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Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a sensor fusion algorithm with Unscented Kalman Filter

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sensorS 2016年第9期16卷 1504-1504页

作者： Chowdhury, Amor Sarjas, Andrej Margento R&D Gosposvetska Cesta 84 Maribor 2000 Slovenia Univ Maribor Fac Elect Engn & Comp Sci Smetanova 17 SLO-2000 Maribor Slovenia

The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation.

关键词： accurate proximity measurement sensor fusion algorithm Unscented Kalman Filter finite element modelling

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Comparison of Computational Efficiency of Magneto Inertial sensor fusion algorithms for ChakaMo 24th

Comparison of Computational Efficiency of Magneto Inertial S...

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24th Argentinian Congress of Bioengineering (SABI) / 13th Clinical Engineering Conference (SABI)

作者： Rene Ledezma, Maria Simini, Franco Univ Republica Nucleo Ingn Biomed Montevideo Uruguay

ISBN: (纸本)9783031619595;9783031619601

During human motion tracking there are several tools that allow the analysis of joints during motor tasks. One of these devices is the magneto-inertial sensor that estimates the orientation of each limb segment and consequently the articulation kinematics. The orientation estimation with the magneto-inertial sensors relies heavily on the combined calculation with data from accelerometer, gyroscope and magnetometer, for which sensor fusion algorithms are used. At the moment there is no generic algorithm that works for all motor tasks, therefore, we compared in this work four sensor fusion algorithms to find out which one has the best behavior during a knee flexion and extension phantom simulation. After a complex comparison based on the computational efficiency, implementation easiness and minor root mean square error, the Guo algorithm is chosen over Madgwick and two Valenti options. The selected algorithm is used in the development of ChakaMo, a clinical tool for 3D analysis of the knee during step up and down motor task.

关键词： sensor fusion algorithm Knee kinematics Biomechanics

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sensor fusion algorithms for orientation tracking via magnetic and inertial measurement units: An experimental comparison survey

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INFORMATION fusion 2021年 76卷 8-23页

作者： Nazarahari, Milad Rouhani, Hossein Univ Alberta Donadeo Innovat Ctr Engn Dept Mech Engn Edmonton AB T6G 1H9 Canada

Lightweight and low-cost wearable magnetic and inertial measurement units (MIMUs) have found numerous applications, such as aerial vehicle navigation or human motion analysis, where the 3D orientation tracking of a rigid body is of interest. However, due to the errors in measurements of gyroscope, accelerometer, and/or magnetometer inside a MIMU, numerous studies have proposed sensor fusion algorithms (SFAs) to estimate the 3D orientation accurately and robustly. This paper contributes to these efforts by performing an experimental comparison among a variety of SFAs. Notably, we compared the estimated orientation of 36 SFAs from the complementary filter and linear/extended/complementary/unscented/cubature Kalman filter families with the reference orientation obtained from a camera motion-capture system. The experimental study included data collection with a foot-worn MIMU where nine participants performed various short- and long-duration tasks. We shared the codes and sample of data in http://***/codes to enable other researchers to compare their works with the literature toward creating a comprehensive online repository for SFAs. To perform a fair comparison, we used the Particle Swarm Optimization routine to find the optimal adaptive gain tuning scheme for each SFAs, as recommended in the literature. Our experimental results showed that gyroscope static bias removal, in general, showed to be effective in reducing the estimation error of SFAs, specifically during long-duration trials. Moreover, our experimental results identified the SFAs with the highest accuracy from each family. We also reported the execution times for the selected SFAs from each family. This paper is among the first experimental comparison studies which provide such breadth of coverage across various SFAs for tracking orientation with MIMUs.

