This thesis proposes a motion sensing system for wheelchairs with the main objective of determining tips, falls and risky situations. The system relies on measurements from an Inertial Measurement Unit, (IMU), consisting of a 3-axis accelerometer and a 2-axis gyroscope as the source of information. The IMU was embedded in a portable device, the "Motion Logger", which collects motion data in a Secure Digital memory card after running a real time preprocessing algorithm. The algorithm was designed to reduce energy consumption and memory usage. Actual signal analysis and attitude estimation is carried out offline. The motion sensing system was developed for determining wheelchair-related falls as part of a major research effort carried out at the research center of the James A Haley VA Hospital Subject Safety Center, Tampa, Florida. The focus of the study concentrated on achieving a thorough understanding of the demographics, nature, consequences and the creation of prediction models for fall events. The main goal of the embedded system was to successfully estimate the motion variables relevant to the occurrence of falls, tips and similar risky situations. Currently, off-line smoothing techniques based on Kalman filter concepts allow for optimal estimation of angles in the longitudinal direction, roll, and in the lateral direction, pitch. Results from both predefined experiments with known outcomes and data collected from actual wheelchair users during pilot and final deployment stages are presented and discussed.

<p>Hasomed GmbH, a German company in the Field of medicine technology, intends to introduce a gait analysis system on the market. The system includes an inertial sensor which collects data used for generating movement patterns of the feet. This thesis describes the development and evaluation of a new version of the sensor, aimed at minimizing costs, maximizing performance and facilitating production.</p><p>Algorithms used in the gait analysis system are sensitive to noise. Noise sources and precautions taken in order to minimize noise levels are described and discussed. By minimizing the physical size of analogue electronics blocks, static noise and occasional high frequency components were substantially reduced.</p><p>New features including internal temperature sensors, firmware update via serial interface, self-test functions and a wireless link were implemented. Additional improvements are e.g. lower power consumption and an extension of the interface from 2 to 256 (theoretical limit) attached devices. By reducing the number of included components and PCB (Printed Circuit Board) layers, together with use of components that do not require advanced soldering techniques, easier and cheaper production was obtained.</p><p>Research and development presented in this thesis resulted in a sensor with overall good performance and new features.</p>

Today the area of high-cost and high-performance navigation for vehicles is a well-developed field. The challenge now is to develop high-performance navigation systems using low-cost sensortechnology. This development involves problems spanning from signal processing of the dirty measurements produced by low-costsensors via fusion and synchronization of information produced by a large set of diverse sensors, to reducing the size and energyconsumption of the systems. This thesis examines and proposessolutions to four of these problems. The first problem examined is the time synchronizing of the sensordata in a global positioning system aided inertial navigationsystem in which no hardware clock synchronization is possible. A poor time synchronization results in an increased mean squareerror of the navigation solution and expressions for calculating this mean square error are presented. A method to solve the timesynchronization issue in the data integration software is proposed. The potential of the method is illustrated with tests onreal-world data that are subjected to timing errors. The second problem examined is the achievable clocksynchronization accuracy in a sensor network employing a two-waymessage exchange model. The Cramer-Rao bound for the estimation of the clock parameters is derived and transformed in to a lower bound on the mean square error of the clock offset.Further, an approximate maximum likelihood estimator for the clockparameters is proposed. The estimator is shown to be of low complexity and to have a mean square error in the vicinity of the Cramer-Rao bound. The third problem examined is the detection of the time epochswhen zero-velocity updates can be applied in a foot-mountedpedestrian navigation system. Four general likelihood ratio testsfor detecting when the navigation system is stationary based onthe inertial measurement data are studied. The performance of thefour detectors is evaluated using levelled ground, forward-gaitdata. The results show that the signals from the gyroscopes holdthe most reliable information for the zero-velocity detection. The fourth problem examined is the calibration of a low-costinertial measurement unit. A calibration procedure that relaxesthe accuracy requirements of the orientation angles the inertialmeasurement unit must be placed in during the calibration isstudied. The proposed calibration method is compared with theCramer-Rao bound for the case when the inertial measurementunit is rotated into precisely controlled orientations. Simulationresults show that the mean square error of the estimated sensormodel parameters reaches the Cramer-Rao bound within fewdecibels. Thus, the proposed method may be acceptable for a widerange of low-cost applications. / QC 20100810

