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Journal articles on the topic 'Inertial and magnetic sensors'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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1

Wada, Tomohito, Mirai Mizutani, James Lee, David Rowlands, and Daniel James. "3D Visualisation of Wearable Inertial/Magnetic Sensors." Proceedings 2, no. 6 (2018): 292. http://dx.doi.org/10.3390/proceedings2060292.

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2

Bonnet, S., C. Bassompierre, C. Godin, S. Lesecq, and A. Barraud. "Calibration methods for inertial and magnetic sensors." Sensors and Actuators A: Physical 156, no. 2 (2009): 302–11. http://dx.doi.org/10.1016/j.sna.2009.10.008.

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3

Piso, M. I. "Applications of magnetic fluids for inertial sensors." Journal of Magnetism and Magnetic Materials 201, no. 1-3 (1999): 380–84. http://dx.doi.org/10.1016/s0304-8853(99)00164-x.

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4

Worsey, Espinosa, Shepherd, and Thiel. "A Systematic Review of Performance Analysis in Rowing Using Inertial Sensors." Electronics 8, no. 11 (2019): 1304. http://dx.doi.org/10.3390/electronics8111304.

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Sporting organizations such as professional clubs and national sport institutions are constantly seeking novel training methodologies in an attempt to give their athletes a cutting edge. The advent of microelectromechanical systems (MEMS) has facilitated the integration of small, unobtrusive wearable inertial sensors into many coaches’ training regimes. There is an emerging trend to use inertial sensors for performance monitoring in rowing; however, the use and selection of the sensor used has not been appropriately reviewed. Previous literature assessed the sampling frequency, position, and fixing of the sensor; however, properties such as the sensor operating ranges, data processing algorithms, and validation technology are left unevaluated. To address this gap, a systematic literature review on rowing performance monitoring using inertial-magnetic sensors was conducted. A total of 36 records were included for review, demonstrating that inertial measurements were predominantly used for measuring stroke quality and the sensors were used to instrument equipment rather than the athlete. The methodology for both selecting and implementing technology appeared ad hoc, with no guidelines for appropriate analysis of the results. This review summarizes a framework of best practice for selecting and implementing inertial sensor technology for monitoring rowing performance. It is envisaged that this review will act as a guide for future research into applying technology to rowing.

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Neto, Pedro, Nuno Mendes, and A. Paulo Moreira. "Kalman filter-based yaw angle estimation by fusing inertial and magnetic sensing: a case study using low cost sensors." Sensor Review 35, no. 3 (2015): 244–50. http://dx.doi.org/10.1108/sr-10-2014-0723.

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Purpose – The purpose of this paper is to achieve reliable estimation of yaw angles by fusing data from low-cost inertial and magnetic sensing. Design/methodology/approach – In this paper, yaw angle is estimated by fusing inertial and magnetic sensing from a digital compass and a gyroscope, respectively. A Kalman filter estimates the error produced by the gyroscope. Findings – Drift effect produced by the gyroscope is significantly reduced and, at the same time, the system has the ability to react quickly to orientation changes. The system combines the best of each sensor, the stability of the magnetic sensor and the fast response of the inertial sensor. Research limitations/implications – The system does not present a stable behavior in the presence of large vibrations. Considerable calibration efforts are needed. Practical implications – Today, most of human–robot interaction technologies need to have the ability to estimate orientation, especially yaw angle, from small-sized and low-cost sensors. Originality/value – Existing methods for inertial and magnetic sensor fusion are combined to achieve reliable estimation of yaw angle. Experimental tests in a human–robot interaction scenario show the performance of the system.

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Patonis, Photis, Petros Patias, Ilias N. Tziavos, Dimitrios Rossikopoulos, and Konstantinos G. Margaritis. "A Fusion Method for Combining Low-Cost IMU/Magnetometer Outputs for Use in Applications on Mobile Devices." Sensors 18, no. 8 (2018): 2616. http://dx.doi.org/10.3390/s18082616.

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This paper presents a fusion method for combining outputs acquired by low-cost inertial measurement units and electronic magnetic compasses. Specifically, measurements of inertial accelerometer and gyroscope sensors are combined with no-inertial magnetometer sensor measurements to provide the optimal three-dimensional (3D) orientation of the sensors’ axis systems in real time. The method combines Euler–Cardan angles and rotation matrix for attitude and heading representation estimation and deals with the “gimbal lock” problem. The mathematical formulation of the method is based on Kalman filter and takes into account the computational cost required for operation on mobile devices as well as the characteristics of the low-cost microelectromechanical sensors. The method was implemented, debugged, and evaluated in a desktop software utility by using a low-cost sensor system, and it was tested in an augmented reality application on an Android mobile device, while its efficiency was evaluated experimentally.