关键词： sensor fusion algorithm Attitude and heading reference system Complementary filter Linear/extended/complementary/unscented/ cubature Kalman filter Adaptive gain tuning Magnetic and inertial measurement units

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Evaluation of lower-body gait kinematics on outdoor surfaces using wearable sensors

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JOURNAL OF BIOMECHANICS 2024年 177卷 112401-112401页

作者： Shah, Vaibhav R. Dixon, Phillipe C. Willmott, Alexander P. Univ Montreal Inst Biomed Engn Fac Med 2900 Bd Edouard Montpetit Montreal PQ H3T 1J4 Canada Ste Justine Univ Hosp CRCHUSJ Res Ctr Montreal PQ Canada McGill Univ Dept Kinesiol & Phys Act 2900 Bd Edouard Montpetit Montreal PQ H3T 1J4 Canada Univ Lincoln Sch Sport & Exercise Sci Lincoln England

The effects of outdoor surfaces on gait are unclear due to difficulties associated with motion tracking outside laboratories. Today, inertial measurement unit (IMU) systems can be deployed to understand the biomechanical adaptations required to navigate real-world environments successfully. This study used IMUs devices to identify lower-limb kinematic adaptations while walking on outdoor surfaces. We hypothesize that gait adaptations between surface types will present as differences in lower-limb joint angles. Thirty able-bodied adults performed walking trials with IMUs on the lower back, thighs, and shanks. Outdoor walking surfaces were flat and even (flateven) (0 degrees grade cement), cobblestone, grass, slope up, slope down, stairs up, and stairs down. A complementary-based sensor fusion algorithm was used to compute hip and knee joint flexion-extension angles, and data were normalized to 100 % of the gait cycle based on foot-strike events. Flateven walking was compared against all other surfaces. Two-sample one-dimensional statistical parametric mapping (1d-SPM) t-tests were used to identify differences between angles (alpha <= 0.05). Significant differences in joint angles were identified when grass, slope up, slope down, stairs up, and stairs down walking were compared with flateven (p <= 0.005). Moreover, differences were found between slope and stair conditions (p <= 0.004). No significant differences were noted between flateven and cobblestone. This study demonstrates that gait adaptations driven by differences in surface types can be observed using IMU sensors in an outdoor setting.

关键词： Inertial measurement unit (IMU) Statistical parametric mapping (SPM) Complementary filter sensor fusion algorithm Outdoor gait analysis

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40 years of sensor fusion for orientation tracking via magnetic and inertial measurement units: Methods, lessons learned, and future challenges

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INFORMATION fusion 2021年 68卷 67-84页

作者： Nazarahari, Milad Rouhani, Hossein Univ Alberta Donadeo Innovat Ctr Engn Dept Mech Engn Edmonton AB T6G 1H9 Canada

Technological developments over the past two decades have resulted in the development of more accurate and lightweight low-cost magnetic and inertial measurement units (MIMUs). These developments have allowed the extensive application of MIMUs in various fields, specifically tracking the 3D orientation of a rigid body. Despite recent technological improvements, measurements from a tri-axial gyroscope, accelerometer, and/or magnetometer inside the MIMU are characterized by uncertainties. Numerous studies have been conducted to address these uncertainties and develop sensor fusion algorithms (SFAs) to estimate the 3D orientation accurately and robustly. This paper contributes to these efforts by providing a survey of the state-of-the-art SFAs for orientation estimation. We surveyed +250 publications, categorized the SFAs with various structures, identified the modifications proposed to improve their performance, and discussed the strengths and weaknesses of these approaches. We found that, while early SFAs were mostly a vector observation algorithm or an extended Kalman filter, to improve the computational efficiency, more recent works have developed SFAs with a complementary filter or complementary Kalman filter structure. At the same time, to improve the performance of the SFAs, several research teams have proposed various modifications to the basic structure of these filters, such as adaptive gain tuning or imperfect measurement rejection. We also provided an outlook on the lessons learned as well as the main challenges related to SFAs and discussed the practical steps toward developing an effective SFA. We have identified the need for benchmarking studies as the main challenge at the moment. This paper is among the first surveys which provide such breadth of coverage across different SFAs for tracking orientation with MIMUs.