Hasomed GmbH, a German company in the Field of medicine technology, intends to introduce a gait analysis system on the market. The system includes an inertial sensor which collects data used for generating movement patterns of the feet. This thesis describes the development and evaluation of a new version of the sensor, aimed at minimizing costs, maximizing performance and facilitating production. Algorithms used in the gait analysis system are sensitive to noise. Noise sources and precautions taken in order to minimize noise levels are described and discussed. By minimizing the physical size of analogue electronics blocks, static noise and occasional high frequency components were substantially reduced. New features including internal temperature sensors, firmware update via serial interface, self-test functions and a wireless link were implemented. Additional improvements are e.g. lower power consumption and an extension of the interface from 2 to 256 (theoretical limit) attached devices. By reducing the number of included components and PCB (Printed Circuit Board) layers, together with use of components that do not require advanced soldering techniques, easier and cheaper production was obtained. Research and development presented in this thesis resulted in a sensor with overall good performance and new features.

This research focuses on the development of intelligent fastening tool tracking systems for the automotive industry to identify the fastened bolts. In order to accomplish such a task, the position of the tool tip must be identified because the tool tip position coincides with the head of the fastened bolt while the tool fastens the bolt. The proposed systems utilize an inertial measurement unit (IMU) and another sensor to track the position and orientation of the tool tip. To minimize the position and orientation calculation error, an IMU needs to be calibrated as accurately as possible. This research presents a novel triaxial accelerometer calibration technique that offers a high accuracy. The simulation and experimental results of the accelerometer calibration are presented. To identify the fastening action, an expert system is developed based on the sensor measurements. When a fastening action is identified, the system identifies the fastened bolt by using an expert system based on the position and orientation of the tool tip and the position and orientation of the bolt. Since each fastening procedure needs different accuracies and requirements, three different systems are proposed. The first system utilizes a triaxial magnetometer and an IMU to identify the fastened bolt. This system calculates the position and orientation by using an IMU. An expert system is used to identify the initial position, stationary state, and the fastened bolt. When the tool fastens a bolt, the proposed expert system detects the fastening action by triaxial accelerometer and triaxial magnetometer measurements. When the fastening action is detected, the system corrects the velocity and position error using zero velocity update (ZUPT). By using the corrected tool tip position and orientation, the system can identify the fastened bolts. Then, with the fastened bolt position, the position of the IMU is corrected. When the tool is stationary, the system corrects linear velocity error and reduces the position error. The experimental results demonstrate that the proposed system can identify fastened bolts if the angles of the bolts are different or the bolts are not closely placed. This low cost system does not require a line of sight, but has limited position accuracy. The second system utilizes an intelligent system that incorporates Kalman filters (KFs) and a fuzzy expert system to track the tip of a fastening tool and to identify the fastened bolt. This system employs one IMU and one encoder-based position sensor to determine the orientation and the centre of mass location of the tool. When the KF is used, the orientation error increases over time due to the integration step. Therefore, a fuzzy expert system is developed to correct the tilt angle error and orientation error. When the tool fastens a bolt, the system identifies the fastened bolt by applying the fuzzy expert system. When the fastened bolt is identified, the 3D orientation error of the tool is corrected by using the location and the orientation of the fastened bolt and the position sensor outputs. This orientation correction method results in improved reliability in determining the tool tip location. The fastening tool tracking system was experimentally tested in a lab environment, and the results indicate that such a system can successfully identify the fastened bolts. This system not only has a low computational cost but also provides good position and orientation accuracy. The system can be used for most applications because it provides a high accuracy. The third system presents a novel position/orientation tracking methodology by hybridizing one position sensor and one factory calibrated IMU with the combination of a particle filter (PF) and a KF. In addition, an expert system is used to correct the angular velocity measurement errors. The experimental results indicate that the orientation errors of this method are significantly reduced compared to the orientation errors obtained from an EKF approach. The improved orientation estimation using the proposed method leads to a better position estimation accuracy. The experimental results of this system show that the orientation of the proposed method converges to the correct orientation even when the initial orientation is completely unknown. This new method was applied to the fastening tool tracking system. This system provides good orientation accuracy even when the gyroscopes (gyros hereafter) include a small error. In addition, since the orientation error of this system does not grow over time, the tool tip position drift is limited. This system can be applied to the applications where the bolts are closely placed. The position error comparison results of the second system and the third system are presented in this thesis. The comparison results indicate that the position accuracy of the third system is better than that of the second system because the orientation error does not increase over time. The advantages and limitations of all three systems are compared in this thesis. In addition, possible future work on fastening tool tracking system is described as well as applications that can be expanded by using the KF/PF combination method.