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Yang, Zhicheng, Shenggang Yan, Bert-Jan F. van Beijnum, Bin Li, and Peter H. Veltink. "Hand-Finger Pose Estimation Using Inertial Sensors, Magnetic Sensors and a Magnet." IEEE Sensors Journal 21, no. 16 (2021): 18115–22. http://dx.doi.org/10.1109/jsen.2021.3085993.

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8

de Vries, W. H. K., H. E. J. Veeger, C. T. M. Baten, and F. C. T. van der Helm. "Magnetic distortion in motion labs, implications for validating inertial magnetic sensors." Gait & Posture 29, no. 4 (2009): 535–41. http://dx.doi.org/10.1016/j.gaitpost.2008.12.004.

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9

Campolo, Domenico, Fabrizio Taffoni, Domenico Formica, Giuseppina Schiavone, Flavio Keller, and Eugenio Guglielmelli. "Inertial-Magnetic Sensors for Assessing Spatial Cognition in Infants." IEEE Transactions on Biomedical Engineering 58, no. 5 (2011): 1499–503. http://dx.doi.org/10.1109/tbme.2011.2105871.

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10

Kortier, Henk G., Victor I. Sluiter, Daniel Roetenberg, and Peter H. Veltink. "Assessment of hand kinematics using inertial and magnetic sensors." Journal of NeuroEngineering and Rehabilitation 11, no. 1 (2014): 70. http://dx.doi.org/10.1186/1743-0003-11-70.

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Zmitri, Makia, Hassen Fourati, and Christophe Prieur. "Magnetic Field Gradient-Based EKF for Velocity Estimation in Indoor Navigation." Sensors 20, no. 20 (2020): 5726. http://dx.doi.org/10.3390/s20205726.

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This paper proposes an advanced solution to improve the inertial velocity estimation of a rigid body, for indoor navigation, through implementing a magnetic field gradient-based Extended Kalman Filter (EKF). The proposed estimation scheme considers a set of data from a triad of inertial sensors (accelerometer and gyroscope), as well as a determined arrangement of magnetometers array. The inputs for the estimation scheme are the spatial derivatives of the magnetic field, from the magnetometers array, and the attitude, from the inertial sensors. As shown in the literature, there is a strong relation between the velocity and the measured magnetic field gradient. However, the latter usually suffers from high noises. Then, the novelty of the proposed EKF is to develop a specific equation to describe the dynamics of the magnetic field gradient. This contribution helps to filter, first, the magnetic field and its gradient and second, to better estimate the inertial velocity. Some numerical simulations that are based on an open source database show the targeted improvements. At the end of the paper, this approach is extended to position estimation in the case of a foot-mounted application and the results are very promising.

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12

Valtin, Markus, Christina Salchow, Thomas Seel, Daniel Laidig, and Thomas Schauer. "Modular finger and hand motion capturing system based on inertial and magnetic sensors." Current Directions in Biomedical Engineering 3, no. 1 (2017): 19–23. http://dx.doi.org/10.1515/cdbme-2017-0005.

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Abstract:The assessment of hand posture and kinematics is increasingly important in various fields. This includes the rehabilitation of stroke survivors with restricted hand function. This paper presents a modular, ambulatory measurement system for the assement of the remaining hand function and for closed-loop controlled therapy. The device is based on inertial sensors and utilizes up to five interchangeable sensor strips to achieve modularity and to simplify the sensor attachment. We introduce the modular hardware design and describe algorithms used to calculate the joint angles. Measurements with two experimental setups demonstrate the feasibility and the potential of such a tracking device.

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13

Qiu, Sen, Zhelong Wang, Hongyu Zhao, Kairong Qin, Zhenglin Li, and Huosheng Hu. "Inertial/magnetic sensors based pedestrian dead reckoning by means of multi-sensor fusion." Information Fusion 39 (January 2018): 108–19. http://dx.doi.org/10.1016/j.inffus.2017.04.006.

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14

Liu, Xiao Yan, and Zhao Ying Zhou. "Application of Inertial and Magnetic Sensors in Human Fall Detection." Advanced Materials Research 317-319 (August 2011): 1590–93. http://dx.doi.org/10.4028/www.scientific.net/amr.317-319.1590.

