La technologie d’aujourd’hui donne la possibilité à chacun de se localiser grâce à son smartphone. Cependant les milieux intra-muros restent encore relativement dépourvus en service de géolocalisation. Pour des raisons d’ubiquité, les centrales inertielles et magnétiques de technologie MEMS présentes dans les smartphones offrent une solution pour la navigation pédestre. Dans ce contexte la stratégie « Pedestrian Dead-Reckoning » s’avère intéressante car elle limite la dérive temporelle de l’estimation de la distance parcourue. Cependant, l’estimation de la direction de marche s’avère critique dans la stratégie PDR, les mouvements de la main présentant un certain désordre/désalignement qui rend difficile une telle estimation. Dans un premier temps, l’estimation de l’orientation de la centrale inertielle est affinée afin de projeter avec un minimum d’erreur les mesures inertielles dans le plan horizontal. Un filtre d’estimation de l’orientation paramétré en quaternions et basé sur une exploitation opportune des champs magnétiques et de gravité a été développé. Dans un second temps, il s’agit d’estimer la direction de marche. Les méthodes de l’état de l’art proposent une estimation de la direction de marche à partir de la maximisation de l’énergie du signal. Cette approche est sensible aux mouvements de la main. Nous proposons une nouvelle approche basée sur les théories des probabilités et de l’information qui s’inspire de la description biomécanique de la marche. Des validations expérimentales sont conduites pour analyser les performances d’estimation de la direction de marche qui est directement reliée à la qualité de l’estimation du positionnement. / Thanks to new technological developments, it is now possible to get our localization with our own smartphone. However, indoor environments are still relatively lacking in localization based service. MEMS sensors, composed of inertial and magnetic sensors, offer a ubiquitous solution. These sensors can be merged with other technologies to give a reliable solution for the Pedestrian Navigation. In this context the “Pedestrian Dead Reckoning” strategy is attractive. Indeed, this strategy enables to estimate the walking distance with a limited drift. But the walking direction estimation remains critical in the PDR strategy. Hand movements are relatively erratic and cause a dynamic angular misalignment, which is difficult to estimate. Firstly, a new orientation estimation algorithm of the handheld unit is developed to reduce the errors in the horizontal inertial measurements. The filter is parametrized with quaternions and based on opportune invariant phases of the magnetic and gravity fields. Secondly, a novel walking direction estimator is proposed. State of the art methods to estimate the walking direction are based on the signal energy maximization and are sensitive to erratic hand movements. The new approach is based on the theories of probability and information that is built on the biomechanical description of walking. Experimental validations are conducted to analyze the performance of the new direction estimation filter whose quality directly depends on the quality of the position estimates

abstract: The advancements in the technology of MEMS fabrication has been phenomenal in recent years. In no mean measure this has been the result of continued demand from the consumer electronics market to make devices smaller and better. MEMS inertial measuring units (IMUs) have found revolutionary applications in a wide array of fields like medical instrumentation, navigation, attitude stabilization and virtual reality. It has to be noted though that for advanced applications of motion tracking, navigation and guidance the cost of the IMUs is still pretty high. This is mainly because the process of calibration and signal processing used to get highly stable results from MEMS IMU is an expensive and time-consuming process. Also to be noted is the inevitability of using external sensors like GPS or camera for aiding the IMU data due to the error propagation in IMU measurements adds to the complexity of the system. First an efficient technique is proposed to acquire clean and stable data from unaided IMU measurements and then proceed to use that system for tracking human motion. First part of this report details the design and development of the low-cost inertial measuring system ‘yIMU’. This thesis intends to bring together seemingly independent techniques that were highly application specific into one monolithic algorithm that is computationally efficient for generating reliable orientation estimates. Second part, systematically deals with development of a tracking routine for human limb movements. The validity of the system has then been verified. The central idea is that in most cases the use of expensive MEMS IMUs is not warranted if robust smart algorithms can be deployed to gather data at a fraction of the cost. A low-cost prototype has been developed comparable to tactical grade performance for under $15 hardware. In order to further the practicability of this device we have applied it to human motion tracking with excellent results. The commerciality of device has hence been thoroughly established. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2016

