Download or read book Robust Human Motion Tracking Using Wireless and Inertial Sensors written by Paul Kisik Yoon and published by . This book was released on 2015 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Robust Human Motion Tracking Using Low cost Inertial Sensors written by Yatiraj K Shetty and published by . This book was released on 2016 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Robust and Large scale Human Motion Estimation with Low cost Sensors written by Hua-I Chang and published by . This book was released on 2016 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: Enabling large-scale monitoring and classification of a range of motion activities is of primary importance due to the need by healthcare and fitness professionals to monitor exercises for quality and compliance. Video based motion capturing systems (e.g., VICON cameras) provide a partial solution. However, these expensive and fixed systems are not suitable for patients' at-home daily motion monitoring. Wireless motion sensors, including accelerometers and gyroscopes, can provide a low-cost, small-size, and highly-mobile option. However, acquiring robust inference of human motion trajectory via low-cost inertial sensors remains challenging. Sensor noise and drift, sensor placement errors and variation of activity over the population all lead to the necessity of a large amount of data collection. Unfortunately, such a large amount of data collection is prohibitively costly. In observance of these issues, a series of solutions for robust human motion monitoring and activity classification will be presented. The implementation of a real-time context-guided activity classification system will be discussed. To facilitate ground truth data acquisition, we proposed a virtual inertial measurements platform to convert the currently available MoCap database into a noiseless and error-free inertial measurements database. An opportunistic calibration system which deals with sensor placement errors will be discussed. In addition, a sensor fusion approach for robust upper limb motion tracking will also be presented.

Download or read book Robust Human Activity Classification and Motion Monitoring Systems Using Inertial Sensors written by Xiaoxu Wu and published by . This book was released on 2016 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proliferation of powerful microcomputers and the development of modern machine learning tools have enabled human daily activity monitoring systems using wearable inertial sensor like accelerometers and gyroscopes. These systems fulfilled the urgent need in health and wellness industries in helping doctors and clinicians during diagnosis, treatments and rehabilitation processes for neurological diseases like strokes and Parkinson's. For most current activity monitoring systems, there exists an assumption that the sensors are always securely and correctly mounted by the users. Unfortunately, such assumptions do not hold as the scale of studies increase. And it is especially challenging for subjects with neurological diseases to follow instructions about how to mount the sensors everyday, because some of the elderlies tend to be technophobic and neurological diseases are often accompanied with cognitive difficulties. Errors in sensor mounting pose can cause large amount of data loss and distortion and will affect the robustness of the systems severely. In observance of these issues, a series of solutions for sensor orientation and position errors in human motion monitoring and activity classification will be presented. Opportunistic calibration methods to find the true sensor orientation and position will be discussed. In addition, systems that provide robust monitoring regardless of the exact sensor pose will be proposed.

Download or read book Multisensor Attitude Estimation written by Hassen Fourati and published by CRC Press. This book was released on 2016-11-03 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: There has been an increasing interest in multi-disciplinary research on multisensor attitude estimation technology driven by its versatility and diverse areas of application, such as sensor networks, robotics, navigation, video, biomedicine, etc. Attitude estimation consists of the determination of rigid bodies’ orientation in 3D space. This research area is a multilevel, multifaceted process handling the automatic association, correlation, estimation, and combination of data and information from several sources. Data fusion for attitude estimation is motivated by several issues and problems, such as data imperfection, data multi-modality, data dimensionality, processing framework, etc. While many of these problems have been identified and heavily investigated, no single data fusion algorithm is capable of addressing all the aforementioned challenges. The variety of methods in the literature focus on a subset of these issues to solve, which would be determined based on the application in hand. Historically, the problem of attitude estimation has been introduced by Grace Wahba in 1965 within the estimate of satellite attitude and aerospace applications. This book intends to provide the reader with both a generic and comprehensive view of contemporary data fusion methodologies for attitude estimation, as well as the most recent researches and novel advances on multisensor attitude estimation task. It explores the design of algorithms and architectures, benefits, and challenging aspects, as well as a broad array of disciplines, including: navigation, robotics, biomedicine, motion analysis, etc. A number of issues that make data fusion for attitude estimation a challenging task, and which will be discussed through the different chapters of the book, are related to: 1) The nature of sensors and information sources (accelerometer, gyroscope, magnetometer, GPS, inclinometer, etc.); 2) The computational ability at the sensors; 3) The theoretical developments and convergence proofs; 4) The system architecture, computational resources, fusion level.

