This thesis reports on a design and modeling of a micro-machined gyroscope. The proposed sensor is a dual mass type, electro-statically driven to primary mode oscillation and senses, capacitively, the output signal. Full decoupling between drive and sense modes minimizes the mechanical crosstalk and based on this a novel gyroscope is designed and modeled which has separate sensing and driving masses. The dual mass gyroscope is designed such that driving and sensing resonant frequency is 23101 Hz with 0% mismatch (in simulation)with quality factor of 31.6227 and bandwidth of 730.51Hz. The gyroscope when actuated in simulation with 25V ac and 10V dc showed sensing capacitance variation of 126aF for 1 rad/s with base capacitance of 244.16fF. To the design of the gyroscope a new semi automatic tool was formulated for the noise analysis and noise based optimization of the resonant MEMS structures. Design of a sensitive gyroscope needs to take into account the noise shaping induced by damping phenomena at micro scale and is critical for optimization. The analysis was further extended to the design of the gyroscope and estimation shows that there is a trade of between the S/N ratio and the sensitivity and the design could be made much better in-terms of S/N by tuning its resonant frequency to 10⁶Hz. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

The goal of this paper is to design and implement a module to determine the rotation around three axes normal to each other. The paper is divided into six parts. The first part deals with the rate sensor - the gyroscope. It is explicated how the gyroscope is used for rotation measurement. The next part of the paper explains the acceleration sensor – the accelerometer, functioning as an inclination sensor. The third part analyses the magnetic field sensor – the magnetometer, functioning as an electronic compass. With each type of sensor, the problems of parasitic influences are discussed. The foregoing parts constitute the basis for the HW of the module design that is explained in the forth parts. It deals especially with components used for processing the sensor signals. The next part is a description of the software of the module. Here, the software of the particular sensors and measurement methods used with them are discussed. The last part describes the software of the control application in the computer. The attention is paid especially to processing data from the sensors and their compensation against parasitic influences.

The goal of this paper is to suggest suitable method for angle measuring of mobile robot. There are being analyzed 3 different sensors – gyroscope, accelerometer and electronic compass in the prologue. Their advantages and disadvantages in the theoretical way are being explained in this part and also their opportunities of use in the practical way. In the following parts the work is focused on MEMS gyroscopes and their opportunities of use in the practical way with regard to achievable exactness and to the application for development of its exactness. The application of device together with main SW for microcontroller and the valuation of achievable exactness and determined facts are being described in the conclusion part.

Yes / The study presents a new approach for assessing plantarflexor muscles’ function using a smartphone. The test involves performing repeated heel raises for 60 s while seated. The seated heel-rise test offers a simple method for assessing plantarflexor muscles’ function in those with severe balance impairment who are unable to complete tests performed while standing. The study aimed to showcase how gyroscopic data from a smartphone placed on the lower limb can be used to assess the test. Eight participants performed the seated heel-rise test with each limb. Gyroscope and 2D video analysis data (60 Hz) of limb motion were used to determine the number of cycles, the average rise (T-rise), lowering (T-lower), and cycle (T-total) times. The number of cycles detected matched exactly when the gyroscope and kinematic data were compared. There was good time domain agreement between gyroscopic and video data (T-rise = 0.0005 s, T-lower = 0.0013 s, and T-total = 0.0017 s). The 95% CI limits of agreement were small (T-total −0.1118, 0.1127 s, T-lower −0.1152, 0.1179 s, and T-total −0.0763, 0.0797 s). Results indicate that a smartphone placed on the thigh can successfully assess the seated heel-rise test. The seated heel-rise test offers an attractive alternative to test plantarflexor muscles’ functionality in those unable to perform tests in standing positions.

