Inductively Powered Implantable System with Far-field Data Transmitter for an Intracranial Pressure Monitoring Application: Design and Performance Validation

Monitoring of the intracranial pressure (ICP) is an essential activity for many brain diseases and injuries. For an adult, ICP value is between 7 mmHg to 15 mmHg . However, for a critically ill patient, the ICP should be maintained below 20 mmHg. Therefore, continuous monitoring of ICP is a life-saving activity. Several invasive and non-invasive methods have been proposed for monitoring of the ICP. However, invasive methods cannot be used for continuous monitoring of the ICP due to the risk of infection. Moreover, non-invasive methods lack in accuracy.Therefore, many researchers reported battery-powered or fully passive implantable systems. However, a battery-powered implant has limited life and large size. On the other hand, in a fully passive implant the readout distance is relatively small in comparison with a battery-powered implant due to its zero-power operation.In contrast, this work presents the development of an inductively powered implantable system equipped with a data transmission unit for an ICP monitoring application. The developed system has three main parts: an implant or in-body unit, an on-body unit and an off-body unit. The on-body unit powers the implant through inductive near-field link. After the activation, the implant, consists of a piezoresistive pressure sensor and a data transmission unit, transmits the pressure signal at the industrial, scientific, and medical radio (ISM) band of 2.45 GHz. The off-body unit receives the transmitted signal from the implant and estimates the pressure value.The simulation and the measurement results of both near-filed and far-field links are presented. After the development of the system, the pressue readout measurement results have been presented in the air, water and in a setting mimicking the human head dielectric properties. For biocompatibility, the implant is coated with biocompatible adhesive silicone. The effect of coating on both wireless links has also been studied.Finally, this work also presents the effect of misalignment between the inductively coupled antennas on the pressure readout accuracy of the developed ICP monitoring system and discusses the solution to overcome this impact. The thesis also presents the response of the developed ICP monitoring system with the change in the temperature

Beyond Tissue replacement: The Emerging role of smart implants in healthcare

Smart implants are increasingly used to treat various diseases, track patient status, and restore tissue and organ function. These devices support internal organs, actively stimulate nerves, and monitor essential functions. With continuous monitoring or stimulation, patient observation quality and subsequent treatment can be improved. Additionally, using biodegradable and entirely excreted implant materials eliminates the need for surgical removal, providing a patient-friendly solution. In this review, we classify smart implants and discuss the latest prototypes, materials, and technologies employed in their creation. Our focus lies in exploring medical devices beyond replacing an organ or tissue and incorporating new functionality through sensors and electronic circuits. We also examine the advantages, opportunities, and challenges of creating implantable devices that preserve all critical functions. By presenting an in-depth overview of the current state-of-the-art smart implants, we shed light on persistent issues and limitations while discussing potential avenues for future advancements in materials used for these devices

Target-specific multiphysics modeling for thermal medicine applications

Dissertation to obtain the degree of Doctor of Philosophy in Biomedical EngineeringThis thesis addresses thermal medicine applications on murine bladder hyperthermia and brain temperature monitoring. The two main objectives are interconnected by the key physics in thermal medicine: heat transfer. The first goal is to develop an analytical solution to characterize the heat transfer in a multi-layer perfused tissue. This analytical solution accounts for important thermoregulation mechanisms and is essential to understand the fundamentals underlying the physical and biological processes associated with heat transfer in living tissues. The second objective is the development of target-specific models that are too complex to be solved by analytical methods. Thus, the software for image segmentation and model simulation is based on numerical methods and is used to optimize non-invasive microwave antennas for specific targets. Two examples are explored using antennas in the passive mode (probe) and active mode (applicator). The passive antenna consists of a microwave radiometric sensor developed for rapid non-invasive feedback of critically important brain temperature. Its design parameters are optimized using a power-based algorithm. To demonstrate performance of the device, we build a realistic model of the human head with separate temperaturecontrolled brain and scalp regions. The sensor is able to track brain temperature with 0.4 °C accuracy in a 4.5 hour long experiment where brain temperature is varied in a 37 °C, 27 °C and 37 °C cycle. In the second study, a microwave applicator with an integrated cooling system is used to develop a new electro-thermo-fluid (multiphysics) model for murine bladder hyperthermia studies. The therapy procedure uses a temperature-based optimization algorithm to maintain the bladder at a desired therapeutic level while sparing remaining tissues from dangerous temperatures. This model shows that temperature dependent biological properties and the effects of anesthesia must be accounted to capture the absolute and transient temperature fields within murine tissues. The good agreement between simulation and experimental results demonstrates that this multiphysics model can be used to predict internal temperatures during murine hyperthermia studies

