418 research outputs found

    A methodology for the performance evaluation of inertial measurement units

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    This paper presents a methodology for a reliable comparison among Inertial Measurement Units or attitude estimation devices in a Vicon environment. The misalignment among the reference systems and the lack of synchronization among the devices are the main problems for the correct performance evaluation using Vicon as reference measurement system. We propose a genetic algorithm coupled with Dynamic Time Warping (DTW) to solve these issues. To validate the efficacy of the methodology, a performance comparison is implemented between the WB-3 ultra-miniaturized Inertial Measurement Unit (IMU), developed by our group, with the commercial IMU InertiaCube3â„¢ by InterSense

    Development of a portable sensorised handle for the objective assessment of the effectiveness and concordance of intervention plans in dementia

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    Dementia is a global issue which is rising rapidly, with 46.8 million people worldwide living with dementia in 2015. This number is expected to increase to 74.7 million by 2030. Some researches show that some kinds of exercises, such as resistance band exercises, would help to improve the memory and other abilities in patients with dementia. However, the true effectiveness of these activities is not really known due to the lack of objective assessment of efforts done during the long intervention time. Moreover, there is no way of measuring the actual activities performed by the patient without direct observation. As a consequence, it is impossible to measure the concordance between the patient and the therapist

    Body Motion Capture Using Multiple Inertial Sensors

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    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

    Anatomical calibration through post-processing of standard motion tests data

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    The inertial measurement unit is popularly used as a wearable and flexible tool for human motion tracking. Sensor-to-body alignment, or anatomical calibration (AC), is fundamental to improve accuracy and reliability. Current AC methods either require extra movements or are limited to specific joints. In this research, the authors propose a novel method to achieve AC from standard motion tests (such as walking, or sit-to-stand), and compare the results with the AC obtained from specially designed movements. The proposed method uses the limited acceleration range on medial-lateral direction, and applies principal component analysis to estimate the sagittal plane, while the vertical direction is estimated from acceleration during quiet stance. The results show a good correlation between the two sets of IMUs placed on frontal/back and lateral sides of head, trunk and lower limbs. Moreover, repeatability and convergence were verified. The AC obtained from sit-to-stand and walking achieved similar results as the movements specifically designed for upper and lower body AC, respectively, except for the feet. Therefore, the experiments without AC performed can be recovered through post-processing on the walking and sit-to-stand data. Moreover, extra movements for AC can be avoided during the experiment and instead achieved through the proposed method

    Inertial Measurement Unit based Virtual Antenna Arrays - DoA Estimation and Positioning in Wireless Networks

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    Today we have different location based services available in a mobile phone or mobile station (MS). These services include: direction finding to nearby ATMs, locating favorite food restaurants, or finding any target destination. Similarly, we see different applications of the positioning and navigation systems in firefighting or other rescue operations. The common factor in almost all of the location based services is the system's ability to determine the user's current position, with reference to a floor plan or a navigation map. Current technologies are using sensor data measurements from one or more sensors, available to the positioning device, for positioning and navigation. Typical examples are radio based positioning such as global positioning system, inertial sensors based inertial navigation system, or camera based positioning systems. Different accuracy and availability conditions of the positioning and navigation solution can be obtained depending on the positioning algorithms and the available sensor information.Nowadays, the focus of research in positioning and navigation has been mostly on the use of existing hardware infrastructure and low-cost solutions, such that the proposed technique can be deployed with ease and without extra infrastructure requirements as well as without any expensive sensor equipment. In this work, we investigate a novel idea for positioning using existing wireless networks and low-cost inertial sensor measurements available at the MS. We propose to use received baseband radio signal along with inertial sensor data, such as accelerometer and rate gyroscope measurements, for direction of arrival (DoA) estimation and positioning. The DoA information from different base stations or access points can be used to estimate the MS position using triangulation technique. Furthermore, due to size and cost restrictions it is difficult to have real antenna arrays at the MS, the idea of DoA estimation and positioning is proposed to be used with single antenna devices by using the so-called virtual antenna arrays.We have presented our research results in three different papers. We provide measurement based results to perform a quantitative evaluation of DoA estimation using arbitrary virtual antenna arrays in 3-D; where a state-of-the-art high-resolution algorithm has been used for radio signal parameter estimation. Furthermore, we provide an extended Kalman filter framework to investigate the performance of unaided inertial navigation systems with 3-axis accelerometer and 3-axis rate gyroscope measurements, from a six-degrees-of-freedom inertial measurement unit. Using the extended Kalman filter framework, we provide results for position estimation error standard deviation with respect to integration time for an unaided inertial navigation system; where the effect of different stochastic errors noise sources in the inertial sensors measurements such as white Gaussian noise and bias instability noise is investigated. Also, we derive a closed form expression for Cramér-Rao lower bound to investigate DoA estimation accuracy for a far-field source using random antenna arrays in 3-D. The Cramér-Rao lower bound is obtained using known antenna coordinates as well as using estimated antenna coordinates, where the antenna coordinates are estimated with an uncertainty whose standard deviation is known. Furthermore, using Monte-Carlo simulations for random antenna arrays, we provide Cramér-Rao lower bound based performance evaluation of random 3-D antenna arrays for DoA estimation