Design and analysis of polysilicon and single crystal silicon gyroscopes have been carried out. Variations in suspension design have been explored. Designs that utilize in-plane and out-of-plane sensing are studied. Damping plays an important role in determining the sense response. Reduction in damping directly affects sensor performance. The various damping mechanisms that are prevalent in gyroscopes are studied. Perforations on the proof mass are observed to significantly reduce the damping in the device when operated in air. The effects of perforation geometry and density have been analyzed. The analysis results show that there is a two orders of magnitude reduction in damping of thick gyroscope structures with optimized perforation design. Equivalent circuit lumped parameter models have been developed to analyze gyroscope performance. The simulation results of these models have been compared with results obtained from SABER, a MEMS specific system level design tool from Coventor-ware. The lumped parameter models are observed to produce faster simulation results with an accuracy comparable to that of Coventorware Three gyroscopes specific to the PolyMUMPS fabrication process have been designed and their performance analyzed. Two of the designs sense motion out-of-plane and the other senses motion in-plane. Results of the simulation show that for a given damping, the gyro design with in-plane modes gives a resolution of 4◦/s. The out-of-plane gyroscopes have two variations in suspension. The hammock suspension resolves a rate of 25◦/s in a 200 Hz bandwidth while the design with folded beam suspension resolves a rate of 2◦/s in a 12 Hz bandwidth. A single crystal silicon in-plane gyroscope has been designed with vertical electrodes to sense Coriolis motion. This design gives an order of magnitude higher capacitance change for a given rotation in comparison to conventional comb-finger design. The effects of process induced residual stress on the characteristic frequencies of the polysilicon gyroscopes are also studied. The in-plane gyroscope is found to be robust to stress variations. Analysis results indicate that the tuning fork gyroscope with the hammock suspension is the most susceptible to compressive residual stress, with a significant drop in sensitivity at high stress values.

Eye tracking research is a growing area and the fields as where eye trackingcould be used in research are large. To understand the eye tracking data dif-ferent filters are used to classify the measured eye movements. To get accu-rate classification this thesis has investigated the possibility to measure bothhead movements and eye movements in order to improve the estimated gazepoint.The thesis investigates the difference in using head movement compensationwith a velocity based filter, I-VT filter, to using the same filter without headmovement compensation. Further on different velocity thresholds are testedto find where the performance of the filter is the best. The study is made with amobile eye tracker, where this problem exist since you have no absolute frameof reference as opposed to when using remote eye trackers. The head move-ment compensation shows promising results with higher precision overall.

La navigation par système inertiel strapdown est aujourd’hui la plus répandue. L’architecture est bien connue et a été très largement améliorée au cours des dernières décennies. Néanmoins, le principe fondamental n’a subi de bouleversement et reste constitué d’une triplette d’accéléromètres et de gyromètres permettant de revenir aux informations d’attitude et de cap.La précision de l’estimation de position repose principalement sur la gamme de performance des capteurs utilisés. En particulier, des applications telles que des lanceurs spatiaux requièrent une très haute précision et des capteurs d’une technologie éprouvée sont utilisés. L’arrivée sur le marché de capteurs inertiels MEMS de haute précision ouvre une alternative à coût réduits couplée à une réduction de masse, volume et de consommation. Les moyens de production des MEMS ainsi qu’une meilleure connaissance des propriétés des matériaux ont permis l’arrivée d’accéléromètres MEMS pouvant rivaliser avec les technologies éprouvées de gamme tactique. Toutefois, les gyromètres de technologie MEMS existantes restent dans une gamme de performance de type industrielle.La présente étude vise à analyser la possibilité d’utiliser des accéléromètres de haute précision pour améliorer les performances gyrométriques, dans l’objectif de réaliser une solution tout MEMS d’unité de mesure inertielle. Une brève introduction sur les techniques de filtrage de Kalman pour la fusion de données est présentée, ainsi que son implémentation pour notre étude. L’analyse théorique se poursuit avec une présentation des résultats expérimentaux.L’étude conclut que l’utilisation d’une paire d’accéléromètres de haute performance et d’un gyroscope de type consommateur permet d’atteindre les performances d’un gyromètre tactique. Les contraintes de définition et de mesure pour l’implémentation du système sont présentées en détail.Cette étude est menée pour la mesure angulaire autour d’un axe unique de rotation, un complément d’étude est nécessaire à l’extrapolation de cette approche pour une mesure générique en 3D. / Strapdown inertial navigation units are the most popular systems used for navigation. The system architecture is well established and has been extensively improved over the past decades. However, the core idea remains same where a triad of accelerometers and gyroscopes provide the attitude and heading information.The accuracy of the position estimate depends on the performance grade of the sensors employed. For applications like space launchers requiring very high accuracy, high-grade devices using traditional technologies are used. The advent of accurate MEMS based sensors offer an exciting low-cost alternative with expected reduction in size and power consumption. MEMS fabrication technology, assisted by improved understanding of material properties have led to accelerometers that can compete with traditional devices for tactical applications. However, the MEMS based solutions currently available for gyroscopes can replace only industrial grade applications.This study attempts to investigate if the currently available high-grade accelerometers can be used to improve the gyroscope performance, towards the final goal of a complete MEMS based solution for inertial navigation units. The study begins with a literature review of current status of technology. A brief explanation of linear Kalman filtering technique for data fusion is presented, along with its implementation concerning this work. The theoretical discussion is then followed by presentation of experimental results.The study found that using a pair of high-grade accelerometers, a consumer grade gyroscope can have its performance upgraded for tactical applications. The design and sensing constraints for realizing this system are discussed in detail.Since this research work primarily concerns with angular rate estimation around a single axis of rotation, further research is recommended for extrapolating this approach for a more general 3-D sensing case.

