Microfluidics in Haemostasis: a Review

Haemostatic disorders are both complex and costly in relation to both their treatment and subsequent management. As leading causes of mortality worldwide, there is an ever-increasing drive to improve the diagnosis and prevention of haemostatic disorders. The field of microfluidic and Lab on a Chip (LOC) technologies is rapidly advancing and the important role of miniaturised diagnostics is becoming more evident in the healthcare system, with particular importance in near patient testing (NPT) and point of care (POC) settings. Microfluidic technologies present innovative solutions to diagnostic and clinical challenges which have the knock-on effect of improving health care and quality of life. In this review, both advanced microfluidic devices (R&D) and commercially available devices for the diagnosis and monitoring of haemostasis-related disorders and antithrombotic therapies, respectively, are discussed. Innovative design specifications, fabrication techniques, and modes of detection in addition to the materials used in developing micro-channels are reviewed in the context of application to the field of haemostasi

Towards A Graphene Chip System For Blood Clotting Disease Diagnostics

Point of care diagnostics (POCD) allows the rapid, accurate measurement of analytes near to a patient. This enables faster clinical decision making and can lead to earlier diagnosis and better patient monitoring and treatment. However, despite many prospective POCD devices being developed for a wide range of diseases this promised technology is yet to be translated to a clinical setting due to the lack of a cost-effective biosensing platform.This thesis focuses on the development of a highly sensitive, low cost and scalable biosensor platform that combines graphene with semiconductor fabrication tech-niques to create graphene field-effect transistors biosensor. The key challenges of designing and fabricating a graphene-based biosensor are addressed. This work fo-cuses on a specific platform for blood clotting disease diagnostics, but the platform has the capability of being applied to any disease with a detectable biomarker.Multiple sensor designs were tested during this work that maximised sensor ef-ficiency and costs for different applications. The multiplex design enabled different graphene channels on the same chip to be functionalised with unique chemistry. The Inverted MOSFET design was created, which allows for back gated measurements to be performed whilst keeping the graphene channel open for functionalisation. The Shared Source and Matrix design maximises the total number of sensing channels per chip, resulting in the most cost-effective fabrication approach for a graphene-based sensor (decreasing cost per channel from £9.72 to £4.11).The challenge of integrating graphene into a semiconductor fabrication process is also addressed through the development of a novel vacuum transfer method-ology that allows photoresist free transfer. The two main fabrication processes; graphene supplied on the wafer “Pre-Transfer” and graphene transferred after met-allisation “Post-Transfer” were compared in terms of graphene channel resistance and graphene end quality (defect density and photoresist). The Post-Transfer pro-cess higher quality (less damage, residue and doping, confirmed by Raman spec-troscopy).Following sensor fabrication, the next stages of creating a sensor platform involve the passivation and packaging of the sensor chip. Different approaches using dielec-tric deposition approaches are compared for passivation. Molecular Vapour Deposi-tion (MVD) deposited Al2O3 was shown to produce graphene channels with lower damage than unprocessed graphene, and also improves graphene doping bringing the Dirac point of the graphene close to 0 V. The packaging integration of microfluidics is investigated comparing traditional soft lithography approaches and the new 3D printed microfluidic approach. Specific microfluidic packaging for blood separation towards a blood sampling point of care sensor is examined to identify the laminar approach for lower blood cell count, as a method of pre-processing the blood sample before sensing.To test the sensitivity of the Post-Transfer MVD passivated graphene sensor de-veloped in this work, real-time IV measurements were performed to identify throm-bin protein binding in real-time on the graphene surface. The sensor was function-alised using a thrombin specific aptamer solution and real-time IV measurements were performed on the functionalised graphene sensor with a range of biologically relevant protein concentrations. The resulting sensitivity of the graphene sensor was in the 1-100 pg/ml concentration range, producing a resistance change of 0.2% per pg/ml. Specificity was confirmed using a non-thrombin specific aptamer as the neg-ative control. These results indicate that the graphene sensor platform developed in this thesis has the potential as a highly sensitive POCD. The processes developed here can be used to develop graphene sensors for multiple biomarkers in the future

Methods for immobilizing receptors in microfluidic devices: A review

In this review article, we discuss state-of-the-art methods for immobilizing functional receptors in microfluidic devices. Strategies used to immobilize receptors in such devices are essential for the development of specific, sensitive (bio)chemical assays that can be used for a wide range of applications. In the first section, we review the principles and the chemistry of immobilization techniques that are the most commonly used in microfluidics. We afterward describe immobilization methods on static surfaces from microchannel surfaces to electrode surfaces with a particular attention to opportunities offered by hydrogel surfaces. Finally, we discuss immobilization methods on mobile surfaces with an emphasis on both magnetic and non-magnetic microbeads, and finally, we highlight recent developments of new types of mobile supports