    Development of MEMS - based IMU for position estimation: comparison of sensor fusion solutions

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    With the surge of inexpensive, widely accessible, and precise Micro-Electro Mechanical Systems (MEMS) in recent years, inertial systems tracking move ment have become ubiquitous nowadays. Contrary to Global Positioning Sys tem (GPS)-based positioning, Inertial Navigation System (INS) are intrinsically unaffected by signal jamming, blockage susceptibilities, and spoofing. Measure ments from inertial sensors are also acquired at elevated sampling rates and may be numerically integrated to estimate position and orientation knowledge. These measurements are precise on a small-time scale but gradually accumulate errors over extended periods. Combining multiple inertial sensors in a method known as sensor fusion makes it possible to produce a more consistent and dependable un derstanding of the system, decreasing accumulative errors. Several sensor fusion algorithms occur in literature aimed at estimating the Attitude and Heading Reference System (AHRS) of a rigid body with respect to a reference frame. This work describes the development and implementation of a low-cost, multi purpose INS for position and orientation estimation. Additionally, it presents an experimental comparison of a series of sensor fusion solutions and benchmarking their performance on estimating the position of a moving object. Results show a correlation between what sensors are trusted by the algorithm and how well it performed at estimating position. Mahony, SAAM and Tilt algorithms had best general position estimate performance.Com o recente surgimento de sistemas micro-eletromecânico amplamente acessíveis e precisos nos últimos anos, o rastreio de movimento através de sistemas de in erciais tornou-se omnipresente nos dias de hoje. Contrariamente à localização baseada no Sistema de Posicionamento Global (GPS), os Sistemas de Naveg ação Inercial (SNI) não são afetados intrinsecamente pela interferência de sinal, suscetibilidades de bloqueio e falsificação. As medições dos sensores inerciais também são adquiridas a elevadas taxas de amostragem e podem ser integradas numericamente para estimar os conhecimentos de posição e orientação. Estas medições são precisas numa escala de pequena dimensão, mas acumulam grad ualmente erros durante longos períodos. Combinar múltiplos sensores inerci ais num método conhecido como fusão de sensores permite produzir uma mais consistente e confiável compreensão do sistema, diminuindo erros acumulativos. Vários algoritmos de fusão de sensores ocorrem na literatura com o objetivo de estimar os Sistemas de Referência de Atitude e Rumo (SRAR) de um corpo rígido no que diz respeito a uma estrutura de referência. Este trabalho descreve o desenvolvimento e implementação de um sistema multiusos de baixo custo para estimativa de posição e orientação. Além disso, apresenta uma comparação experimental de uma série de soluções de fusão de sensores e compara o seu de sempenho na estimativa da posição de um objeto em movimento. Os resultados mostram uma correlação entre os sensores que são confiados pelo algoritmo e o quão bem ele desempenhou na posição estimada. Os algoritmos Mahony, SAAM e Tilt tiveram o melhor desempenho da estimativa da posição geral

    Taming and Leveraging Directionality and Blockage in Millimeter Wave Communications

