Download or read book Towards Wearable Platform for Accurate Unconstrained Trunk Motion Tracking Using Inertial and Strain Sensors Data Fusion written by Ahmad Rezaei and published by . This book was released on 2019 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: The thesis focused on the development of a wearable motion tracking platform employing fiber strain sensors and inertial measurement units through a data fusion algorithm. The development of a smart sleeveless shirt for measuring the kinematic angles of the trunk in complicated 3-dimensional movements was demonstrated. Fiber strain sensors were integrated into the fabric as the sensing element of the system. Furthermore, a novel method for obtaining the kinematic data of joints based on the data from wearable sensors was proposed. More specifically, the proposed method uses the data from two gyroscopes and the smart shirt strain sensors in a combined machine learning-unscented Kalman filter (UKF) data fusion approach to track the three-dimensional movements of a joint accurately. The suggested technique thus avoids the common problems associated with extracting the movement information from accelerometer and magnetometer readings in the presence of disturbances. A study with 12 participants performing an exhaustive set of simple to complex trunk movements was conducted to investigate the performance of the developed algorithm. The results of this study demonstrated that the data fusion algorithm could significantly improve the accuracy of motion tracking in complicated 3-dimensional movements. Future work requires coherently combining both types of sensors in a wearable platform for full-body motion tracking so that the proposed algorithm can be tested in a variety of daily living activities.

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 Wearable and Wireless Systems for Healthcare I written by Robert LeMoyne and published by Springer. This book was released on 2017-10-20 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides visionary perspective and interpretation regarding the role of wearable and wireless systems for the domain of gait and reflex response quantification. These observations are brought together in their application to smartphones and other portable media devices to quantify gait and reflex response in the context of machine learning for diagnostic classification and integration with the Internet of things and cloud computing. The perspective of this book is from the first-in-the-world application of these devices, as in smartphones, for quantifying gait and reflex response, to the current state of the art. Dr. LeMoyne has published multiple groundbreaking applications using smartphones and portable media devices to quantify gait and reflex response.

Download or read book A Platform for High speed Biomechanical Analysis Using Wearable Wireless Sensors written by Michael Tomasz Lapinski and published by . This book was released on 2013 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Humanity's desire to capture and understand motion started in 1878 and has continually evolved. Today, the best-of- breed technology for capturing motion are marker based optical systems that leverage high speed cameras. While these systems are excellent at providing positional information, they suffer from an innate inability to accurately provide fundamental parameters such as velocity and acceleration. The problem is further compounded when the target of capture is high-speed human motion. When applied to biomechanical study, this inaccuracy is magnified when higher order parameters, such as torque and force, are calculated using optical information. This dissertation presents a a first-of-its-kind wearable dual-range inertial sensor platform that allows end-to-end investigation of high level biomechanical parameters. The platform takes a novel approach by providing these parameters more accurately and at a higher fidelity than the current state of the art.The dual-range sensing approach allows accurate capture of both slow-moving motion and rapid movement which pushes the limits of human ability. The platform addresses inherent problems with scaling clinical biomechanical analysis to tens-of-thousands of trials using the sensor platform's data. This end-to-end approach provides mechanisms for rapid player instrumentation, en masse data translation and calculation of clinically relevant joint forces and torques. I present design details for this platform along with kinematic testing and some early biomechanical insight gleamed from system measurements.

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 Wearable and Wireless Systems for Healthcare II written by Robert LeMoyne and published by Springer. This book was released on 2019-02-20 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a far-sighted perspective on the role of wearable and wireless systems for movement disorder evaluation, such as Parkinson’s disease and Essential tremor. These observations are brought together in the application of quantified feedback for deep brain stimulation systems using the wireless accelerometer and gyroscope of a smartphone to determine tuning efficacy. The perspective of the book ranges from the pioneering application of these devices, such as the smartphone, for quantifying Parkinson’s disease and Essential tremor characteristics, to the current state of the art. Dr. LeMoyne has published multiple first-of-their-kind applications using smartphones to quantify movement disorder, with associated extrapolation to portable media devices.

Download or read book Wearable Sensor System for Human Localization and Motion Capture written by Shaghayegh Zihajehzadeh and published by . This book was released on 2017 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in MEMS wearable inertial/magnetic sensors and mobile computing have fostered a dramatic growth of interest for ambulatory human motion capture (MoCap). Compared to traditional optical MoCap systems such as the optical systems, inertial (i.e. accelerometer and gyroscope) and magnetic sensors do not require external fixtures such as cameras. Hence, they do not have in-the-lab measurement limitations and thus are ideal for ambulatory applications. However, due to the manufacturing process of MEMS sensors, existing wearable MoCap systems suffer from drift error and accuracy degradation over time caused by time-varying bias. The goal of this research is to develop algorithms based on multi-sensor fusion and machine learning techniques for precise tracking of human motion and location using wearable inertial sensors integrated with absolute localization technologies. The main focus of this research is on true ambulatory applications in active sports (e.g., skiing) and entertainment (e.g., gaming and filmmaking), and health-status monitoring. For active sports and entertainment applications, a novel sensor fusion algorithm is developed to fuse inertial data with magnetic field information and provide drift-free estimation of human body segment orientation. This concept is further extended to provide ubiquitous indoor/outdoor localization by fusing wearable inertial/magnetic sensors with global navigation satellite system (GNSS), barometric pressure sensor and ultra-wideband (UWB) localization technology. For health applications, this research is focused on longitudinal tracking of walking speed as a fundamental indicator of human well-being. A regression model is developed to map inertial information from a single waist or ankle-worn sensor to walking speed. This approach is further developed to estimate walking speed using a wrist-worn device (e.g., a smartwatch) by extracting the arm swing motion intensity and frequency by combining sensor fusion and principal component analysis.