Download or read book Visual inertial Integration for Human Motion Tracking and Navigation in Free living Environments written by Ya Tian and published by . This book was released on 2012 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis comprises three specific goals using our developed IMU board and the camera from the imaging source company: (1) to develop a robust and real-time orientation algorithm using only the measurements from IMU; (2) to develop a robust distance estimation in static free-living environments to estimate people's position and navigate people in static free-living environments and simultaneously the scale ambiguity problem, usually appearing in the monocular camera tracking, is solved by integrating the data from the visual and inertial sensors; (3) in case of moving objects viewed by the camera existing in free-living environments, to firstly design a robust scene segmentation algorithm and then respectively estimate the motion of the vIMU system and moving objects.

Download or read book Robust Motion Detection in Real Life Scenarios written by Ester Martínez-Martín and published by Springer Science & Business Media. This book was released on 2012-07-10 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work proposes a complete sensor-independent visual system that provides robust target motion detection. First, the way sensors obtain images, in terms of resolution distribution and pixel neighbourhood, is studied. This allows a spatial analysis of motion to be carried out. Then, a novel background maintenance approach for robust target motion detection is implemented. Two different situations are considered: a fixed camera observing a constant background where objects are moving; and a still camera observing objects in movement within a dynamic background. This distinction lies on developing a surveillance mechanism without the constraint of observing a scene free of foreground elements for several seconds when a reliable initial background model is obtained, as that situation cannot be guaranteed when a robotic system works in an unknown environment. Other problems are also addressed to successfully deal with changes in illumination, and the distinction between foreground and background elements.

Download or read book Wireless Algorithms Systems and Applications written by Lei Wang and published by Springer Nature. This book was released on 2022-11-17 with total page 677 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set constitutes the proceedings of the 17th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2022, which was held during October 28-30, 2022. The conference took place in Dalian, China.The 95 full and 62 short papers presented in these proceedings were carefully reviewed and selected from 265 submissions. The contributions in ​algorithms, systems; and applications of internet of things;information processing and data management;radar and sonar networks

Download or read book Ambulatory Human Motion Tracking Using Inertial and Magnetic Sensing written by Jung Keun Lee and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Human Motion Tracking and Orientation Estimation Using Inertial Sensors and RSSI Measurements written by Ami Luttwak and published by . This book was released on 2011 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Intelligent Systems and Applications written by Yaxin Bi and published by Springer Nature. This book was released on 2019-08-23 with total page 1302 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a remarkable collection of chapters covering a wide range of topics in the areas of intelligent systems and artificial intelligence, and their real-world applications. It gathers the proceedings of the Intelligent Systems Conference 2019, which attracted a total of 546 submissions from pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer-review process, after which 190 were selected for inclusion in these proceedings. As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have made it possible to tackle a host of problems more effectively. This branching out of computational intelligence in several directions and use of intelligent systems in everyday applications have created the need for an international conference as a venue for reporting on the latest innovations and trends. This book collects both theory and application based chapters on virtually all aspects of artificial intelligence; presenting state-of-the-art intelligent methods and techniques for solving real-world problems, along with a vision for future research, it represents a unique and valuable asset.

Download or read book Human Motion Capture with Sparse Inertial Sensors and Video written by Timo von Marcard and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Intelligent Robotics and Applications written by Huayong Yang and published by Springer Nature. This book was released on 2023-11-11 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 9-volume set LNAI 14267-14275 constitutes the proceedings of the 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023, which took place in Hangzhou, China, during July 5–7, 2023. The 413 papers included in these proceedings were carefully reviewed and selected from 630 submissions. They were organized in topical sections as follows: Part I: Human-Centric Technologies for Seamless Human-Robot Collaboration; Multimodal Collaborative Perception and Fusion; Intelligent Robot Perception in Unknown Environments; Vision-Based Human Robot Interaction and Application. Part II: Vision-Based Human Robot Interaction and Application; Reliable AI on Machine Human Reactions; Wearable Sensors and Robots; Wearable Robots for Assistance, Augmentation and Rehabilitation of Human Movements; Perception and Manipulation of Dexterous Hand for Humanoid Robot. Part III: Perception and Manipulation of Dexterous Hand for Humanoid Robot; Medical Imaging for Biomedical Robotics; Advanced Underwater Robot Technologies; Innovative Design and Performance Evaluation of Robot Mechanisms; Evaluation of Wearable Robots for Assistance and Rehabilitation; 3D Printing Soft Robots. Part IV: 3D Printing Soft Robots; Dielectric Elastomer Actuators for Soft Robotics; Human-like Locomotion and Manipulation; Pattern Recognition and Machine Learning for Smart Robots. Part V: Pattern Recognition and Machine Learning for Smart Robots; Robotic Tactile Sensation, Perception, and Applications; Advanced Sensing and Control Technology for Human-Robot Interaction; Knowledge-Based Robot Decision-Making and Manipulation; Design and Control of Legged Robots. Part VI: Design and Control of Legged Robots; Robots in Tunnelling and Underground Space; Robotic Machining of Complex Components; Clinically Oriented Design in Robotic Surgery and Rehabilitation; Visual and Visual-Tactile Perception for Robotics. Part VII: Visual and Visual-Tactile Perception for Robotics; Perception, Interaction, and Control of Wearable Robots; Marine Robotics and Applications; Multi-Robot Systems for Real World Applications; Physical and Neurological Human-Robot Interaction. Part VIII: Physical and Neurological Human-Robot Interaction; Advanced Motion Control Technologies for Mobile Robots; Intelligent Inspection Robotics; Robotics in Sustainable Manufacturing for Carbon Neutrality; Innovative Design and Performance Evaluation of Robot Mechanisms. Part IX: Innovative Design and Performance Evaluation of Robot Mechanisms; Cutting-Edge Research in Robotics.

