Projection Micro-Stereolithography to Manufacture a Biocompatible Micro-Optofluidic Device for Cell Concentration Monitoring.

In this work, a 3D printed biocompatible micro-optofluidic (MoF) device for two-phase flow monitoring is presented. Both an air-water bi-phase flow and a two-phase mixture composed of micrometric cells suspended on a liquid solution were successfully controlled and monitored through its use. To manufacture the MoF device, a highly innovative microprecision 3D printing technique was used named Projection Microstereolithography (PμSL) in combination with the use of a novel 3D printable photocurable resin suitable for biological and biomedical applications.

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 . In addition, we show our novel, fast, and cost-effective methodology, dual-slit particle signal velocimetry (DPSV), for fluids and microparticle velocity detection.

A Regression Approach to Model Refractive Index Measurements of Novel 3D Printable Photocurable Resins for Micro-Optofluidic Applications.

In this work, a quadratic polynomial regression model was developed to aid practitioners in the determination of the refractive index value of transparent 3D printable photocurable resins usable for micro-optofluidic applications. The model was experimentally determined by correlating empirical optical transmission measurements (the ) to known refractive index values (the ) of photocurable materials used in optics, thus obtaining a related regression equation. In detail, a novel, simple, and cost-effective experimental setup is proposed in this study for the first time for collecting the transmission measurements of smooth 3D printed samples (roughness ranging between 0.

Cell counting and velocity algorithms for hydrodynamic study of unsteady biological flows in micro-channels.

In this paper, the combination of two algorithms, a cell counting algorithm and a velocity algorithm based on a Digital Particle Image Velocimetry (DPIV) method, is presented to study the collective behavior of micro-particles in response to hydrodynamic stimuli. A wide experimental campaign was conducted using micro-particles of different natures and diameters (from to ), such as living cells and silica beads. The biological fluids were injected at the inlet of a micro-channel with an external oscillating flow, and the process was monitored in an investigated area, simultaneously, through a CCD camera and a photo-detector.

Cortical networks underlying successful control of nociceptive processing using real-time fMRI.

Real-time fMRI (rt-fMRI) enables self-regulation of neural activity in localized brain regions through neurofeedback. Previous studies showed successful up- and down-regulation of neural activity in the anterior cingulate cortex (ACC) and the insula (Ins) during nociceptive stimulation. Such self-regulation capacity is, however, variable across subjects, possibly related to the ability of cognitive top-down control of pain.

3D Printing Manufacturing of Polydimethyl-Siloxane/Zinc Oxide Micro-Optofluidic Device for Two-Phase Flows Control.

Tailored ZnO surface functionalization was performed inside a polydimethyl-siloxane (PDMS) microchannel of a micro-optofluidic device () to modulate its surface hydrophobicity to develop a method for fine tuning the fluid dynamics inside a microchannel. The wetting behavior of the surface is of particular importance if two different phases are used for system operations. Therefore, the fluid dynamic behavior of two immiscible fluids, (i) air-water and (ii) air-glycerol/water in PDMS and ZnO-PDMS was investigated by using different experimental conditions.

Remote Ultrasound Scan Procedures with Medical Robots: Towards New Perspectives between Medicine and Engineering.

Background: This review explores state-of-the-art teleoperated robots for medical ultrasound scan procedures, providing a comprehensive look including the recent trends arising from the COVID-19 pandemic.

Methods: Physicians' experience is included to indicate the importance of their role in the design of improved medical robots. From this perspective, novel classes of equipment for remote diagnostics based on medical robotics are discussed in terms of innovative engineering technologies.

3D-Printed micro-optofluidic device for chemical fluids and cells detection.

In this work, it is presented a micro-optofluidic flow detector used for on-chip biological and chemical samples investigation. It is made in Poly-dimethyl-siloxane using a master-slave approach based on the 3D-Printing techniques. The micro-optofluidic device is made by assembling a microfluidic T-junction with a micro-optical section that consists of two optical fiber insertions and a PDMS gold-spattered micro-waveguide.

A polymeric micro-optical interface for flow monitoring in biomicrofluidics.

We describe design and miniaturization of a polymeric optical interface for flow monitoring in biomicrofluidics applications based on polydimethylsiloxane technology, providing optical transparency and compatibility with biological tissues. Design and ray tracing simulation are presented as well as device realization and optical analysis of flow dynamics in microscopic blood vessels. Optics characterization of this polymeric microinterface in dynamic experimental conditions provides a proof of concept for the application of the device to two-phase flow monitoring in both in vitro experiments and in vivo microcirculation investigations.

An environment for complex behaviour detection in bio-potential experiments.

We propose BioS (Bio-potential Study) as a new virtual data analysis and management environment. It was devised to cope with the physiological signals, in order to manage different data using advanced methods of analysis and to find a simple way to decode and interpret data. BioS has been structured as a flexible, modular, and portable environment.

An innovative opto-sensing workbench for bio-microfluidics monitoring and control.

A non-invasive real-time testing workbench for the opto-electric characterization of microfluidic phenomena and particle transport tracking is proposed. It consists of an automated monitoring of microfluidodynamic phenomena, exploiting suitable opto-sensing setup, analog-digital and analog real-time monitoring, and an adaptive control system. The opto-sensing setup is based on a customized opto-mechanic system designed and developed using discrete optic components mounted on a breadboard.

Mapping heart dynamics by using nonlinear indicators.

A novel approach for the nonlinear characterization of Electrocardiogram (ECG) signals has been developed. The new developed methodology is based on a numerical algorithm that extracts the value of dinfinity (d-infinite) characterizing the asymptotic chaotic behavior of a system. This algorithm also extracts a measure of the maximum Lyapunov exponent and it is applicable to time series where the knowledge of the system structure and laws is not necessary.

BioS: a new tool for biopotential experiments.

BioS (Bio-potential Study), a novel environment for Biopotential analysis is here proposed. It provides the processing of biopotentials of any number of channels distributed with different geometry. It includes several features as data importing, data visualization (1D, 2D, 3D), preprocessing (frequency & saturation filtering, statistical analysis), spatio-temporal processing (power spectrum analysis, nonlinear analysis, independent component analysis both in the spatial and time domain).

Complementary methods for interpreting brain signals: linear versus nonlinear techniques.

Magnetoencephalography (MEG) brain signals are characterized using both linear and nonlinear dynamical methods. The linear approach employs the power analysis in a spatial visualization. The nonlinear approach estimates the value of d(infinity) to characterize the system's asymptotic chaotic behavior using a computationally less onerous method than the conventional one for d(infinity).

Complex spatio-temporal features in meg data.

Magnetoencephalography (MEG) brain signals are studied using a method for characterizing complex nonlinear dynamics. This approach uses the value of d(infinity) (d-infinite) to characterize the system's asymptotic chaotic behavior. A novel procedure has been developed to extract this parameter from time series when the system's structure and laws are unknown.