Inertial Measurement Units, the main component of a navigation system, are used in several systems today. IMU&rsquo / s main components, gyroscopes and accelerometers, can be produced at a lower cost and higher quantity. Together with the decrease in the production cost of sensors it is observed that the performances of these sensors are getting worse. In order to improve the performance of an IMU, the error compensation algorithms came into question and several algorithms have been designed. Inertial sensors contain two main types of errors which are deterministic errors like scale factor, bias, misalignment and stochastic errors such as bias instability and scale factor instability. Deterministic errors are the main part of error compensation algorithms. This thesis study explains the methodology of how the deterministic errors are defined by 27 state static and 60 state dynamic rate table calibration test data and how those errors are used in the error compensation model. In addition, the stochastic error parameters, gyroscope and bias instability, are also modeled with Gauss Markov Model and instant sensor bias instability values are estimated by Kalman Filter algorithm. Therefore, accelerometer and gyroscope bias instability can be compensated in real time. In conclusion, this thesis study explores how the IMU performance is improved by compensating the deterministic end stochastic errors. The simulation results are supported by a real IMU test data.

This research focuses on the development of intelligent fastening tool tracking systems for the automotive industry to identify the fastened bolts. In order to accomplish such a task, the position of the tool tip must be identified because the tool tip position coincides with the head of the fastened bolt while the tool fastens the bolt. The proposed systems utilize an inertial measurement unit (IMU) and another sensor to track the position and orientation of the tool tip. To minimize the position and orientation calculation error, an IMU needs to be calibrated as accurately as possible. This research presents a novel triaxial accelerometer calibration technique that offers a high accuracy. The simulation and experimental results of the accelerometer calibration are presented. To identify the fastening action, an expert system is developed based on the sensor measurements. When a fastening action is identified, the system identifies the fastened bolt by using an expert system based on the position and orientation of the tool tip and the position and orientation of the bolt. Since each fastening procedure needs different accuracies and requirements, three different systems are proposed. The first system utilizes a triaxial magnetometer and an IMU to identify the fastened bolt. This system calculates the position and orientation by using an IMU. An expert system is used to identify the initial position, stationary state, and the fastened bolt. When the tool fastens a bolt, the proposed expert system detects the fastening action by triaxial accelerometer and triaxial magnetometer measurements. When the fastening action is detected, the system corrects the velocity and position error using zero velocity update (ZUPT). By using the corrected tool tip position and orientation, the system can identify the fastened bolts. Then, with the fastened bolt position, the position of the IMU is corrected. When the tool is stationary, the system corrects linear velocity error and reduces the position error. The experimental results demonstrate that the proposed system can identify fastened bolts if the angles of the bolts are different or the bolts are not closely placed. This low cost system does not require a line of sight, but has limited position accuracy. The second system utilizes an intelligent system that incorporates Kalman filters (KFs) and a fuzzy expert system to track the tip of a fastening tool and to identify the fastened bolt. This system employs one IMU and one encoder-based position sensor to determine the orientation and the centre of mass location of the tool. When the KF is used, the orientation error increases over time due to the integration step. Therefore, a fuzzy expert system is developed to correct the tilt angle error and orientation error. When the tool fastens a bolt, the system identifies the fastened bolt by applying the fuzzy expert system. When the fastened bolt is identified, the 3D orientation error of the tool is corrected by using the location and the orientation of the fastened bolt and the position sensor outputs. This orientation correction method results in improved reliability in determining the tool tip location. The fastening tool tracking system was experimentally tested in a lab environment, and the results indicate that such a system can successfully identify the fastened bolts. This system not only has a low computational cost but also provides good position and orientation accuracy. The system can be used for most applications because it provides a high accuracy. The third system presents a novel position/orientation tracking methodology by hybridizing one position sensor and one factory calibrated IMU with the combination of a particle filter (PF) and a KF. In addition, an expert system is used to correct the angular velocity measurement errors. The experimental results indicate that the orientation errors of this method are significantly reduced compared to the orientation errors obtained from an EKF approach. The improved orientation estimation using the proposed method leads to a better position estimation accuracy. The experimental results of this system show that the orientation of the proposed method converges to the correct orientation even when the initial orientation is completely unknown. This new method was applied to the fastening tool tracking system. This system provides good orientation accuracy even when the gyroscopes (gyros hereafter) include a small error. In addition, since the orientation error of this system does not grow over time, the tool tip position drift is limited. This system can be applied to the applications where the bolts are closely placed. The position error comparison results of the second system and the third system are presented in this thesis. The comparison results indicate that the position accuracy of the third system is better than that of the second system because the orientation error does not increase over time. The advantages and limitations of all three systems are compared in this thesis. In addition, possible future work on fastening tool tracking system is described as well as applications that can be expanded by using the KF/PF combination method.