Motion analysis deals with determining what and how activities are being performed by a subject, through the use of sensors. The process of answering the what question is commonly known as classification, and answering the how question is here referred to as characterization. Frequently, combinations of inertial sensor such as accelerometers and gyroscopes are used for motion analysis. These sensors are cheap, small, and can easily be incorporated into wearable systems. The overall goal of this thesis was to improve the processing of inertial sensor data for the characterization of movements. This thesis presents a framework for the development of motion analysis systems that targets movement characterization, and describes an implementation of the framework for gait analysis. One substantial aspect of the framework is symbolization, which transforms the sensor data into strings of symbols. Another aspect of the framework is the inclusion of human expert knowledge, which facilitates the connection between data and human concepts, and clarifies the analysis process to a human expert. The proposed implementation was compared to state of practice gait analysis systems, and evaluated in a clinical environment. Results showed that expert knowledge can be successfully used to parse symbolic data and identify the different phases of gait. In addition, the symbolic representation enabled the creation of new gait symmetry and gait normality indices. The proposed symmetry index was superior to many others in detecting movement asymmetry in early-to-mid-stage Parkinson's Disease patients. Furthermore, the normality index showed potential in the assessment of patient recovery after hip-replacement surgery. In conclusion, this implementation of the gait analysis system illustrated that the framework can be used as a road map for the development of movement analysis systems.

The ability to walk and negotiate stairs is an important predictor of independent ambulation. The superposition of mobility impairments to the effects of natural aging in persons with stroke render the completion of many daily activities unsafe, thus limiting individuals’ independence within their communities. Currently however, no means exist for the monitoring of mobility levels during daily living in survivors after the completion of rehabilitation programs. The application of inertial sensors for stroke survivors could provide a basis for the study of gait outside of traditional laboratory settings. The main objective of this thesis was to evaluate the performance of inertial sensors in measuring gait of hemiparetic stroke survivors through the completion of three studies. The first study explored the use of inertial measurement units (IMUs) for the measurement of lower limb joint kinematics during stair ascent and descent in both stroke survivors and healthy older adults. Results suggested that IMUs were suitable for the measurement of lower limb range of motion in both healthy and post-stroke subjects during stair ambulation. The second study evaluated the measurement of step length and spatial symmetry during overground walking using IMUs. A systematic error resulting in the underestimation of step lengths calculated using IMUs compared with those measured using video analysis was found, however results suggested that IMUs were suitable for the assessment of spatial symmetry between affected and less-affected limbs in stroke survivors. The final study evaluated the automatic classification of gait activities using inertial sensor data. Findings revealed that the use of a classifier composed of frequency-features extracted from IMU accelerometer and gyroscope data from both the affected and less-affected limbs most accurately identified gait activities from post stroke gait data. This thesis provides a first attempt at applying IMUs to the study of gait post-stroke. Future work may extend the findings of these studies to provide a better understanding to rehabilitation professionals of the demands of everyday life for stroke survivors. / Thesis (Master, Mechanical and Materials Engineering) -- Queen's University, 2013-08-29 12:42:05.505

Falls are the most frequent cause of unintentional injuries among older adults; afflicting 30 percent of persons aged 65 and older and more than 50 percent of persons aged 85 and older. There is a serious need for strategies to prevent falls in elderly individuals, but an important challenge in fall prevention is the paucity of objective evidence regarding the mechanisms that lead directly to falls. There exists no mechanisms about how to predict and manage elderly falls, which has multifactorial risk factors associated with its occurrence in the elderly. As the U.S. population continues to age, both the number of falls as well as the cost of treatment of fall injuries will continue to grow. Decades of research in fall prevention has not led to a decrease in the fall incidence; thus new strategies need to be introduced to understand and prevent falls. Aging reduces the adaptability of various physical and environmental stressors that hinder stability and balance maintenance and may therefore result in a fall. Movement variability in an individual's task performance can be used to assess the limitations of the movement control system. Maintaining variation in movement engenders flexible and adaptable modalities for elderly individuals to prevent falls in an unpredictable and ever changing external environment. Conversely, excessive variability of movement may drive the control system closer to its stability limits during balance and walking tasks. Accordingly, inertial sensors are an emerging wearable technology that can facilitate noninvasive monitoring of fall prone individuals in clinical settings. This research examined the potential of inertial sensors for use in clinical settings, and evaluated their effectiveness in comparison to mature laboratory systems (i.e., force platform and camera system). Study findings showed a relationship between movement variability and fall risk among healthy young and older adults. Further, the outcomes of this work translates to the clinical environment to better understand the health status (leading to frailty) of cardiac patients; reflected by the underlying adaptability of the control system, but requires further improvements if to be used as robust clinical tool. This research provides the groundwork for rapid clinical assessments in which its validity and robustness should be investigated in future efforts. / Ph. D.