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    To cope with the challenge for high-rate data transmission, Millimeter Wave(mmWave) is one potential solution. The short wavelength unlatched the era of directional mobile communication. The semi-optical communication requires revolutionary thinking. To assist the research and evaluate various algorithms, we build a motion-sensitive mmWave testbed with two degrees of freedom for environmental sensing and general wireless communication.The first part of this thesis contains two approaches to maintain the connection in mmWave mobile communication. The first one seeks to solve the beam tracking problem using motion sensor within the mobile device. A tracking algorithm is given and integrated into the tracking protocol. Detailed experiments and numerical simulations compared several compensation schemes with optical benchmark and demonstrated the efficiency of overhead reduction. The second strategy attempts to mitigate intermittent connections during roaming is multi-connectivity. Taking advantage of properties of rateless erasure code, a fountain code type multi-connectivity mechanism is proposed to increase the link reliability with simplified backhaul mechanism. The simulation demonstrates the efficiency and robustness of our system design with a multi-link channel record.The second topic in this thesis explores various techniques in blockage mitigation. A fast hear-beat like channel with heavy blockage loss is identified in the mmWave Unmanned Aerial Vehicle (UAV) communication experiment due to the propeller blockage. These blockage patterns are detected through Holm\u27s procedure as a problem of multi-time series edge detection. To reduce the blockage effect, an adaptive modulation and coding scheme is designed. The simulation results show that it could greatly improve the throughput given appropriately predicted patterns. The last but not the least, the blockage of directional communication also appears as a blessing because the geometrical information and blockage event of ancillary signal paths can be utilized to predict the blockage timing for the current transmission path. A geometrical model and prediction algorithm are derived to resolve the blockage time and initiate active handovers. An experiment provides solid proof of multi-paths properties and the numeral simulation demonstrates the efficiency of the proposed algorithm

    Innovative intelligent sensors to objectively understand exercise interventions for older adults

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    The population of most western countries is ageing and, therefore, the ageing issue now matters more than ever. According to the reports of the United Nations in 2017, there were a total of 15.8 million (26.9%) people over 60 years of age in the United Kindom, and the numbers are projected to reach 23.5 million (31.5%) by 2050. Spending on medical treatment and healthcare for older adults accounts for two-fifths of the UK National Health Service (NHS) budget. Keeping older people healthy is a challenge. In general, exercise is believed to benefit both mental and physical health. Specifically, resistance band exercises are proven by many studies that they have potentially positive effects on both mental and physical health. However, treatment using resistance band exercise is usually done in unmonitored environments, such as at home or in a rehabilitation centre; therefore, the exercise cannot be measured and/or quantified accurately. Despite many years of research, the true effectiveness of resistance band exercises remains unclear. [Continues.]</div

    Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

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    Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error)

    Machine-human Cooperative Control of Welding Process

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    An innovative auxiliary control system is developed to cooperate with an unskilled welder in a manual GTAW in order to obtain a consistent welding performance. In the proposed system, a novel mobile sensing system is developed to non-intrusively monitor a manual GTAW by measuring three-dimensional (3D) weld pool surface. Specifically, a miniature structured-light laser amounted on torch projects a dot matrix pattern on weld pool surface during the process; Reflected by the weld pool surface, the laser pattern is intercepted by and imaged on the helmet glass, and recorded by a compact camera on it. Deformed reflection pattern contains the geometry information of weld pool, thus is utilized to reconstruct its 33D surface. An innovative image processing algorithm and a reconstruction scheme have been developed for (3D) reconstruction. The real-time spatial relations of the torch and the helmet is formulated during welding. Two miniature wireless inertial measurement units (WIMU) are mounted on the torch and the helmet, respectively, to detect their rotation rates and accelerations. A quaternion based unscented Kalman filter (UKF) has been designed to estimate the helmet/torch orientations based on the data from the WIMUs. The distance between the torch and the helmet is measured using an extra structure-light low power laser pattern. Furthermore, human welder\u27s behavior in welding performance has been studied, e.g., a welder`s adjustments on welding current were modeled as response to characteristic parameters of the three-dimensional weld pool surface. This response model as a controller is implemented both automatic and manual gas tungsten arc welding process to maintain a consistent full penetration
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