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Fall is a risky event in the elderly people’s daily life, it often cause serious injury both in physiology and psychology. An inertial and magnetic sensor based system is designed for fall detection in real time. This paper presents the design and test of this system. The system consists of three attitude measurement units fixed on the human legs and waist. Each unit contains orthogonally mounted triads of accelerometers, magnetometers and gyros. With an integrated microcontroller for attitude calculating and flash for data storage, the size of the unit is 32mm×23mm×12mm. An extended Kalman filter based on quaternions is designed for attitude measurement. The digital angle output rate is 100Hz. Human lower limb kinematic model is presented. The position of the gravity center is tracking by the inertial and magnetic sensing system.

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15

Choi, Ho-Rim, Mun-Ho Ryu, Yoon-Seok Yang, and Seong-Hyun Kim. "Upper Limb Position Tracking System Using Inertial and Magnetic Sensors." Sensor Letters 10, no. 5 (2012): 1119–24. http://dx.doi.org/10.1166/sl.2012.2273.

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Choi, H. R., M. H. Ryu, and Y. S. Yang. "Human Body Orientation Tracking System Using Inertial and Magnetic Sensors." Journal of Biomedical Engineering Research 32, no. 2 (2011): 118–26. http://dx.doi.org/10.9718/jber.2011.32.2.118.

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17

Fantozzi, Silvia, Andrea Giovanardi, Davide Borra, and Giorgio Gatta. "Gait Kinematic Analysis in Water Using Wearable Inertial Magnetic Sensors." PLOS ONE 10, no. 9 (2015): e0138105. http://dx.doi.org/10.1371/journal.pone.0138105.

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18

Miao, Cunxiao, Qingdong Zhang, Jiancheng Fang, and Xusheng Lei. "Design of orientation estimation system by inertial and magnetic sensors." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 228, no. 7 (2013): 1105–13. http://dx.doi.org/10.1177/0954410013485523.

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19

Becq, Guillaume, Stéphane Bonnet, Lorella Minotti, Michel Antonakios, Régis Guillemaud, and Philippe Kahane. "Classification of epileptic motor manifestations using inertial and magnetic sensors." Computers in Biology and Medicine 41, no. 1 (2011): 46–55. http://dx.doi.org/10.1016/j.compbiomed.2010.11.005.

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20

Picerno, P., A. Cereatti, and A. Cappozzo. "A spot check for estimating inertial and magnetic sensors errors." Gait & Posture 30 (October 2009): S71. http://dx.doi.org/10.1016/j.gaitpost.2009.07.072.

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21

Yu, Jing, Xiongzhu Bu, Chao Xiang, and Bo Yang. "Spinning projectile’s attitude measurement using intersection ratio of magnetic sensors." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 231, no. 5 (2016): 866–76. http://dx.doi.org/10.1177/0954410016644628.

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Concerning on the problem of low measuring precision of the current micro-inertial sensors, a novel attitude measurement method is proposed to dismiss the drift for remarkable attitude error. According to the output of the onboard three-axis magnetic sensor in the process of projectile flight, a low-cost attitude detection system is designed by using the intersection ratio of the sensor. First, the output model of the onboard three-axis magnetic sensor is established. The mathematical relationship between the characteristic ratio of magnetic sensor output and the pitch angle is then derived. Then, the solution and correction algorithm of the attitude angles are studied. Finally, the effectiveness of the attitude measurement method has been validated by carrying out the semi-physical experiments. The experimental results indicate that the error of attitude angles is within ±1° and the attitude angle error of the combined magnetic sensors is not cumulative. Meanwhile, the geomagnetic field strength is dispensable during the whole calculation process. Compared with the “Zero Crossing Method”, the proposed method has shown a nearly two-times higher accuracy and has no limitation of “MAGSONDE window”. What is more, this method proves to be more simple and has a doubled update rate in attitude angle calculation.

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22

Tjhai, Chandra, and Kyle O’Keefe. "Using Step Size and Lower Limb Segment Orientation from Multiple Low-Cost Wearable Inertial/Magnetic Sensors for Pedestrian Navigation." Sensors 19, no. 14 (2019): 3140. http://dx.doi.org/10.3390/s19143140.