Download or read book Wearable Computing written by Giancarlo Fortino and published by John Wiley & Sons. This book was released on 2018-04-06 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the most up-to-date research and development on wearable computing, wireless body sensor networks, wearable systems integrated with mobile computing, wireless networking and cloud computing This book has a specific focus on advanced methods for programming Body Sensor Networks (BSNs) based on the reference SPINE project. It features an on-line website (http://spine.deis.unical.it) to support readers in developing their own BSN application/systems and covers new emerging topics on BSNs such as collaborative BSNs, BSN design methods, autonomic BSNs, integration of BSNs and pervasive environments, and integration of BSNs with cloud computing. The book provides a description of real BSN prototypes with the possibility to see on-line demos and download the software to test them on specific sensor platforms and includes case studies for more practical applications. • Provides a future roadmap by learning advanced technology and open research issues • Gathers the background knowledge to tackle key problems, for which solutions will enhance the evolution of next-generation wearable systems • References the SPINE web site (http://spine.deis.unical.it) that accompanies the text • Includes SPINE case studies and span topics like human activity recognition, rehabilitation of elbow/knee, handshake detection, emotion recognition systems Wearable Systems and Body Sensor Networks: from modeling to implementation is a great reference for systems architects, practitioners, and product developers. Giancarlo Fortino is currently an Associate Professor of Computer Engineering (since 2006) at the Department of Electronics, Informatics and Systems (DEIS) of the University of Calabria (Unical), Rende (CS), Italy. He was recently nominated Guest Professor in Computer Engineering of Wuhan University of Technology on April, 18 2012 (the term of appointment is three years). His research interests include distributed computing and networks, wireless sensor networks, wireless body sensor networks, agent systems, agent oriented software engineering, streaming content distribution networks, distributed multimedia systems, GRID computing. Raffaele Gravina received the B.Sc. and M.S. degrees both in computer engineering from the University of Calabria, Rende, Italy, in 2004 and 2007, respectively. Here he also received the Ph.D. degree in computer engineering. He's now a Postdoctoral research fellow at University of Calabria. His research interests are focused on high-level programming methods for WSNs, specifically Wireless Body Sensor Networks. He wrote almost 30 scientific/technical articles in the area of the proposed Book. He is co-founder of SenSysCal S.r.l., a spin-off company of the University of Calabria, and CTO of the wearable computing area of the company. Stefano Galzarano received the B.S. and M.S. degrees both in computer engineering from the University of Calabria, Rende, Italy, in 2006 and 2009, respectively. He is currently pursuing a joint Ph.D. degree in computer engineering with University of Calabria and Technical University of Eindhoven (The Netherlands). His research interests are focused on high-level programming methods for wireless sensor networks and, specifically, novel methods and frameworks for autonomic wireless body sensor networks.

Download or read book Textile based Electromagnetic Soft Strain Sensors for Fast Frequency Movement and Their Application in Wearable Devices Measuring Multi axial Hip Joint Angles During Running written by Mohammad Tavassolian and published by . This book was released on 2020 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wearable in situ multi-axis motion tracking with inductive sensors and machine learning is presented. The production, characterization, and use of a modular and size adjustable inductive sensor for kinematic motion tracking are introduced. The sensor was highly stable and able to track high frequency (>15Hz) and high strain rates (>450%/s). Four sensors were used to fabricate a pair of motion capture shorts. A random forest machine learning algorithm was used to predict the sagittal, transverse, and frontal hip joint angle using the raw signals from the sport shorts strain sensors during running with a cohort of 12 participants against a gold standard optical motion capture system to an accuracy as high as R2 = 0.98 and an RMSE of 2° in all three planes. This present study provides an alternative strain sensor to those typically used (piezoresistive/capacitive) for soft wearable motion capture devices with distinct advantages that could find applications in smart wearable devices, robotics, or direct integration into textiles.