Microwave sensing for neurodegenerative diseases

The rapidly increasing rate of the ageing population has led to a higher rate in people suffering from neurodegenerative diseases. Neurodegenerative diseases, such as Alzheimer’s and Parkinson’s disease, are characterised by the progressive loss of brain cells, which leads to a decline in a person’s cognitive abilities, and eventually leads to death. The alarming increase in people suffering from these diseases has created a global socioeconomic burden that affects caregivers, nurses, and family members, just as much as the patient themselves. Due to the critical nature of these diseases, it is paramount that systems and devices can detect and monitor neurodegenerative diseases as early as possible, so that the right treatment can be provided to hinder its progression. Existing technologies have provided key results in the detection and monitoring of neurodegenerative diseases. However, they are limited by their bulky size, high costs, and inconvenient or invasive approach. Meanwhile, microwave sensing technology has generated promising results in several medical applications, such as cancer and stroke detection. The ability to fabricate components easily and integrate them into a wearable prototype makes microwave sensing a promising non-invasive, cost-effective, and portable or wearable solution for medical diagnostics. This work proposes the use of microwave sensing as an inexpensive, non-invasive, reliable, accurate, efficient, and wearable tool for monitoring the progression of neurodegenerative diseases. For evaluation, models were created to emulate symptoms of Alzheimer’s disease to demonstrate the technology. It is observed that microwave sensing was able to detect brain atrophy and lateral ventricle enlargement with a minimum change of 5%. In addition, microwave sensing could non-invasively detect and image regions of the brain affected by Alzheimer’s disease pathology, providing a transformational and major improvement compared to PET scans that rely on biomarkers. Moreover, microwave sensing could detect Alzheimer’s disease at one of its earliest stages: mild cognitive impairment. This work provides a promising and transformative approach for wearable and non-invasive neurodegenerative disease monitoring

Fibre optic pressure sensors in healthcare applications

This PhD thesis provides an extensive description of the development of two fibre optic pressure sensors for applications in health care: (i) a miniature fibre optic Fabry–Perot pressure sensor for fluid pressure measurements in invasive blood pressure monitoring and; (ii) a highly sensitive fibre Bragg grating sensor for contact/interface pressure measurement. The fibre optic Fabry-Perot pressure sensor has a diameter of 125 μm and is created by forming a cavity at the tip of a single-mode optical fibre. Parylene films were used as the pressure-sensitive diaphragm. The performance of three sensors with different aspect ratios has been investigated. The pressure sensing range of ~10 kPa (diastolic pressure)- ~15 kPa (systolic pressure) was targeted; sensor with the cavity of 70 μm in diameter and cavity length of 87 μm is able to sense within a range of 0- 18 kPa with an average sensitivity of 0.12 nm/kPa and response time of 3 seconds. The temperature sensitivity of 0.084 nm/°C was observed. Hysteresis and wavelength drift were observed for the sensors, which may be due to the permeability of the Parylene film to the air. Solutions for reducing hysteresis, wavelength drift and temperature cross-sensitivity are discussed in detail. Fibre Bragg grating (FBG) sensor technology is an ideal candidate for contact pressure measurement in compression therapy, pressure ulcer or prosthetics due to its many advantages such as conforming to body parts, small size, biocompatibility and multiplexing capabilities. A successful mathematical model for an FBG contact pressure sensor for healthcare applications has been presented and experimentally validated. The model has been compared with previous studies reported in the literature and takes into account birefringence. The highest sensitivity was achieved for the disc shape with a sensitivity of 0.8719 nm/MPa for a diameter of 5.5 mm, thickness of 1 mm and Young’s modulus of 20 MPa. This sensor was comprised of a 3 mm long FBG 6 centrally located in the patch. This is a pressure sensitivity of ~270 times increase when compared with a bare FBG reported in the literature. Birefringence effect was observed for the disk patch for pressures larger than 2.6 MPa. Even though FBGs provide high sensitivity in contact pressure sensing in healthcare, the potential applications are limited by the size and cost of commercially available FBG interrogators. A successful first attempt towards the development of a single channel compact FBG interrogation was accomplished. The system consists of a three-section distributed Bragg Reflector (DBR) tuneable laser, microcontroller unit, precision 5 channel current driver IC, photodiode circuit and a temperature controller IC. The tuneable laser was calibrated within 1535-1544 nm wavelength range to produce three current–wavelength lookup tables for wavelength resolution of 1 nm, 0.1 nm, 0.01 nm which is dependent on the current resolution. Futureworkincludesaddingpowercircuitry, a photodiode circuit and a feedback circuit to minimize power fluctuations. The system was tested compared to the commercial Smartscope FBG interrogator