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This paper demonstrates the use of multiple low-cost inertial/magnetic sensors as a pedestrian navigation system for indoor positioning. This research looks at the problem of pedestrian navigation in a practical manner by investigating dead-reckoning methods using low-cost sensors. This work uses the estimated sensor orientation angles to compute the step size from the kinematics of a skeletal model. The orientations of limbs are represented by the tilt angles estimated from the inertial measurements, especially the pitch angle. In addition, different step size estimation methods are compared. A sensor data logging system is developed in order to record all motion data from every limb segment using a single platform and similar types of sensors. A skeletal model of five segments is chosen to model the forward kinematics of the lower limbs. A treadmill walk experiment with an optical motion capture system is conducted for algorithm evaluation. The mean error of the estimated orientation angles of the limbs is less than 6 degrees. The results show that the step length mean error is 3.2 cm, the left stride length mean error is 12.5 cm, and the right stride length mean error is 9 cm. The expected positioning error is less than 5% of the total distance travelled.

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23

Cuervo, Mauro Callejas, Manuel A. Vélez-Guerrero, and Andrea C. Alarcón-Aldana. "Proposal for Gait Analysis Using Fusion of Inertial-Magnetic and Optical Sensors." Revista EIA 17, no. 34 (2020): 1–11. http://dx.doi.org/10.24050/reia.v17i34.1472.

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A proposed measurement protocol for the lower limbs movement analysis during walking is presented, with the use of a measurement system based on inertial-magnetic motion processing units and an optical system. Initially, the state of the art in terms of methods and tools for the biomechanical capture of movements is shown, to finally explore the protocols used in the health sciences for the gait analysis. The measurement proposal made in this document uses robust features of inertial-magnetic and optical technology that can be used in medical diagnosis. The application of this proposal can generate tools that have a positive impact in the fields of health and medicine.

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Schmidt, Marcus, Tobias Alt, Kevin Nolte, and Thomas Jaitner. "Comment on “Hurdle Clearance Detection and Spatiotemporal Analysis in 400 Meters Hurdles Races Using Shoe-Mounted Magnetic and Inertial Sensor”." Sensors 20, no. 10 (2020): 2995. http://dx.doi.org/10.3390/s20102995.

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The recent paper “Hurdle Clearance Detection and Spatiotemporal Analysis in 400 Meters Hurdles Races Using Shoe-Mounted Magnetic and Inertial Sensor” (Sensors 2020, 20, 354) proposes a wearable system based on a foot-worn miniature inertial measurement unit (MIMU) and different methods to detect hurdle clearance and to identify the leading leg during 400-m hurdle races. Furthermore, the presented system identifies changes in contact time, flight time, running speed, and step frequency throughout the race. In this comment, we discuss the original paper with a focus on the ecological validity and the applicability of MIMU systems for field-based settings, such as training or competition for elite athletes.

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Voinea, Gheorghe Daniel, and Gheorghe Mogan. "Development of a Wearable Scoliosis Monitoring System Using Inertial Sensors." Applied Mechanics and Materials 811 (November 2015): 353–58. http://dx.doi.org/10.4028/www.scientific.net/amm.811.353.

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Monitoring human motion with magnetic and inertial measurement units is a complex task and there are many factors that must be taken into consideration. In this work, a wearable system for monitoring scoliosis using three inertial measurement units (IMUs) is introduced. The proposed solution can be used indoor and is focused on using the roll angle for measuring lateral movement of the spine, which characterizes the scoliosis spinal disorder.

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Bouvier, Brice, Sonia Duprey, Laurent Claudon, Raphaël Dumas, and Adriana Savescu. "Upper Limb Kinematics Using Inertial and Magnetic Sensors: Comparison of Sensor-to-Segment Calibrations." Sensors 15, no. 8 (2015): 18813–33. http://dx.doi.org/10.3390/s150818813.

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27

Podoprosvetov, Aleksei Valerievich, Anton Pavlovich Aliseychik, Igor Aleksandrovich Orlov, and Sergei Petrovich Rebrik. "Calibration Algorithm for MIMU Sensors Group." Keldysh Institute Preprints, no. 43 (2021): 1–16. http://dx.doi.org/10.20948/prepr-2021-43.

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Non-optical wearable sensors, such as magnetic and inertial measuring units (MIMU), are becoming popular in various fields: sports, medical, industrial - due to their ease of use and relative availability. We propose an algorithm for calibrating wearable sensors based on the rotation algebra. A system for visualizing human kinematics, which is reconstructed from MIMUs' data, is presented.

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Gao, Mingjing, Min Yu, Hang Guo, and Yuan Xu. "Mobile Robot Indoor Positioning Based on a Combination of Visual and Inertial Sensors." Sensors 19, no. 8 (2019): 1773. http://dx.doi.org/10.3390/s19081773.

