Encapsulation of Catheter-tip Pressure Sensor using Silicone Elastomer 

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Chapter 2. Piezoresistive MEMS Pressure Sensors

Various technologies exist for measurement of pressure including but not limited to:
piezoresistive, capacitive, optical and resonant. Discrepancies between sensor technologies include size, cost, pressure range, accuracy, resolution, packaging and other functional parameters such as operational temperature [118]. In this Chapter, different technologies are discussed with emphasis on their suitability for use in long-term ICP monitoring. A novel instrumentation rig developed to screen sensors is presented, followed by studies performed ton identify MEMS pressure sensors suitable for long-term monitoring. Comparison of various technologies available for this study requires careful analysis of practical technology limitations critical for lifetime implantation. High risk factors crucial to lifetime implantation include but are not limited to [63]:
• Simple compact interfacing between sensor and transmitter;
• Small enough to be clinically insignificant;
• Insignificant drift over the implantation lifetime;
• Compatibility with modern imaging techniques;
• Hermetically sealable and biocompatibility.
Of the membrane based sensors, capacitive and piezoresistive are the most common, with the former exhibiting higher-pressure sensitivity and lower thermal drift. However, unlike capacitive sensors, piezoresistive sensors do not require in situ amplification [1], [2], minimizing the required volume and seeing exclusive use in catheter-tip sensors.All sensors transduce physiological parameters via a transfer function, describing the relationship between the parameter and the sensor’s response under different conditions. To minimize complexity, it is preferential for this transfer function to be linear as shown by Equation.Here the function gradient is denoted ?, representing the device sensitivity over a specified linear range. The transfer function also determines the device calibration coefficients, which are typically determined during manufacturing and supplied with the device. Equation . represents the ideal operation of a linear sensor, neglecting real world effects. Noise and interference are described as the stochastic fluctuation of an output signal, where the former is internally generated and the latter is adsorbed from external sources [119]. Typical sources of noise and interference include: thermal fluctuations, electromagnetic interference, sensing element instability, electronic instability, mechanical vibrations, light and fluid flow artefacts [119]. Given the diverse range of possible noise and interference contributors it is not surprising that sensors are often sensitive to a plethora of physiological parameters which can also interfere with measurement accuracy. This is known as sensor selectivity, where a common example in piezoresistive pressure sensors is temperature sensitivity, which requires some form of compensation. Real world sensors are also subject to limited response rates to changes in physiological states, necessitating a settling time to maximise measurement accuracy.Furthermore, the limited response rate also limits sensor bandwidth, as the sensor may not reach stability before the parameter of interest changes [119]. Identifying and ameliorating drift is difficult without studying device components and construction processes in isolation. In this Chapter, a heuristic bottom-up approach is employed, partitioning the conventional catheter-tip sensor into two fundamental components:
the bare MEMS sensor and its interconnecting wires.

The Piezoresisitve Effect

In 1856, William Thomson (also known as Lord Kelvin) observed a change in resistance in both copper and iron wires when tensile stress was applied. Furthermore, William reported that the change in resistance was not only dependant on material elongation but also varied between copper and iron when elongation was constrained [120]. This geometrically dependant effect was coined “Piezoresistance” by Cookson [121], derived from Greek Piezem, meaning to press, and resistance, describing a change in electrical conductivity. The homogenous electrical resistance of a material (?) can be described by Equation .