MEMS gyroscopes have become an essential component in consumer, industrial and automotive applications, owing to their small form factor and low production cost. However, their poor stability, also known as drift, has hindered their penetration into high-end tactical and navigation applications, where highly stable bias and scale factor are required over long period of time to avoid significant positioning error. Improving the long-term stability of MEMS gyroscopes has created new challenges in both the physical sensor design and fabrication, as well as the system architecture used for interfacing with the physical sensor. The objective of this research is to develop interface circuits and systems for in-situ control and self-calibration of MEMS resonators and resonant gyroscopes to enhance the stability of bias and scale factor without the need for any mechanical rotary stage, or expensive bulky lab characterization equipment. The self-calibration techniques developed in this work provide 1-2 orders of magnitude improvement in the drift of bias and scale factor of a resonant gyroscope over temperature and time.

Les travaux entrepris dans cette thèse s'inscrivent dans le cadre du projet BodyScoring. Ce dernier propose une solution innovante basée sur l'utilisation d'une technologie embarquée (BodyTrack) et des applications web (BodyLink) pour évaluer les habiletés motrices et pour développer la motivation pour l’accomplissement d’une pratique physique régulière. Dans le cadre de ce projet, notre apport a consisté à évaluer et à noter la qualité de la marche des personnes âgées par le biais de capteurs inertiels qui incluent accéléromètre, gyromètre et magnétomètre. Notre apport original a consisté à caractériser le pattern de marche au travers de différentes configurations de capteurs placés sur le corps et de proposer un score global validé et facilement interprétable. Le score permettra de se positionner par rapport à une population de référence jeune et asymptomatique et in fine autoévaluer l’évolution de sa marche. Afin d’atteindre cet objectif plusieurs étapes sont nécessaires. Ainsi, le premier chapitre de ce mémoire décrit en se référant à la littérature les paramètres déterminants de la marche, les facteurs pouvant les influencer et les moyens utilisés pour les quantifier. Le second chapitre porte principalement sur la définition de la meilleure configuration de capteurs pour la détection des événements clés de la marche qui sont la survenue du contact initial et final et la quantification des paramètres temporels. Il en ressort que le gyromètre fixé au bord distal du tibia est la configuration la plus précise aussi bien pour la détection des événements de la marche que pour la quantification des paramètres temporels chez des sujets sains. Le troisième chapitre expose un nouveau protocole expérimental afin de définir les paramètres pertinents pour caractériser la marche et définir l'incidence de la pratique de la marche nordique sur les paramètres biomécaniques. Autrement dit, définir les paramètres biomécaniques qui rendent compte de l'altération du pattern de marche au cours de la sénescence ou encore apprécier l'effet d'une activité physique régulière. Cette étude a révélé 72 paramètres au pouvoir discriminant et rejoint les études qui rapportent un effet bénéfique de lamarche nordique. Pour finir, le quatrième chapitre décrit l'élaboration de nouveaux scores d'évaluation de la marche basé sur les paramètres mis en évidence au chapitre 3 complémentés par ceux qualifiant la symétrie des membres inférieurs et supérieurs. Ces derniers décrivent la qualité de la marche dans son ensemble (score global) et la qualité de chaque aspect (score partiel). Quantifiés pour trois groupes de sujets (âgés sédentaire, âgés sportif et jeune) ces scores ont permis de mettre en évidence l'altération du pattern de marche au cours de la sénescence et l'effet de la pratique d'une activité physique sur les paramètres associés à la marche. / The purpose of this thesis is to asses and scores the gait quality of elderly persons through inertial sensors. The originality of this contribution is to characterize the pattern of walking through different sensor configurations and propose an overall score, valid and easily interpretable. This latter, allows subjects to self-assess to position themselves compared to a young and asymptomatic reference population and ultimately track their evolution.The first chapter, following a review of the literature, identifies the determinant gait parameters, its influent factors and the means used to quantify them.The second chapter, focuses on the definition of the best configuration of sensors to detect gait events and quantify temporal parameters.The third chapter, lists the biomechanical parameters that reflect the changing pattern of walking during senescence or consecutive to a regular physical activity.In the fourth chapter, a new method to compute the score based on the parameters identified in Chapter 3 was developed.