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Multi-sensor integrated navigation technology has been applied to the indoor navigation and positioning of robots. For the problems of a low navigation accuracy and error accumulation, for mobile robots with a single sensor, an indoor mobile robot positioning method based on a visual and inertial sensor combination is presented in this paper. First, the visual sensor (Kinect) is used to obtain the color image and the depth image, and feature matching is performed by the improved scale-invariant feature transform (SIFT) algorithm. Then, the absolute orientation algorithm is used to calculate the rotation matrix and translation vector of a robot in two consecutive frames of images. An inertial measurement unit (IMU) has the advantages of high frequency updating and rapid, accurate positioning, and can compensate for the Kinect speed and lack of precision. Three-dimensional data, such as acceleration, angular velocity, magnetic field strength, and temperature data, can be obtained in real-time with an IMU. The data obtained by the visual sensor is loosely combined with that obtained by the IMU, that is, the differences in the positions and attitudes of the two sensor outputs are optimally combined by the adaptive fade-out extended Kalman filter to estimate the errors. Finally, several experiments show that this method can significantly improve the accuracy of the indoor positioning of the mobile robots based on the visual and inertial sensors.

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SABATINI, ANGELO MARIA. "ADAPTIVE FILTERING ALGORITHMS ENHANCE THE ACCURACY OF LOW-COST INERTIAL/MAGNETIC SENSING IN PEDESTRIAN NAVIGATION SYSTEMS." International Journal of Computational Intelligence and Applications 07, no. 03 (2008): 351–61. http://dx.doi.org/10.1142/s1469026808002326.

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The availability of inexpensive, miniaturized sensors and the development of efficient and accurate filtering algorithms are important elements in order that pedestrian navigation system (PNS) will become an enabling technology for monitoring unconstrained daily living activities of human subjects. In this paper, we develop and test a computational method that estimates the path traveled by a walker from in-shoe mounted tri-axis inertial and magnetic sensors. The interest for inertial and magnetic sensors stems from their low cost, suitable form factors, small power consumption, which may give rise to self-contained, portable PNS whose hindrance to walking is limited. An important element in our approach is represented by an extended Kalman filter (EKF), whose aim is to estimate the body part orientation and to perform the in-line calibration of the tri-axis magnetometer. Two validation tests are applied to either acceleration or magnetic vector measurements, in order to adapt the measurement noise covariance matrix against the effects of body motion and external magnetic fields on the sensed gravity and earth's magnetic fields involved in orientation determination. Additionally, some biomechanical facts about how humans normally move are exploited to enhance the positioning performance of the developed method.

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MARUYAMA, Yutaka, Takeshi MIZUNO, Masaya TAKASAKI, Yuji ISHINO, Takayuki ISHIGAMI, and Hironori KAMENO. "An Application of Active Magnetic Bearing to Gyroscopic and Inertial Sensors." Journal of System Design and Dynamics 2, no. 1 (2008): 155–64. http://dx.doi.org/10.1299/jsdd.2.155.

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31

Tang, Zunyi, Masaki Sekine, Toshiyo Tamura, Noriko Tanaka, Masaki Yoshida, and Wenxi Chen. "Measurement and Estimation of 3D Orientation using Magnetic and Inertial Sensors." Advanced Biomedical Engineering 4 (2015): 135–43. http://dx.doi.org/10.14326/abe.4.135.

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32

Sammarco, J. J. "Mining machine orientation control based on inertial, gravitational, and magnetic sensors." IEEE Transactions on Industry Applications 28, no. 5 (1992): 1126–30. http://dx.doi.org/10.1109/28.158838.

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33

Byun and Lee. "Implementation of Hand Gesture Recognition Device Applicable to Smart Watch Based on Flexible Epidermal Tactile Sensor Array." Micromachines 10, no. 10 (2019): 692. http://dx.doi.org/10.3390/mi10100692.

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Ever since the development of digital devices, the recognition of human gestures has played an important role in many Human-Computer interface applications. Various wearable devices have been developed, and inertial sensors, magnetic sensors, gyro sensors, electromyography, force-sensitive resistors, and other types of sensors have been used to identify gestures. However, there are different drawbacks for each sensor, which affect the detection of gestures. In this paper, we present a new gesture recognition method using a Flexible Epidermal Tactile Sensor based on strain gauges to sense deformation. Such deformations are transduced to electric signals. By measuring the electric signals, the sensor can estimate the degree of deformation, including compression, tension, and twist, caused by movements of the wrist. The proposed sensor array was demonstrated to be capable of analyzing the eight motions of the wrist, and showed robustness, stability, and repeatability throughout a range of experiments aimed at testing the sensor array. We compared the performance of the prototype device with those of previous studies, under the same experimental conditions. The result shows our recognition method significantly outperformed existing methods.