Fibre optic pressure sensors in healthcare applications

This PhD thesis provides an extensive description of the development of two fibre optic pressure sensors for applications in health care: (i) a miniature fibre optic Fabry–Perot pressure sensor for fluid pressure measurements in invasive blood pressure monitoring and; (ii) a highly sensitive fibre Bragg grating sensor for contact/interface pressure measurement. The fibre optic Fabry-Perot pressure sensor has a diameter of 125 μm and is created by forming a cavity at the tip of a single-mode optical fibre. Parylene films were used as the pressure-sensitive diaphragm. The performance of three sensors with different aspect ratios has been investigated. The pressure sensing range of ~10 kPa (diastolic pressure)- ~15 kPa (systolic pressure) was targeted; sensor with the cavity of 70 μm in diameter and cavity length of 87 μm is able to sense within a range of 0- 18 kPa with an average sensitivity of 0.12 nm/kPa and response time of 3 seconds. The temperature sensitivity of 0.084 nm/°C was observed. Hysteresis and wavelength drift were observed for the sensors, which may be due to the permeability of the Parylene film to the air. Solutions for reducing hysteresis, wavelength drift and temperature cross-sensitivity are discussed in detail. Fibre Bragg grating (FBG) sensor technology is an ideal candidate for contact pressure measurement in compression therapy, pressure ulcer or prosthetics due to its many advantages such as conforming to body parts, small size, biocompatibility and multiplexing capabilities. A successful mathematical model for an FBG contact pressure sensor for healthcare applications has been presented and experimentally validated. The model has been compared with previous studies reported in the literature and takes into account birefringence. The highest sensitivity was achieved for the disc shape with a sensitivity of 0.8719 nm/MPa for a diameter of 5.5 mm, thickness of 1 mm and Young’s modulus of 20 MPa. This sensor was comprised of a 3 mm long FBG 6 centrally located in the patch. This is a pressure sensitivity of ~270 times increase when compared with a bare FBG reported in the literature. Birefringence effect was observed for the disk patch for pressures larger than 2.6 MPa. Even though FBGs provide high sensitivity in contact pressure sensing in healthcare, the potential applications are limited by the size and cost of commercially available FBG interrogators. A successful first attempt towards the development of a single channel compact FBG interrogation was accomplished. The system consists of a three-section distributed Bragg Reflector (DBR) tuneable laser, microcontroller unit, precision 5 channel current driver IC, photodiode circuit and a temperature controller IC. The tuneable laser was calibrated within 1535-1544 nm wavelength range to produce three current–wavelength lookup tables for wavelength resolution of 1 nm, 0.1 nm, 0.01 nm which is dependent on the current resolution. Futureworkincludesaddingpowercircuitry, a photodiode circuit and a feedback circuit to minimize power fluctuations. The system was tested compared to the commercial Smartscope FBG interrogator

Technology applications

A summary of NASA Technology Utilization programs for the period of 1 December 1971 through 31 May 1972 is presented. An abbreviated description of the overall Technology Utilization Applications Program is provided as a background for the specific applications examples. Subjects discussed are in the broad headings of: (1) cancer, (2) cardiovascular disease, (2) medical instrumentation, (4) urinary system disorders, (5) rehabilitation medicine, (6) air and water pollution, (7) housing and urban construction, (8) fire safety, (9) law enforcement and criminalistics, (10) transportation, and (11) mine safety

Source Modelling of the Human Hippocampus for MEG

Magnetoencephalography (MEG) is a neuroimaging technique which gives direct non-invasive measurements of neuronal activity with high temporal resolution. Given its increasing use in cognitive and clinical research, it is important to characterize, and ideally improve upon, its advantages and limitations. For example, it is conventionally assumed to be insensitive to deep structures because of their distance from the sensors. Consequently, knowledge about their signal contribution is limited. One deep structure of particular interest is the hippocampus which plays a key role in memory and learning, and in organising temporal flow of information across regions. A large body of rodent studies have demonstrated quantifiable oscillatory underpinnings of these functions, now waiting to be addressed in humans. Due to its high temporal resolution, MEG is ideally suited for doing so but faces technical challenges. Firstly, the source-to-sensor distance is large, making it difficult to obtain sufficiently high signal-to-noise ratio (SNR) data. Secondly, most generative models (which describe the relationship between sensors and signal) include only the cortical surface. Thirdly, errors in co-registering data to an anatomical image easily obstruct or blur hippocampal sources. This thesis tested the hypotheses that a) identification and optimisation of acquisition parameters which improve the SNR, b) inclusion of the hippocampus in the generative model, and c) minimisation of co-registration error, together enable reliable inferences about hippocampal activity from MEG data. We found the most important empirical factor in detecting hippocampal activity using the extended generative model to be co-registration error; that this can be minimised using flexible head-casts; and that combining anatomical modelling, head-casts, and a spatial memory task, allows hippocampal activity to be reliably observed. Hence the work confirmed the overall hypothesis to be valid. Additionally, simulation results revealed that for a new generation of MEG sensors, ~5-fold sensitivity improvements can be obtained but critically depend on low sensor location errors. These findings set down a new basis for time-resolved examination of hippocampal function