Human Motion Tracking and Its Data Compression in Body-Area Inertial Sensor Networks PDF Download
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Author: 吳鈞豪
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: 吳鈞豪
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Timo von Marcard
Publisher:
ISBN: 9783186866103
Category :
Languages : de
Pages :
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Author: Yatiraj K Shetty
Publisher:
ISBN:
Category : Human mechanics
Languages : en
Pages : 136
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Book Description
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.
Author: Chen, Xi (Researcher on human mechanics)
Publisher:
ISBN:
Category : Human locomotion
Languages : en
Pages : 169
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High-resolution, quantitative data obtained by a human motion capture system can be used to better understand the cause of many diseases for effective treatments. Talking about the daily care of the aging population, two issues are critical. One is to continuously track motions and position of aging people when they are at home, inside a building or in the unknown environment; the other is to monitor their health status in real time when they are in the free-living environment. Continuous monitoring of human movement in their natural living environment potentially provide more valuable feedback than these in laboratory settings. However, it has been extremely challenging to go beyond laboratory and obtain accurate measurements of human physical activity in free-living environments. Commercial motion capture systems produce excellent in-studio capture and reconstructions, but offer no comparable solution for acquisition in everyday environments. Therefore in this dissertation, a wearable human motion analysis system is developed for continuously tracking human motions, monitoring health status, positioning human location and recording the itinerary. In this dissertation, two systems are developed for seeking aforementioned two goals: tracking human body motions and positioning a human. Firstly, an inertial-based human body motion tracking system with our developed inertial measurement unit (IMU) is introduced. By arbitrarily attaching a wearable IMU to each segment, segment motions can be measured and translated into inertial data by IMUs. A human model can be reconstructed in real time based on the inertial data by applying high efficient twists and exponential maps techniques. Secondly, for validating the feasibility of developed tracking system in the practical application, model-based quantification approaches for resting tremor and lower extremity bradykinesia in Parkinson's disease are proposed. By estimating all involved joint angles in PD symptoms based on reconstructed human model, angle characteristics with corresponding medical ratings are employed for training a HMM classifier for quantification. Besides, a pedestrian positioning system is developed for tracking user's itinerary and positioning in the global frame. Corresponding tests have been carried out to assess the performance of each system.
Author: Paul Kisik Yoon
Publisher:
ISBN:
Category :
Languages : en
Pages : 62
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Recently, miniature inertial measurement units (IMUs) have been deployed as wearable devices to monitor human motion in an ambulatory fashion. This thesis presents a robust human motion tracking algorithm using the IMU and radio-based wireless sensors, such as the Bluetooth Low Energy (BLE) and ultra-wideband (UWB). First, a novel indoor localization method using the BLE and IMU is proposed. The BLE trilateration residue is deployed to adaptively weight the estimates from these sensor modalities. Second, a robust sensor fusion algorithm is developed to accurately track the location and capture the lower body motion by integrating the estimates from the UWB system and IMUs, but also taking advantage of the estimated height and velocity obtained from an aiding lower body biomechanical model. The experimental results show that the proposed algorithms can maintain high accuracy for tracking the location of a sensor/subject in the presence of the BLE/UWB outliers and signal outages.
Author: Eric Robert Bachmann
Publisher:
ISBN: 9781423532248
Category :
Languages : en
Pages : 199
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Book Description
Current motion tracking technologies fail to provide accurate wide area tracking of multiple users without interference and occlusion problems. This research proposes to overcome current limitations using nine-axis magnetic/ angular/rate/gravity (MARG) sensors combined with a quaternion-based complementary filter algorithm capable of continuously correcting for drift and following angular motion through all orientations without singularities. Primarily, this research involves the development of a prototype tracking system to demonstrate the feasibility of MARG sensor body motion tracking Mathematical analysis and computer simulation are used to validate the correctness of the complementary filter algorithm The implemented human body model utilizes the world-coordinate reference frame orientation data provided in quaternion form by the complementary filter and orients each limb segment independently. Calibration of the model and the inertial sensors is accomplished using simple but effective algorithms. Physical experiments demonstrate the utility of the proposed system by tracking of human limbs in real-time using multiple MARG sensors. The system is "sourceless" and does not suffer from range restrictions and interference problems. This new technology overcomes the limitations of motion tracking technologies currently in use. It has the potential to provide wide area tracking of multiple users in virtual environment and augmented reality applications.