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Lee, Jung Keun, and Tae Hyeong Jeon. "Magnetic Condition-Independent 3D Joint Angle Estimation Using Inertial Sensors and Kinematic Constraints." Sensors 19, no. 24 (2019): 5522. http://dx.doi.org/10.3390/s19245522.

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In biomechanics, joint angle estimation using wearable inertial measurement units (IMUs) has been getting great popularity. However, magnetic disturbance issue is considered problematic as the disturbance can seriously degrade the accuracy of the estimated joint angles. This study proposes a magnetic condition-independent three-dimensional (3D) joint angle estimation method based on IMU signals. The proposed method is implemented in a sequential direction cosine matrix-based orientation Kalman filter (KF), which is composed of an attitude estimation KF followed by a heading estimation KF. In the heading estimation KF, an acceleration-level kinematic constraint from a spherical joint replaces the magnetometer signals for the correction procedure. Because the proposed method does not rely on the magnetometer, it is completely magnetic condition-independent and is not affected by the magnetic disturbance. For the averaged root mean squared errors of the three tests performed using a rigid two-link system, the proposed method produced 1.58°, while the conventional method with the magnetic disturbance compensation mechanism produced 5.38°, showing a higher accuracy of the proposed method in the magnetically disturbed conditions. Due to the independence of the proposed method from the magnetic condition, the proposed approach could be reliably applied in various fields that require robust 3D joint angle estimation through IMU signals in an unspecified arbitrary magnetic environment.

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Qiu, Sen, Long Liu, Hongyu Zhao, Zhelong Wang, and Yongmei Jiang. "MEMS Inertial Sensors Based Gait Analysis for Rehabilitation Assessment via Multi-Sensor Fusion." Micromachines 9, no. 9 (2018): 442. http://dx.doi.org/10.3390/mi9090442.

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Gait and posture are regular activities which are fully controlled by the sensorimotor cortex. In this study, fluctuations of joint angle and asymmetry of foot elevation in human walking stride records are analyzed to assess gait in healthy adults and patients affected with gait disorders. This paper aims to build a low-cost, intelligent and lightweight wearable gait analysis platform based on the emerging body sensor networks, which can be used for rehabilitation assessment of patients with gait impairments. A calibration method for accelerometer and magnetometer was proposed to deal with ubiquitous orthoronal error and magnetic disturbance. Proportional integral controller based complementary filter and error correction of gait parameters have been defined with a multi-sensor data fusion algorithm. The purpose of the current work is to investigate the effectiveness of obtained gait data in differentiating healthy subjects and patients with gait impairments. Preliminary clinical gait experiments results showed that the proposed system can be effective in auxiliary diagnosis and rehabilitation plan formulation compared to existing methods, which indicated that the proposed method has great potential as an auxiliary for medical rehabilitation assessment.

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Wang, Cuo, Xingfei Li, Ke Kou, and Chunguo Long. "Optimization of magnetic hat for quartz flexible accelerometer." Sensor Review 36, no. 1 (2016): 71–76. http://dx.doi.org/10.1108/sr-04-2015-0067.

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Purpose – This study aims to ameliorate the strength and uniformity of the magnetic field in the air-gap of quartz flexible accelerometers. Quartz flexible accelerometers (QFAs), a type of magneto-electric inertial sensors, have wide applications in inertial navigation systems, and their precision, linearity and stability performance are largely determined by the magnetic field in operation air-gap. To enhance the strength and uniformity of the magnetic field in the air-gap, a magnetic hat structure has been proposed to replace the traditional magnetic pole piece which tends to produce stratiform magnetic field distribution. Design/methodology/approach – Three-dimensional analysis in ANSYS workbench helps to exhibit magnetic field distribution for the structures with a pole piece and a magnetic hat, and under the hypothesis of cylindrical symmetry, two-dimensional finite element optimization by ANSYS APDL gives an optimal set of dimensions of the magnetic hat. Findings – Three structures of the QFA with a pole piece, a non-optimized magnetic hat and an optimized magnetic hat are compared by the simulation in ANSYS Maxwell and experiments measuring the electromagnetic rebalance force. The results show that the optimized hat can supply stronger and more uniform magnetic field, which is reflected by larger and more linear rebalance force. Originality/value – To the authors ' knowledge, the magnetic hat and its dimension optimization have rarely been reported, and they can find significant applications in designing QFAs or other similar magnetic sensors.