Alcohol abuse is the third leading lifestyle-related cause of death for individuals in the United States, causing 88,000 deaths each year in the United States from 2006-2010. Existing smartphone applications allow users to manually record their alcohol consumption or take cognitive tests to estimate intoxication levels; however, no smartphone application passively determines one's level of intoxication. After gathering smartphone sensor data from 34 "intoxicated" subjects, we generated time and frequency domain features such as sway area (gyroscope) and cadence (accelerometer), which were then classified using a supervised machine learning framework. Other novel contributions explored include feature normalization to account for differences in walking styles and automatic outlier elimination to reduce the effect of accidental falls by identifying and removing the top and bottom of a chosen percentage of the data. Various machine learning classifier types such as Random Forest and Bayes Net were compared, and J48 classifier was the most accurate, classifying user gait patterns into BAC ranges of [0.00-0.08), [0.08-0.15), [0.15-0.25), [0.25+) with an accuracy of 89.45%. This best performing classifier was used to build an intelligent smartphone app that will detect the user's intoxication level in real time.

Although tremor is one of the most common movement disorders, there are few effective tremor-suppressing options available to patients. One potential tremor-suppression device involves a wearable gyrostabilizer similar to those used to stabilize cameras. However, we do not currently know how to design a gyrostabilizer to suppress tremor in an optimal manner. To address this gap, we present a systematic investigation of how gyrostabilizer parameters affect tremor suppression in a single degree of freedom (DOF). A simple model of the hand with a single DOF at the wrist and a gyroscope mounted on the back of the hand was used to focus on the most basic effects. After demonstrating that a linearized version of the non-linear equations of motion provides an adequate approximation, we simulated the frequency response of the system (hand + gyroscope) to a tremorogenic input torque at the wrist. By varying system parameters one at a time, we determined the effect of individual parameters on the frequency response of the system. To minimize the bandwidth without adding significant inertia about the wrist joint, the inertia and spin speed of the flywheel should be as high as design constraints allow, whereas the distance from the wrist joint axis to the gyroscope, the precession stiffness, and the precession damping should be kept as low as possible. The results demonstrate the potential of gyroscopic tremor suppression and can serve as the foundation for further investigations of gyroscopic tremor suppression in the upper limb.

Among the many safety hazards facing chainsaw operators, the phenomenon known as kickback is the most dangerous. Kickback occurs when the chain at the tip of the chainsaw is caused to stop abruptly, and transfers the energy of the cutting chain to motion of the saw. The saw will rotate backward toward the operator rapidly. The limited amount of published research on the topic of chainsaw kickback was conducted to develop standardized testing for consumer chainsaws. Modern chainsaws are equipped with safety measures such as low-kickback cutting chains and hand-guard braking mechanisms. These mechanisms have greatly improved the safety of chainsaws, but their inherent mechanical simplicity leaves room for improvement. The current work presents the research that analyzed the possible methods for detecting kickback electronically. Phase 1 of this work utilized a set of two accelerometers and a single gyroscope to determine if it is possible to distinguish a kickback event from normal cutting operations. A method for applying weighting coefficients to the three sensor readings, then summing the three signal values was optimized to obtain the greatest margin between kickback and normal cutting. The result of this study was that kickback is most easily identified by using only a gyroscope and setting a threshold. Phase 2 focused on detecting kickback as early as possible. Three methods were attempted: Signal Differentiation, a Simplified Bag of Words method, and applying a Support Vector Machine with selective undersampling and a stack of classifier vectors. Signal differentiation, while detecting the kickback events earlier, also suffered from many false positives. The Bag of Words method was unsuccessful in creating results different than the threshold method from Phase 1. The Support Vector Machine classification was able to detect kickback an average of 19.4 ms before the simple threshold method with no occurrence of either false positives or false negatives. This method is the most reliable and provides the greatest likelihood of detecting kickback early. / Graduation Date: 2013