Download or read book Inertial and Magnetic Tracking of Limb Segment Orientation for Inserting Humans Into Synthetic Environments written by Eric Robert Bachmann and published by . This book was released on 2000-12-01 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Miniatured Inertial Motion and Position Tracking and Visualization Systems Using Android Wear Platform written by Dhruvkumar Navinchandra Patel and published by . This book was released on 2016 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we have designed and developed a motion tracking and visualization system using the latest motion tracking sensory technologies. It is one of the enabling technologies for our novel visual-inertial odometer and human anatomy based 3D Locating, Mapping and Navigation system for endoscopy and drug delivery capsules used inside GI tract. In particular, we have: i) designed and completed a cloud-based sensory data collecting, processing and storage system to provide the reliable computing and storage platform; ii) explored different data processing methods to obtain improved-quality motion results from extremely noisy raw data, e.g., by using a low pass and high pass filter, and Kalman filters; iii) developed low-complexity algorithms to support real-time data analysis; and, iv) provided real-time 3 dimensional visualizations by a Unity 3D based visualizer.In this thesis, we have also showcased the use of application processors, which are widely used in smartphones and tablets, to develop a potentially low-cost sensor system and networks with enhanced computing, storage and networking capabilities. Specifically, we have explored Android/Android Wear, Google{u2019}s open source mobile OS{u2019}s, enabled smart devices, such as Sony Smartwatch 3, and their built-in sensory capabilities to build our sensory system. The completeness and maturity of such a widely used mobile platform ensure a fast prototype design and development process, as well as significantly better reliability and usability. The reliability of our sensory system is further improved through the use of a database approach, such as transactions, for the data flow from sensors to mobile platform and eventually to the cloud. Thus, our prototype design provides a working model to collect sensor data from Android Wear, and then transfer and store them into the cloud for further processing and disseminations.

Download or read book Data Analytics and Applications of the Wearable Sensors in Healthcare written by Shabbir Syed-Abdul and published by MDPI. This book was released on 2020-06-17 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a collection of comprehensive research articles on data analytics and applications of wearable devices in healthcare. This Special Issue presents 28 research studies from 137 authors representing 37 institutions from 19 countries. To facilitate the understanding of the research articles, we have organized the book to show various aspects covered in this field, such as eHealth, technology-integrated research, prediction models, rehabilitation studies, prototype systems, community health studies, ergonomics design systems, technology acceptance model evaluation studies, telemonitoring systems, warning systems, application of sensors in sports studies, clinical systems, feasibility studies, geographical location based systems, tracking systems, observational studies, risk assessment studies, human activity recognition systems, impact measurement systems, and a systematic review. We would like to take this opportunity to invite high quality research articles for our next Special Issue entitled “Digital Health and Smart Sensors for Better Management of Cancer and Chronic Diseases” as a part of Sensors journal.

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 Efficient and Accurate Motion Tracking and Its Applications Within the Internet of Things Design Space written by Kevin Gardner and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Finger motion tracking from unobtrusive inertial measurement unit (IMU) methods, such as smart rings and smart watches, is becoming increasingly useful as adoption of wearables become ubiquitous. Its applications range from better evaluations of a patient's motor skills to real-time sign language translation. This paper explores two different methods for finger motion tracking--a hidden markov model (HMM) and a long short-term model (LSTM)--of the index finger metacarpophalangeal (MCP) and Interphalangeal Proximal (PIP) joints relative to the wrist using accelerometer data to predict relative position and discusses the tradeoffs of both methods. In order to overcome the challenge of limited IMU data, a synthetic IMU data preparation method was also explored.

Download or read book Inertial Sensor Based Tracking and Navigation written by Rui Zhang and published by . This book was released on 2014 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Tracking Center of Mass with Limited Inertial Measurement Units written by and published by . This book was released on 2019 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wearable motion tracking systems pose an opportunity to study and correct human balance and posture during movement. Currently, these observations are either being conducted in laboratories with the use of camera systems and markers placed on the body, or through the use of suits containing large numbers (15-20) of inertial measurement units. However, to aid with rehabilitation of individuals with impaired balance, there needs to be an option to collect these observations outside of clinics and without incurring much cost from the user. I have focused on three inertial measurement units, one placed on each shank and one placed on the upper torso, to record posture and estimate where an individual's center of mass is located. The use of three inertial measurement units significantly reduces the cost and encumbrance for studying balance in an individual's primary environment. This reduction comes at the cost of accuracy, which is explored further through this thesis. First, I looked at different methods used for determining IMU orientation, such as a biologically inspired orientation algorithm and a gradient descent algorithm. I then incorporated those methods to create a model of the body that calculates an estimate on the center of mass, based on the user's weight and height. Finally, this estimate is compared to a force plate derived method of finding center of mass to determine viability of sensor reduction for practical applications. The created algorithm is able to generate a center of mass location that is able to match the actual location within 3 cm.

Download or read book Microsensors written by Julian W. Gardner and published by . This book was released on 1994-09-06 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Devoted primarily to the many applications of microsensors, this text covers thermal, radiation, mechanical, magnetic, chemical and biological microsensors. Information is also provided on basic processing, interfacing and bus systems, microsensor array and intelligent sensors.