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HIROSE, Kiyoshi, Hitoshi DOKI, and Akiko KONDO. "Studies on Orientation Measurement in Sports Using Inertial and Magnetic Field Sensors." Journal of Japan Society of Sports Industry 22, no. 2 (2012): 255–62. http://dx.doi.org/10.5997/sposun.22.255.

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Altun, Kerem, Billur Barshan, and Orkun Tunçel. "Comparative study on classifying human activities with miniature inertial and magnetic sensors." Pattern Recognition 43, no. 10 (2010): 3605–20. http://dx.doi.org/10.1016/j.patcog.2010.04.019.

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Papafotis, Konstantinos, and Paul P. Sotiriadis. "MAG.I.C.AL.–A Unified Methodology for Magnetic and Inertial Sensors Calibration and Alignment." IEEE Sensors Journal 19, no. 18 (2019): 8241–51. http://dx.doi.org/10.1109/jsen.2019.2919179.

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Campolo, Domenico, Fabrizio Taffoni, Domenico Formica, et al. "Embedding inertial-magnetic sensors in everyday objects: Assessing spatial cognition in children." Journal of Integrative Neuroscience 11, no. 01 (2012): 103–16. http://dx.doi.org/10.1142/s0219635212500070.

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Fourati, Hassen, Noureddine Manamanni, Lissan Afilal, and Yves Handrich. "Complementary Observer for Body Segments Motion Capturing by Inertial and Magnetic Sensors." IEEE/ASME Transactions on Mechatronics 19, no. 1 (2014): 149–57. http://dx.doi.org/10.1109/tmech.2012.2225151.

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van den Noort, Josien C., Alberto Ferrari, Andrea G. Cutti, Jules G. Becher, and Jaap Harlaar. "Gait analysis in children with cerebral palsy via inertial and magnetic sensors." Medical & Biological Engineering & Computing 51, no. 4 (2012): 377–86. http://dx.doi.org/10.1007/s11517-012-1006-5.

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Picerno, P., P. Caliandro, C. Simbolotti, et al. "Anatomical calibration of inertial and magnetic sensors for estimating upper limb kinematics." Gait & Posture 57 (September 2017): 28–29. http://dx.doi.org/10.1016/j.gaitpost.2017.07.087.

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Cutti, Andrea Giovanni, Andrea Giovanardi, Laura Rocchi, Angelo Davalli, and Rinaldo Sacchetti. "Ambulatory measurement of shoulder and elbow kinematics through inertial and magnetic sensors." Medical & Biological Engineering & Computing 46, no. 2 (2007): 169–78. http://dx.doi.org/10.1007/s11517-007-0296-5.

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Suh, Young Soo. "l 1 Norm Regularization Robust Attitude Smoother Using Inertial and Magnetic Sensors." IEEE Transactions on Instrumentation and Measurement 70 (2021): 1–9. http://dx.doi.org/10.1109/tim.2021.3094233.

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46

Abdulrahim, Khairi, Chris Hide, Terry Moore, and Chris Hill. "Aiding Low Cost Inertial Navigation with Building Heading for Pedestrian Navigation." Journal of Navigation 64, no. 2 (2011): 219–33. http://dx.doi.org/10.1017/s0373463310000573.

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Abstract:

In environments where GNSS is unavailable or not useful for positioning, the use of low cost MEMS-based inertial sensors has paved a way to a more cost effective solution. Of particular interest is a foot mounted pedestrian navigation system, where zero velocity updates (ZUPT) are used with the standard strapdown navigation algorithm in a Kalman filter to restrict the error growth of the low cost inertial sensors. However heading drift still remains despite using ZUPT measurements since the heading error is unobservable. External sensors such as magnetometers are normally used to mitigate this problem, but the reliability of such an approach is questionable because of the existence of magnetic disturbances that are often very difficult to predict. Hence there is a need to eliminate the heading drift problem for such a low cost system without relying on external sensors to give a possible stand-alone low cost inertial navigation system. In this paper, a novel and effective algorithm for generating heading measurements from basic knowledge of the orientation of the building in which the pedestrian is walking is proposed to overcome this problem. The effectiveness of this approach is demonstrated through three field trials using only a forward Kalman filter that can work in real-time without any external sensors. This resulted in position accuracy better than 5 m during a 40 minutes walk, about 0·1% in position error of the total distance. Due to its simplistic algorithm, this simple yet very effective solution is appealing for a promising future autonomous low cost inertial navigation system.