Microfluidics for Biosensing and Diagnostics

Efforts to miniaturize sensing and diagnostic devices and to integrate multiple functions into one device have caused massive growth in the field of microfluidics and this integration is now recognized as an important feature of most new diagnostic approaches. These approaches have and continue to change the field of biosensing and diagnostics. In this Special Issue, we present a small collection of works describing microfluidics with applications in biosensing and diagnostics

Microfluidic platform for multiple parameters readouts in a point-of-care

The research is motivated by real applications, such as pasteurization plant, water networks and autonomous system, which each of them require a specific control system to provide proper management able to take into account their particular features and operating limits in presence of uncertainties related to their operation and failures from component breakdowns. According to that most of the real systems have nonlinear behaviors, it can be approximated them by polytopic linear uncertain models such as Linear Parameter Varying (LPV) and Takagi-Sugeno (TS) models. Therefore, a new economic Model Predictive Control (MPC) approach based on LPV/TS models is proposed and the stability of the proposed approach is certified by using a region constraint on the terminal state. Besides, the MPC-LPV strategy is extended based on the system with varying delays affecting states and inputs. The control approach allows the controller to accommodate the scheduling parameters and delay change. By computing the prediction of the state variables and delay along a prediction time horizon, the system model can be modified according to the evaluation of the estimated state and delay at each time instant. To increase the system reliability, anticipate the appearance of faults and reduce the operational costs, actuator health monitoring should be considered. Regarding several types of system failures, different strategies are studied for obtaining system failures. First, the damage is assessed with the rainflow-counting algorithm that allows estimating the component’s fatigue and control objective is modified by adding an extra criterion that takes into account the accumulated damage. Besides, two different health-aware economic predictive control strategies that aim to minimize the damage of components are presented. Then, economic health-aware MPC controller is developed to compute the components and system reliability in the MPC model using an LPV modeling approach and maximizes the availability of the system by estimating system reliability. Additionally, another improvement considers chance-constraint programming to compute an optimal list replenishment policy based on a desired risk acceptability level, managing to dynamically designate safety stocks in flow-based networks to satisfy non-stationary flow demands. Finally, an innovative health-aware control approach for autonomous racing vehicles to simultaneously control it to the driving limits and to follow the desired path based on maximization of the battery RUL. The proposed approach is formulated as an optimal on-line robust LMI based MPC driven from Lyapunov stability and controller gain synthesis solved by LPV-LQR problem in LMI formulation with integral action for tracking the trajectory

Microfluidic platform for multiple parameters readouts in a point-of-care

The research is motivated by real applications, such as pasteurization plant, water networks and autonomous system, which each of them require a specific control system to provide proper management able to take into account their particular features and operating limits in presence of uncertainties related to their operation and failures from component breakdowns. According to that most of the real systems have nonlinear behaviors, it can be approximated them by polytopic linear uncertain models such as Linear Parameter Varying (LPV) and Takagi-Sugeno (TS) models. Therefore, a new economic Model Predictive Control (MPC) approach based on LPV/TS models is proposed and the stability of the proposed approach is certified by using a region constraint on the terminal state. Besides, the MPC-LPV strategy is extended based on the system with varying delays affecting states and inputs. The control approach allows the controller to accommodate the scheduling parameters and delay change. By computing the prediction of the state variables and delay along a prediction time horizon, the system model can be modified according to the evaluation of the estimated state and delay at each time instant. To increase the system reliability, anticipate the appearance of faults and reduce the operational costs, actuator health monitoring should be considered. Regarding several types of system failures, different strategies are studied for obtaining system failures. First, the damage is assessed with the rainflow-counting algorithm that allows estimating the component’s fatigue and control objective is modified by adding an extra criterion that takes into account the accumulated damage. Besides, two different health-aware economic predictive control strategies that aim to minimize the damage of components are presented. Then, economic health-aware MPC controller is developed to compute the components and system reliability in the MPC model using an LPV modeling approach and maximizes the availability of the system by estimating system reliability. Additionally, another improvement considers chance-constraint programming to compute an optimal list replenishment policy based on a desired risk acceptability level, managing to dynamically designate safety stocks in flow-based networks to satisfy non-stationary flow demands. Finally, an innovative health-aware control approach for autonomous racing vehicles to simultaneously control it to the driving limits and to follow the desired path based on maximization of the battery RUL. The proposed approach is formulated as an optimal on-line robust LMI based MPC driven from Lyapunov stability and controller gain synthesis solved by LPV-LQR problem in LMI formulation with integral action for tracking the trajectory