Near-fall detection is important for medical research since it can help doctors diagnose fall-related diseases and also help alert both doctors and patients of possible falls. However, in people’s daily life, there are lots of similarities between near-falls and other Activities of Daily Living (ADLs), which makes near-falls particularly difficult to detect. In order to find the subtle difference between ADLs and near-fall and accurately identify the latter, the movement of whole human body needs to be captured and displayed by a computer generated avatar. In this thesis, a wireless inertial motion capture system consisting of a central control host and ten sensor nodes is used to capture human body movements. Each of the ten sensor nodes in the system has a tri-axis accelerometer and a tri-axis gyroscope. They are attached to separate locations of a human body to record both angular and acceleration data with which body movements can be captured by applying Euler angle based algorithms, specifically, single rotation order algorithm and the optimal rotation order algorithm. According to the experiment results of capturing ten ADLs, both the single rotation order algorithm and the optimal rotation order algorithm can track normal human body movements without significantly distortion and the latter shows higher accuracy and lower data shifting. Compared to previous inertial systems with magnetometers, this system reduces hardware complexity and software computation while ensures a reasonable accuracy in capturing human body movements.

International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / The GPS/INS equipment is used at the Air Force Flight Test Center (AFFTC) to collect time space position information (TSPI) during testing. The GPS-based test instrumentation is lagging behind available commercial technologies. Advancing technologies for test use requires investigation of affordable commercial equipment. To enable technology insertion for state of the art testing, there is a need for more robust, flexible, reliable, modular, affordable low cost TSPI systems capable of operating in all flight environments. Modular (plug-and-play) hardware and software, quick and easy to re-configure, are required for supporting various test platforms from fighter aircraft to cargo size aircraft. Flight testing dynamics are such that, GPS-only systems tend to lose data during critical maneuvers. To minimize this data loss, inertial measurement systems coupled with GPS sensors are used in most sophisticated range instrumentation packages. However, these packages have required fairly expensive inertial units, are usually very large and not very flexible in terms of quick and easy reconfiguration to meet the unique needs of AFFTC’s test customers. WADDAN SYSTEMS has begun to address this problem with a modular design concept, which incorporates their high-performance navigation quality inertial measurement unit, but with costs comparative to that of lower-end performance inertial units. This paper describes WADDAN’s concept and the components that make up MAGI; and addresses some of the preliminary testing and near-term proposed activities. In general, the system will provide GPS, inertial and discrete MIL-STD 1553, RS-232/422 and video data from the participant. The MAGI will be structured around the Compact personal computer interface (PCI) backplane bus with on-board recording and processing and will include real-time command and control through a UHF data link.

This dissertation discusses the design, simulation and characterization of process-compatible accelerometers and gyroscopes for the implementation of multi-degree-of-freedom (multi-DOF) systems. All components presented herein were designed to operate under the same vacuum-sealed environment to facilitate batch fabrication and wafer-level packaging (WLP), enabling the development of small form-factor single-die inertial measurement units (IMUs). The high-aspect-ratio poly and single-crystal silicon (HARPSS) process flow was used to co-fabricate the devices that compose the system, enabling the implementation ultra-narrow capacitive gaps (< 300 nm) in thick device-layer substrates (40 um). The presented gyroscopes were implemented as high-frequency BAW disk resonators operating in a mode-matched condition. A new technique to reduced dependencies on environmental stimuli such as temperature, vibration and shock was introduced. Novel decoupling springs were utilized to effectively isolate the gyros from their substrate, minimizing the effect that external sources of error have on offset and scale-factor. The substrate-decoupled (SD) BAW gyros were interfaced with a customized IC to achieve supreme random-vibration immunity (0.012 (deg/s)/g) and excellent rejection to shock (0.075 (deg/s)/g). With a scale factor of 800 uV/(deg/s), the complete SD-BAW gyro system attains a large full-scale range (2500 deg/s) with excellent linearity. The measured angle-random walk (ARW) of 0.36 deg/rthr and bias-instability of 10.5 deg/hr are dominated by the thermal and flicker noise of the IC, respectively. Additional measurements using external electronics show bias-instability values as low as 3.5 deg/hr. To implement the final monolithic multi-DOF IMU, accelerometers were carefully designed to operate in the same vacuum environment required for the gyroscopes. Narrow capacitive gaps were used to adjust the accelerometer squeeze-film damping (SFD) levels, preventing an under-damped response. Robust simulation techniques were developed using finite-element analysis (FEA) tools to extract accurate values of SFD, which were then match with measured results. Ultra-small single proof-mass tri-axial accelerometers with Brownian-noise as low as 30 ug/rtHz were interfaced with front-end electronics exhibiting scale-factor values in the order of 5 to 10 mV/g and cross-axis sensitivities of less than 3% before any electronic compensation.