Design of a Customized multipurpose nano-enabled implantable system for in-vivo theranostics

The first part of this paper reviews the current development and key issues on implantable multi-sensor devices for in vivo theranostics. Afterwards, the authors propose an innovative biomedical multisensory system for in vivo biomarker monitoring that could be suitable for customized theranostics applications. At this point, findings suggest that cross-cutting Key Enabling Technologies (KETs) could improve the overall performance of the system given that the convergence of technologies in nanotechnology, biotechnology, micro&nanoelectronics and advanced materials permit the development of new medical devices of small dimensions, using biocompatible materials, and embedding reliable and targeted biosensors, high speed data communication, and even energy autonomy. Therefore, this article deals with new research and market challenges of implantable sensor devices, from the point of view of the pervasive system, and time-to-market. The remote clinical monitoring approach introduced in this paper could be based on an array of biosensors to extract information from the patient. A key contribution of the authors is that the general architecture introduced in this paper would require minor modifications for the final customized bio-implantable medical device

Ultraminiature Piezoelectric Implantable Acoustic Transducers for Biomedical Applications

Miniature piezoelectric acoustic transducers have been developed for numerous applications. Compared to other transduction mechanisms like capacitive or piezoresistive, piezoelectric transducers do not need direct current (DC) bias voltage and can work directly exposed to fluid. Hence, they are good candidates for biomedical applications that often require the transducer to work in water based fluid. Among all piezoelectric materials, aluminum nitride (AlN) is a great choice for implantable sensors because of the high electrical resistance, low dielectric loss, and biocompatibility for in vivo study. This thesis presents the design, modeling, fabrication, and testing of the AlN acoustic transducers, miniaturized to be implantable for biomedical applications like hearing or cardiovascular devices. To design and model the transducer in air and in water, a 3D finite element analysis (FEA) model was built to study the transducer in a viscous fluid environment. An array of AlN bimorph cantilevers were designed to create a multi-resonance transducer to increase the sensitivity in a broad band frequency range. A two-wafer process using microelectricalmechanical systems (MEMS) techniques was used to fabricate the xylophone transducer with flexible cable. Benchtop testing confirmed the transducer functionality and verified the FEA model experimentally. The transducer was then implanted inside a living cochlea of a guinea pig and tested in vivo. The piezoelectric voltage output from the transducer was measured in response to 80-95 dB sound pressure level (SPL) sinusoidal excitation spanning 1-14 kHz. The phases showed clear acoustic delay. The measured voltage responses were linear and above the noise level. These results demonstrated that the transducer can work as a sensor for a fully implantable cochlear implant. The second generation device, an ultraminiature diaphragm transducer, was designed to be smaller, and yet with an even lower noise floor. The transducer was designed and optimized using a 2D axial-symmetric FEA model for a better figure of merit (FOM), which considered both minimal detectable pressure (MDP) and the diaphragm area. The low-frequency sensitivity was increased significantly, because of the encapsulated back cavity. Because of this merit, cardiovascular applications, which focus on low frequency signals, were also investigated. The diaphragm transducers were fabricated using MEMS techniques. Benchtop tests for both actuating and sensing confirmed the transducer functionality, and verified the design and model experimentally. The transducer had a better FOM than other existing piezoelectric diaphragm transducers, and it had a much lower MDP than the other intracochlear acoustic sensors.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147673/1/chumingz_1.pd

Using Hidden Markov Models to Segment and Classify Wrist Motions Related to Eating Activities