Microfluidic platform for multiple parameters readouts in a point-of-care

Tesi amb una secció retallada per drets de l'editorThe research is motivated by real applications, such as pasteurization plant, water networks and autonomous system, which each of them require a specific control system to provide proper management able to take into account their particular features and operating limits in presence of uncertainties related to their operation and failures from component breakdowns. According to that most of the real systems have nonlinear behaviors, it can be approximated them by polytopic linear uncertain models such as Linear Parameter Varying (LPV) and Takagi-Sugeno (TS) models. Therefore, a new economic Model Predictive Control (MPC) approach based on LPV/TS models is proposed and the stability of the proposed approach is certified by using a region constraint on the terminal state. Besides, the MPC-LPV strategy is extended based on the system with varying delays affecting states and inputs. The control approach allows the controller to accommodate the scheduling parameters and delay change. By computing the prediction of the state variables and delay along a prediction time horizon, the system model can be modified according to the evaluation of the estimated state and delay at each time instant. To increase the system reliability, anticipate the appearance of faults and reduce the operational costs, actuator health monitoring should be considered. Regarding several types of system failures, different strategies are studied for obtaining system failures. First, the damage is assessed with the rainflow-counting algorithm that allows estimating the component’s fatigue and control objective is modified by adding an extra criterion that takes into account the accumulated damage. Besides, two different health-aware economic predictive control strategies that aim to minimize the damage of components are presented. Then, economic health-aware MPC controller is developed to compute the components and system reliability in the MPC model using an LPV modeling approach and maximizes the availability of the system by estimating system reliability. Additionally, another improvement considers chance-constraint programming to compute an optimal list replenishment policy based on a desired risk acceptability level, managing to dynamically designate safety stocks in flow-based networks to satisfy non-stationary flow demands. Finally, an innovative health-aware control approach for autonomous racing vehicles to simultaneously control it to the driving limits and to follow the desired path based on maximization of the battery RUL. The proposed approach is formulated as an optimal on-line robust LMI based MPC driven from Lyapunov stability and controller gain synthesis solved by LPV-LQR problem in LMI formulation with integral action for tracking the trajectory.Postprint (published version

Development of an autonomous lab-on-a-chip system with ion separation and conductivity detection for river water quality monitoring

This thesis discusses the development of a lab on a chip (LOC) ion separation for river water quality monitoring using a capacitively coupled conductivity detector (C⁴D) with a novel baseline suppression technique.Our first interest was to be able to integrate such a detector in a LOC. Different designs (On-capillary design and on-chip design) have been evaluated for their feasibility and their performances. The most suitable design integrated the electrode close to the channel for an enhanced coupling while having the measurement electronics as close as possible to reduce noise. The final chip design used copper tracks from a printed circuit board (PCB) as electrodes, covered by a thin Polydimethylsiloxane (PDMS) layer to act as electrical insulation. The layer containing the channel was made using casting and bonded to the PCB using oxygen plasma. Flow experiments have been conduced to test this design as a detection cell for capacitively coupled contactless conductivity detection (C⁴D).The baseline signal from the system was reduced using a novel baseline suppression technique. Decrease in the background signal increased the dynamic range of the concentration to be measured before saturation occurs. The sensitivity of the detection system was also improved when using the baseline suppression technique. Use of high excitation voltages has proven to increase the sensitivity leading to an estimated limit of detection of 0.0715 μM for NaCl (0.0041 mg/L).The project also required the production of an autonomous system capable of operating for an extensive period of time without human intervention. Designing such a system involved the investigation of faults which can occur in autonomous system for the in-situ monitoring of water quality. Identification of possible faults (Bubble, pump failure, etc.) and detection methods have been investigated. In-depth details are given on the software and hardware architecture constituting this autonomous system and its controlling software

Sensors and Biosensors for C-Reactive Protein, Temperature and pH, and Their Applications for Monitoring Wound Healing: A Review

Wound assessment is usually performed in hospitals or specialized labs. However, since patients spend most of their time at home, a remote real time wound monitoring would help providing a better care and improving the healing rate. This review describes the advances in sensors and biosensors for monitoring the concentration of C-reactive protein (CRP), temperature and pH in wounds. These three parameters can be used as qualitative biomarkers to assess the wound status and the effectiveness of therapy. CRP biosensors can be classified in: (a) field effect transistors, (b) optical immunosensors based on surface plasmon resonance, total internal reflection, fluorescence and chemiluminescence, (c) electrochemical sensors based on potentiometry, amperometry, and electrochemical impedance, and (d) piezoresistive sensors, such as quartz crystal microbalances and microcantilevers. The last section reports the most recent developments for wearable non-invasive temperature and pH sensors suitable for wound monitoring