device suitably designed and manufactured through a 3D-printed-based master-slave approach. It exploits optical detection techniques to characterize immiscible fluids or microparticles in suspension inside a compartment specifically designed at the core of the device referred to as the MoF chamber. In addition, we show our novel, fast, and cost-effective methodology, dual-slit particle signal velocimetry (DPSV), for fluids and microparticle velocity detection. Different from the standard state-of-the-art approaches, the methodology focuses on signal processing rather than image processing. This alternative has several advantages, including the ability to circumvent the requirement of complex and extensive setups and cost reduction. Additionally, its rapid processing speed allows for real-time sample manipulations in ongoing image-based analyses. For our specific design, optical signals have been detected from the micro-optics components placed in two slots designed ad hoc in the device. To show the devices' multipurpose capabilities, the device has been tested with fluids of various colors and densities and the inclusion of synthetic microparticles. Additionally, several experiments have been conducted to prove the effectiveness of the DPSV approach in estimating microparticle velocities. A digital particle image velocimetry (DPIV)-based approach has been used as a baseline against which the outcomes of our methods have been evaluated. The combination of the suitability of the micro-optical components for integration, along with the MoF chamber device and the DPSV approach, demonstrates a proof of concept towards the challenge of real-time total-on-chip analysis.

An Optimal Design of an Electromagnetic Actuation System towards a Large Homogeneous Magnetic Field and Accessible Workspace for Magnetic Manipulation

Untethered nano-/microrobots have been appealing to biomedical applications under magnetic guidance. Numerous actuation systems are specifically designed to generate either uniform or non-uniform fields which are unable to support all actuating mechanisms of magnetic robots. The size of their accessible space does not enable applications in life sciences (e.g., placing around human parts for tasks or an in vivo experiment in animals). Moreover, homogeneity of uniform magnetic fields is limited in a small region. Here, we propose an electromagnetic coil system that is optimally designed based on numerical simulation investigations to derestrict the mentioned constraints. The built-up system provides a large bore in which magnetic field generation by passing a 10 A current is strong enough for nano-/micromanipulation switchable between uniformity in a large-homogeneous region about 50-mm-wide along the x- and y-axes and 80-mm-wide along the z-axis, and with a non-uniformity of about 12 mT with 100 mT/m. It experimentally carries out potential and versatile controls to manipulate several commonly used microrobots that require a particular type of magnetic field to perform multi-DOF locomotion in diverse viscous environments. (e.g., helical propulsion by rotating magnetic field in the 3D-large workspace and in the complex network path, side-to-side sweeping-slip locomotion by oscillating fields, translation and rocking-slip locomotion by gradient-based fields). Besides, the system can be reproduced into any accessible space size regarding the square coil size to support diverse applications and guarantee the result in both uniformity of magnetic field in the large homogeneous region and a sufficiently strong gradient over the workspace.

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.

Real-time machine vision FPGA implementation for microfluidic monitoring on Lab-on-Chips

A machine vision implementation on a field-programmable gate array (FPGA) device for real-time microfluidic monitoring on Lab-On-Chips is presented in this paper. The machine vision system is designed to follow continuous or plug flows, for which the menisci of the fluids are always visible. The system discriminates between the front or "head" of the flow and the back or "tail" and is able to follow flows with a maximum speed of 20 mm/sec in circular channels of a diameter of 200 μm (corresponding to approx. 60 μl/sec ). It is designed to be part of a complete Point-of-Care system, which will be portable and operate in non-ideal laboratory conditions. Thus, it is able to cope with noise due to lighting conditions and small LoC displacements during the experiment execution. The machine vision system can be used for a variety of LoC devices, without the need for fiducial markers (such as redundancy patterns) for its operation. The underlying application requirements called for a complete hardware implementation. The architecture uses a variety of techniques to improve performance and minimize memory access requirements. The system input is 8 bit grayscale uncompressed video of up to 1 Mpixel resolution. The system uses an operating frequency of 170 Mhz and achieves a computational time of 13.97 ms (worst case), which leads to a throughput of 71.6 fps for 1 Mpixel video resolution.

Automatic cell segmentation and nuclear-to-cytoplasmic ratio analysis for third harmonic generated microscopy medical images

Traditional biopsy procedures require invasive tissue removal from a living subject, followed by time-consuming and complicated processes, so noninvasive in vivo virtual biopsy, which possesses the ability to obtain exhaustive tissue images without removing tissues, is highly desired. Some sets of in vivo virtual biopsy images provided by healthy volunteers were processed by the proposed cell segmentation approach, which is based on the watershed-based approach and the concept of convergence index filter for automatic cell segmentation. Experimental results suggest that the proposed algorithm not only reveals high accuracy for cell segmentation but also has dramatic potential for noninvasive analysis of cell nuclear-to-cytoplasmic ratio (NC ratio), which is important in identifying or detecting early symptoms of diseases with abnormal NC ratios, such as skin cancers during clinical diagnosis via medical imaging analysis.

Functional optical imaging at the microscopic level

Functional microscopic imaging of in vivo tissues aims at characterizing parameters at the level of the unitary cellular components under normal conditions, in the presence of blood flow, to understand and monitor phenomena that lead to maintaining homeostatic balance. Of principal interest are the setting of shear stress on the endothelium; formation of the plasma layer, where the balance between nitric oxide production and scavenging is established; and formation of the oxygen gradients that determine the distribution of oxygen from blood into the tissue. Optical techniques that enable the analysis of functional microvascular processes are the measurement of blood vessel dimensions by image shearing, the photometric analysis of the extent of the plasma layer, the dual-slit methodology for measuring blood flow velocity, and the direct measurement of oxygen concentration in blood and tissue. Each of these technologies includes the development of paired, related mathematical approaches that enable characterizing the transport properties of the blood tissue system. While the technology has been successful in analyzing the living tissue in experimental conditions, deployment to clinical settings remains an elusive goal, due to the difficulty of obtaining optical access to the depth of the tissue.