The instrumentation and methodology of this study provided quantitative data for a group of six advanced slalom skiers. Rope load, skier velocity, ski roll, ski acceleration and ski deceleration were calculated during the deep water start and cutting portion of a slalom run. Four different ski designs were tested in order to determine if the test subjects were able to achieve a different level of performance on each ski. Through a statistical analysis there was enough evidence to suggest that a different performance was achieved between the skis, for rope load and peak roll. There was also enough evidence to suggest that the skiers were achieving different overall levels of performance. The analysis procedure of this study achieved the goal of proving that it could be used to improve coaching capabilities and product design in the water ski industry.

The work described in this thesis contributes to the development of a system to evaluate sailing performance. This work was motivated by the lack of tools available to evaluate sailing performance. The goal of the work presented is to detect and classify the turns of a sailing yacht. Data was collected using a BlackBerry PlayBook affixed to a J/24 sailing yacht. This data was manually annotated with three types of turn: tack, gybe, and mark rounding. This manually annotated data was used to train classification methods. Classification methods tested were multi-layer perceptrons (MLPs) of two sizes in various committees and nearest- neighbour search. Pre-processing algorithms tested were Kalman filtering, categorization using quantiles, and residual normalization. The best solution was found to be an averaged answer committee of small MLPs, with Kalman filtering and residual normalization performed on the input as pre-processing.

O mecanismo Plataforma de Stewart é um manipulador do tipo paralelo, com seis graus de liberdade, boa relação peso/carga e alta rigidez. Tais características conferem a este tipo de manipulador propriedades superiores de precisão em relação aos manipuladores seriais. Neste trabalho, o controle de um Manipulador Plataforma de Stewart (MPS) acionado por atuadores hidráulicos é estudado com o objetivo de compensação de movimentos para viabilização de transferência de cargas e pessoas em ambiente naval.Visando ao desenvolvimento de um protótipo experimental, o manipulador é estudado considerando a situação em que se encontra sobreposto a um segundo MPS que tem por objetivo simular o movimento da maré, sendo ambos MPS considerados desacoplados dinamicamente. Neste contexto, o estudo envolve a análise cinemática e dinâmica do manipulador incluindo, também, a dinâmica dos cilindros hidráulicos. Além disso, são estudadas unidades de medição inercial (IMU) utilizando-as como instrumento para medição do movimento da base a ser compensado. O projeto do controlador do sistema de atenuação de movimento faz uso da técnica de Torque Computado (TC). A análise de estabilidade, feita separadamente para o sistema mecânico e hidráulico, baseou-se da teoria de Lyapunov. Simulações realizadas considerando trajetórias similares às do movimento de um navio são utilizadas. Para compensação do movimento são utilizados, também, sinais provenientes de uma IMU. Por meio de simulação, comprova-se que o sistema proposto é capaz de compensar adequadamente os movimentos da base estudados. / The Stewart platform mechanism is a parallel manipulator with six degrees of freedom, high load/weight ratio and high stifness. These properties give them a better accuracy when compared to serial manipulators. This work focuses on study of electrohydraucally Stewart Platform Manipulators (MPS) to enable compensation of vessels motions for load and personell transfer in sea. Aimed at developing an experimental prototype, a second MPS is placed underneath the rst MPS to simulate vessels motions and so both manipulators are considered dynamically decoupled. In this sense, the kinematics and dynamics of this manipulator are presented, as well as a mathematical model of the hydraulic actuator. Furthermore, special attention is given to the study of inertial measurement units (IMU) which is used as an instrument for measuring the motion to be compensated. Controller design for the compensation system is developed considering compute torque theory which consider the system separated in two: mechanical and hydraulic. The Lyapunov criteria is used to guarantee closed loop stability for each subsystem. Simulations are performed considering similar vessel motions. Signals provided from a comercial IMU are used for motion compensation. The control compensation performance is veri ed by means of computer simulations.