Download or read book Innovation in Medicine and Healthcare 2014 written by M. Graña and published by IOS Press. This book was released on 2015-01-06 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances are constantly being made in the fields of medicine and healthcare, and keeping abreast of them is not always easy. This book presents the proceedings of the second KES International Conference on Innovation in Medicine and Healthcare (InMed 14), held in San Sebastian, Spain, in July 2014. The conference was attended by researchers and engineers, managers, students and practitioners from a broad spectrum of medically related fields, and this multidisciplinary group discussed the ways in which technological and methodological innovation, knowledge exchange and enterprise can be applied to issues relating to medicine, surgery, healthcare and the issues of an ageing population. A central theme of the conference was smart medical and healthcare systems, which explored how modern intelligent systems can contribute to the solution of problems faced by healthcare and medical practitioners today and addressed the application of the systems. The 43 papers included here provided a useful and interesting reference for anyone requiring an overview of current innovations in healthcare.

Download or read book Human Motion Analysis with Wearable Inertial Sensors written by Chen, Xi (Researcher on human mechanics) and published by . This book was released on 2013 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Human Motion Sensing and Recognition written by Honghai Liu and published by Springer. This book was released on 2017-05-11 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to the latest exciting advances in human motion sensing and recognition, from the theoretical development of fuzzy approaches to their applications. The topics covered include human motion recognition in 2D and 3D, hand motion analysis with contact sensors, and vision-based view-invariant motion recognition, especially from the perspective of Fuzzy Qualitative techniques. With the rapid development of technologies in microelectronics, computers, networks, and robotics over the last decade, increasing attention has been focused on human motion sensing and recognition in many emerging and active disciplines where human motions need to be automatically tracked, analyzed or understood, such as smart surveillance, intelligent human-computer interaction, robot motion learning, and interactive gaming. Current challenges mainly stem from the dynamic environment, data multi-modality, uncertain sensory information, and real-time issues. These techniques are shown to effectively address the above challenges by bridging the gap between symbolic cognitive functions and numerical sensing & control tasks in intelligent systems. The book not only serves as a valuable reference source for researchers and professionals in the fields of computer vision and robotics, but will also benefit practitioners and graduates/postgraduates seeking advanced information on fuzzy techniques and their applications in motion analysis.

Download or read book A Case Study on Robustness of Dynamic Time Warping for Activity Recognition Using Wearable Computers written by Nimish Rajiv Kale and published by . This book was released on 2012 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: We describe a body sensor system that detects human activities in real-time. The system consists of wearable computers known as sensor nodes (motes) that can sense information, process them and transmit the results to a Personal Device like Smart phone, PDA or Personal Computer. The motes are attached to different parts of the human body, namely waist and right thigh. Daily living activity monitoring is important in improving quality of life especially in elderly. A wireless wearable network of inertial sensor nodes can be used to observe daily motions. Continuous stream of data generated by these sensor networks can be used to recognize the movements of interest. Dynamic Time Warping (DTW) is a widely used signal processing for time-series pattern matching because of its robustness to variations in time domain and speed as opposed to other template matching methods such as Euclidean Distance. Despite of this flexibility, for the application of activity recognition, DTW can only find the similarity between template of a movement and the incoming samples, when the location and orientation of sensor remains unchanged. Due to this restriction, small sensor misplacements can lead to false classifications. In this work, we adopt DTW distance as a feature for real-time detection of human daily activities like sit to stand. To measure this performance of DTW, we need infinite closely spaced sensors which are impractical. To deal with this problem, we use the marker based optical motion capture system and generate inertial sensor data for different location and orientation on the body. We study the performance of the DTW under these conditions and determine the worst-case sensor location variations, the algorithm can accommodate.