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Rüschen, Daniel, Berno J. E. Misgeld, Saim Kim, and Steffen Leonhardt. "A Novel Algorithm for the Calibration of Inertial/Magnetic Sensors: Application to a Body Sensor Network." Acta Mechanica Slovaca 18, no. 2 (2014): 42–49. http://dx.doi.org/10.21496/ams.2014.018.

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Sandino, Luis A., Manuel Bejar, Konstantin Kondak, and Anibal Ollero. "Multi-Sensor Data Fusion for a Tethered Unmanned Helicopter Using a Square-Root Unscented Kalman Filter." Unmanned Systems 04, no. 04 (2016): 273–87. http://dx.doi.org/10.1142/s2301385016500114.

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The use of tethered Unmanned Aircraft Systems (UAS) in aerial robotic applications is a relatively unexplored research field. This work addresses the attitude and position estimation of a small-size unmanned helicopter tethered to a moving platform using a multi-sensor data fusion algorithm based on a numerically efficient sigma-point Kalman filter implementation. For that purpose, the state prediction is performed using a kinematic process model driven by measurements of the inertial sensors (accelerometer and gyroscope) onboard the helicopter and the subsequent correction is done using information from additional sensors like magnetometer, barometric altimeter, LIDAR altimeter and magnetic encoders measuring the tether orientation relative to the helicopter. Assuming the tether is kept taut by an actuated device on the platform during the system operation, the helicopter position is estimated relative to the anchor point. Although this configuration avoids the need of a GPS, a standard operation mode for estimation of the absolute position (the position relative to the inertial reference frame) incorporating corrections with the GPS position and velocity measurements, is also implemented in order to highlight the benefits of the proposed tethered setup. The filter performance is evaluated in simulations.

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Bieszczad, Grzegorz, Krzysztof Sawicki, Sławomir Gogler, Andrzej Ligienza, and Mariusz Mścichowski. "Thermal Imaging Camera Supporting the Navigation of UAVs." Pomiary Automatyka Robotyka 25, no. 3 (2021): 43–50. http://dx.doi.org/10.14313/par_241/43.

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The topic of this paper is an evaluation of developed sensor intended for navigation aid of unmanned aerial vehicles (UAVs). Its operation is based on processing images acquired with a thermal camera operating in the long-wave infrared band (LWIR) placed underneath a vehicle’s chassis. The vehicle’s spatial displacement is determined by analyzing movement of characteristic thermal radiation points (ground, forest, buildings, etc.) in pictures acquired by the thermal camera. Magnitude and direction of displacement is obtained by processing the stream of consecutive pictures with optical-flow based algorithm in real time. Radiation distribution analysis allows to calculate camera’s self-translation vector. Advantages of measuring translation based on thermal image analysis is lack of drift effect, resistance to magnetic field variations, low susceptibility to electromagnetic interference and change in weather conditions as compared to traditional inertial navigation sensors. As opposed to visible light situational awareness sensors, it offers operation in complete darkness (harsh weather, nights and indoors).The topic of this paper is an evaluation of developed sensor intended for navigation aid of unmanned aerial vehicles (UAVs). Its operation is based on processing images acquired from a thermal camera operating in the long wave infrared band (LWIR) placed underneath a vehicle’s chassis. The vehicle’s spatial displacement is determined by analyzing movement of characteristic thermal radiation points (ground, forest, buildings, etc.) in pictures acquired by the thermal camera. Magnitude and direction of displacement is obtained by processing the stream of consecutive pictures with optical-flow based algorithm in real time. Radiation distribution analysis allows to calculate camera’s self-translation vector. Advantages of measuring translation based on thermal image analysis is lack of drift effect, resistance to magnetic field variations, low susceptibility to electromagnetic interference and change in weather conditions as compared to traditional inertial navigation sensors. As opposed to visible light situational awareness sensors, it offers operation in complete darkness (harsh weather, nights and indoors).

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Fan, Bingfei, Qingguo Li, Chao Wang, and Tao Liu. "An Adaptive Orientation Estimation Method for Magnetic and Inertial Sensors in the Presence of Magnetic Disturbances." Sensors 17, no. 5 (2017): 1161. http://dx.doi.org/10.3390/s17051161.

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