Author: Giancarlo Fortino
Publisher: Springer
ISBN: 3030028194
Category : Technology & Engineering
Languages : en
Pages : 477
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Book Description
This book presents the post-proceedings, including all revised versions of the accepted papers, of the 2017 European Alliance for Innovation (EAI) International Conference on Body Area Networks (BodyNets 2017). The goal of BodyNets 2017 was to provide a world-leading and unique forum, bringing together researchers and practitioners from diverse disciplines to plan, analyze, design, build, deploy and experiment with/on Body Area Networks (BANs).
Author: David Forsyth
Publisher: Now Publishers Inc
ISBN: 1933019301
Category : Automatic tracking
Languages : en
Pages : 188
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Book Description
Computational Studies of Human Motion: Part 1, Tracking and Motion Synthesis reviews methods for kinematic tracking of the human body in video. The review confines itself to the earlier stages of motion, focusing on tracking and motion synthesis. There is an extensive discussion of open issues. The authors identify some puzzling phenomena associated with the choice of human motion representation --- joint angles vs. joint positions. The review concludes with a quick guide to resources and an extensive bibliography of over 400 references. Computational Studies of Human Motion: Part 1, Tracking and Motion Synthesis is an invaluable reference for those engaged in computational geometry, computer graphics, image processing, imaging in general, and robotic.
Author: Guang-Zhong Yang
Publisher: Springer
ISBN: 1447163745
Category : Computers
Languages : en
Pages : 572
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Book Description
The last decade has witnessed a rapid surge of interest in new sensing and monitoring devices for wellbeing and healthcare. One key development in this area is wireless, wearable and implantable in vivo monitoring and intervention. A myriad of platforms are now available from both academic institutions and commercial organisations. They permit the management of patients with both acute and chronic symptoms, including diabetes, cardiovascular diseases, treatment of epilepsy and other debilitating neurological disorders. Despite extensive developments in sensing technologies, there are significant research issues related to system integration, sensor miniaturisation, low-power sensor interface, wireless telemetry and signal processing. In the 2nd edition of this popular and authoritative reference on Body Sensor Networks (BSN), major topics related to the latest technological developments and potential clinical applications are discussed, with contents covering. Biosensor Design, Interfacing and Nanotechnology Wireless Communication and Network Topologies Communication Protocols and Standards Energy Harvesting and Power Delivery Ultra-low Power Bio-inspired Processing Multi-sensor Fusion and Context Aware Sensing Autonomic Sensing Wearable, Ingestible Sensor Integration and Exemplar Applications System Integration and Wireless Sensor Microsystems The book also provides a comprehensive review of the current wireless sensor development platforms and a step-by-step guide to developing your own BSN applications through the use of the BSN development kit.
Author: Jung Keun Lee
Publisher:
ISBN:
Category : Accelerometers
Languages : en
Pages : 0
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Book Description
Recent advances in miniature sensors and mobile computing have fostered a dramatic growth of interest for 'ambulatory' human motion tracking. Inertial (i.e. accelerometers and gyroscopes) and magnetic sensors do not have in-the-lab measurement limitations and thus are ideal for ambulatory applications. This thesis presents ambulatory human motion tracking using inertial/magnetic sensing. In particular, the purpose of this thesis is to introduce novel orientation estimation algorithms using an inertial/magnetic sensor and demonstrate practical applications of the inertial/magnetic sensors in spinal and gait analysis. First, two quaternion-based orientation estimation algorithms were newly developed with focus on improving computational efficiency. Both algorithms deal with so-called Wahba's problem, a least squares minimization problem, to find a best fit orientation estimation solution. A major difference between them is that one is based on a deterministic approach using a Gauss-Newton method and the other is based on a stochastic approach that employs Kalman filtering. The Gauss-Newton method in the former was formulated using virtual rotation concept while the Kalman filter in the latter was designed to have a minimum-order structure, which significantly improves the computational efficiency of each algorithm. Second, a novel 3D spinal motion measurement system based on inertial/magnetic sensors was proposed. The proposed system can provide not only 3D orientations of the spine/pelvis but also temporal gait parameters, enabling a comprehensive analysis of the 3D spinal kinematics together with the gait analysis. In particular, the spinal motions during the staircase walking were compared to those during level walking using the proposed system, to fill a gap in the spinal kinematics literature. Furthermore, the system was applied to investigate low back pain effects on spinal motion during stair-climbing. This study revealed that the lumbar spinal sagittal motion during stair-climbing can provide an effective quantitative measure in the assessment of low back pain patients. In addition to the spinal motion analysis, an automatic gait event detection algorithm using shank attached inertial sensors was presented for further gait analysis. The outcomes of the research in this thesis can serve as foundation towards achieving a truly ambulatory human motion tracking system.