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Table of Contents
List of Figures
List of Tables 
Nomenclature 
Chapter 1. Introduction 
1.1. Hydrocephalus
1.1.1 Pathophysiology
1.1.2 Etiologies and Implications.
1.1.3 Incidence and Prognosis
1.2. Treatment: The Drainage Shunt
1.2.1 Shunt Complications
1.2.2 Clinical Features of Shunt Malfunction and Diagnosis
1.2.3 Financial Cost of Hydrocephalus and Shunt Revisions
1.3. ICP Monitoring 
1.3.1 Percutaneous Acute Monitoring of Hydrocephalus
1.3.2 Fully Implantable Chronic Monitoring of Hydrocephalus
1.4. Device Requirements for Fully Implantable ICP Monitors
1.4.1 Sensor Stability and Lifetime
1.4.2 MRI Compatibility
1.4.3 Biocompatibility
1.4.4 Hermeticity, Sensitivity and Package Size
1.4.5 Measurement Range of Absolute ICP Sensors
1.4.6 Summary of Device Requirements
1.5. Scope and Objectives
Chapter 2. Piezoresistive MEMS Pressure Sensors
2.1. The Piezoresisitve Effect 
2.2. Piezoresistive MEMS Pressure Sensor
2.3. Instrumentation for Long-term Measurement of Drift 
2.3.1 Sensor Receptacle
2.3.2 Instrumentation
2.3.3 Thermal compensation
2.3.4 Complete Setup
2.3.5 Calibration Fidelity
2.4. Long-term Drift in the P41 Family of Sensors
2.5. Wiring Methods: Ultrasonic Wire Bonding Versus Soldering 
2.5.1 Ultrasonic Wire Bonding
2.5.2 Ultrasonic Parameter Optimization
2.5.3 Drift in P41 Sensors Bonded with Ultrasonic Wire bonding
2.6. Long-term Drift in the P330 Family of Sensors
2.7. Summary 
Chapter 3. Encapsulation of Catheter-tip Pressure Sensor using Silicone Elastomer 
3.1. Polymer Encapsulation of Implantable Devices
3.2. Catheter-tip P330 Sensor Encapsulated for Biocompatibility and Moisture Protection
3.3. Mass Gain of Silicone Encapsulation Layers in Catheter-tip Sensors 
3.4. DC Excitation of Catheter-tip Sensors
3.4.1 Drift of Encapsulated Catheter-tip Sensor in Absence of Moisture
3.4.2 Drift of Encapsulated Catheter-tip Sensor Hydrated with Saline
3.5. Electrically Neutral Excitation of Catheter-tip Sensors
3.5.1 Excitation and Sampling Rate
3.5.2 Drift with Various Electrical Excitation Patterns
3.6. Kaplan-Meier Analysis
3.7. Summary 
Chapter 4. Encapsulation of MEMS Pressure Sensors using Thin Film Atomic Layer Deposition 
4.1. Atomic Layer Deposition of Thin Films 
4.2. Modelling Moisture Permeation Through Single Layer Al2O3 Thin Films
4.3. Mechanical Modelling of Pressure Sensor Coated in Single Layer Al2O3 Thin Films
4.4. Al2O3 as a Thin Film Moisture Barrier 
4.4.1 Experiment setup
4.4.2 Effect of Vacuum on Sensor Performance
4.4.3 Al2O3 ALD Coating of MEMS Pressure Sensors
4.4.4 Effect of Al2O3 Coating on Sensor Performance
4.4.5 Hydration of Al2O3 ALD Coated Pressure Sensors
4.5. Al2O3/TiO2 Bilayers as a Thin Film Moisture Barrier
4.5.1 Al2O3/TiO2 Bilayer Coating of MEMS Pressure Sensors
4.5.2 Effect of Al2O3/TiO2 Thin Film on Sensor Performance
4.5.3 Hydration of Al2O3/TiO2 ALD Coated Pressure Sensors
4.6. Summary 
Chapter 5. Metal Enclosure as a Moisture Protection Barrier for MEMS Pressure Sensors
5.1. Operating Principles and Constraints 
5.2. Sensor Media Compatibility
5.3. The Electrical Feed-through
5.4. Titanium as a Diaphragm 
5.5. Joining Dissimilar Metals
5.6. Enclosure Design
5.7. Assembly of the Implantable Device 
5.8. Flat Diaphragm Mechanical Modelling 
5.8.1 Validating the Model
5.8.2 Pressure Transmission and Thermal Pressure Modelling
5.9. Bench-top Testing 
5.10. Summary
Chapter 6. Conclusion and Future Work 
6.1. Contributions 
6.2. Publications
6.3. Future Work
References

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Lifetime Monitoring of Pressure from an Implanted Sensor

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