Advances in body sensing and mobile health technology have created new opportunities for empowering people to take a more active role in managing their health. Measurements of dietary intake are commonly used for the study and treatment of obesity. However, the most widely used tools rely upon self-report and require considerable manual effort, leading to underreporting of consumption, non-compliance, and discontinued use over the long term. We are investigating the use of wrist-worn accelerometers and gyroscopes to automatically recognize eating gestures. In order to improve recognition accuracy, we studied the sequential ependency of actions during eating. In chapter 2 we first undertook the task of finding a set of wrist motion gestures which were small and descriptive enough to model the actions performed by an eater during consumption of a meal. We found a set of four actions: rest, utensiling, bite, and drink; any alternative gestures is referred as the other gesture. The stability of the definitions for gestures was evaluated using an inter-rater reliability test. Later, in chapter 3, 25 meals were hand labeled and used to study the existence of sequential dependence of the gestures. To study this, three types of classifiers were built: 1) a K-nearest neighbor classifier which uses no sequential context, 2) a hidden Markov model (HMM) which captures the sequential context of sub-gesture motions, and 3) HMMs that model inter-gesture sequential dependencies. We built first-order to sixth-order HMMs to evaluate the usefulness of increasing amounts of sequential dependence to aid recognition. The first two were our baseline algorithms. We found that the adding knowledge of the sequential dependence of gestures achieved an accuracy of 96.5%, which is an improvement of 20.7% and 12.2% over the KNN and sub-gesture HMM. Lastly, in chapter 4, we automatically segmented a continuous wrist motion signal and assessed its classification performance for each of the three classifiers. Again, the knowledge of sequential dependence enhances the recognition of gestures in unsegmented data, achieving 90% accuracy and improving 30.1% and 18.9% over the KNN and the sub-gesture HMM

A High-Yield Microfabrication Process for Sapphire Substrate Pressure Sensors with Low Parasitic Capacitances and 200 C Tolerance

Microelectromechanical systems (MEMS) can offer many benefits over conventional sensor assembly, especially as the desire for smaller and more effective instrumentation escalates in demand. While many industries continually strive for improved sensing capabilities, those invested in natural gas and oil extraction have a particular interest in miniaturized pressure sensing systems. These sensors need to operate autonomously in harsh environment (50 MPa, 125°C) fissures (≤1 cm) with at least 10 bit pressure resolution (≤0.05 MPa). The primary focus of this report is the development of a surface micromachining process to fabricate high performance capacitive pressures sensors, utilizing dielectric substrates to enable extremely low offset and parasitic capacitances and temperature coefficients. In contrast to conventional bulk silicon micromachining methods that use various kinds of etch stops such as electrochemical or dopant selective, dry additive processes are utilized to reduce manufacturing complexity, cost, and material consumption and have gained favor in recent years as the tools have matured. The fabricated devices must meet both pressure sensing and dimensional scaling requirements with a full scale range of ≥50 MPa, resolution of ≤50 kPa (>20 fF/MPa with a system resolution of 1 fF/code), and size of ≤2×1×0.5 mm3. In order to meet these goals while maximizing yield, particular attention has been given to the interplay between equipment limitations and device design. Process and design features have been refined over four process generations that together lead to a capacitance response of >450 fF/MPa over 50 MPa, provide a yield of >80%, permit an extreme span (>1000×) of full scale range designs, and allow automated system assembly. Devices have been tested at pressures and temperatures of up to ≥50 MPa and 200°C, representing downhole environments, demonstrating < 7.0 kPa (< 1 psi) resolution. Devices designed to operate over a much lower full scale range of < 50 kPa (≤350 Torr), representing biomedical applications, have been tested and demonstrate a resolution of < 80 Pa (< 0.6 Torr). Sensor response and design have been validated in the primary use case of autonomous microsystem integration. The system circuity includes a microcontroller, capacitance-to-digital converter, temperature sensor, photodiode, and battery. The readout electronics and sensor are mounted onto a flexible PCB, packaged into stainless steel or ceramic shells, sealed with silicone epoxy to permit pressure transmission while providing environmental protection, and measure < 9×9×7 mm3 in size. The systems have been successfully field tested in a brine well. While the capacitive pressure sensors have been developed primarily for active microsystems, there may be situations where a wired connection to the readout circuitry is not possible. A passive wireless pressure monitoring system utilizing short range inductive coupling has been developed to evaluate the performance of the sapphire substrate sensors for this use case. The passive sensing element consists of the capacitive pressure sensor and an inductor, packaged in a 3D printed biocompatible housing measuring ø12 x 24 mm3. Pressure monitoring within the GI tract has been targeted; an in situ resolution of 1.6 kPa (12 Torr) at 6 cm has been achieved through conductive saline. A practical application of the sensor has been demonstrated in vivo, having been ingested and successfully interrogated in a canine model to monitor stomach pressure for over two days.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/149856/1/acbenken_1.pd