关键词： sensor fusion algorithm Attitude and heading reference system Linear/extended Kalman filter Complementary Filter Adaptive gain tuning Magnetic and inertial measurement unit

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Benchmarking Dataset of Signals from a Commercial MEMS Magnetic-Angular Rate-Gravity (MARG) sensor Manipulated in Regions with and without Geomagnetic Distortion

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sensorS 2023年第8期23卷 3786-3786页

作者： Sonchan, Pontakorn Ratchatanantakit, Neeranut O-larnnithipong, Nonnarit Adjouadi, Malek Barreto, Armando Florida Int Univ Elect & Comp Engn Dept Miami FL 33174 USA

In this paper, we present the FIU MARG Dataset (FIUMARGDB) of signals from the tri-axial accelerometer, gyroscope, and magnetometer contained in a low-cost miniature magnetic-angular rate-gravity (MARG) sensor module (also known as magnetic inertial measurement unit, MIMU) for the evaluation of MARG orientation estimation algorithms. The dataset contains 30 files resulting from different volunteer subjects executing manipulations of the MARG in areas with and without magnetic distortion. Each file also contains reference ("ground truth") MARG orientations (as quaternions) determined by an optical motion capture system during the recording of the MARG signals. The creation of FIUMARGDB responds to the increasing need for the objective comparison of the performance of MARG orientation estimation algorithms, using the same inputs (accelerometer, gyroscope, and magnetometer signals) recorded under varied circumstances, as MARG modules hold great promise for human motion tracking applications. This dataset specifically addresses the need to study and manage the degradation of orientation estimates that occur when MARGs operate in regions with known magnetic field distortions. To our knowledge, no other dataset with these characteristics is currently available. FIUMARGDB can be accessed through the URL indicated in the conclusions section. It is our hope that the availability of this dataset will lead to the development of orientation estimation algorithms that are more resilient to magnetic distortions, for the benefit of fields as diverse as human-computer interaction, kinesiology, motor rehabilitation, etc.

关键词： MARG MIMU orientation estimation sensor fusion algorithm dataset orientation algorithm benchmarking

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An interpretable assessment of sensor's orientation in the Quaternion domain

An interpretable assessment of sensor's orientation in the Q...

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11th International Conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Gil Resina, Debora Navarrete, Manuel Ramirez, Esmitt Sanchez Ramos, Carles Garcia Calvo, Carlos Castells-Rufas, David Carrabina, Jordi Univ Autonoma Barcelona Comp Vis Ctr Bellaterra Spain Univ Autonoma Barcelona Microelect & Elect Syst Dept Bellaterra Spain Inst Anna Gironella Mundet Barcelona Spain

ISBN: (纸本)9781665404020

Magnetic and inertial measurement unit (MIMU) systems have been universally adopted in numerous navigation applications. These include domains such as aircraft, pedestrians, home automation, robots, etc. due to their advantages referring to price, size and accuracy. The fusion of the values recorded from magnetic and inertial sensors (magnetometer, accelerometer, gyroscope) can provide orientation with respect to the navigation path. Orientation can be given as either Euler angles or quaternions representing the rotation matrix associated with the orientation. The first is the commonest way since Euler angles can be easily interpreted in terms of yaw, pitch, and roll. However, their computation is ill-conditioned for some angulations due to a bad propagation of errors. Such intrinsic computational errors limit their use for free indoor, but equally affect the comparison and assessment of sensor fusion algorithms. In this paper, we present an assessment of orientation based on quaternion distances easy to interpret in terms of rotation axis and angle. We compare our approach to the standard assessment of orientation based on Euler angles in rotational trajectories around the three axes made using a Staubli robotic arm. Results show the more superior reliability of the quaternion distance and the intrinsic artifacts of Euler angles for representing the whole space of rotations.

关键词： MIMU assessment quaternion Euler angles orientation sensor fusion algorithm

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HeadUp: A Low-Cost Solution for Tracking Head Movement of Children with Cerebral Palsy Using IMU

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sensorS 2021年第23期21卷 8148页

作者： Al-azzawi, Sana Sabah Khaksar, Siavash Hadi, Emad Khdhair Agrawal, Himanshu Murray, Iain Lulea Univ Technol SRT Dept EISLAB S-97187 Lulea Sweden Univ Informat Technol & Commun Coll Engn Baghdad 10013 Iraq Curtin Univ Sch Elect Engn Comp & Math Sci Bentley WA 6102 Australia Rehabil Med Ctr & Joint Dis Baghdad 10001 Iraq

Cerebral palsy (CP) is a common reason for human motor ability limitations caused before birth, through infancy or early childhood. Poor head control is one of the most important problems in children with level IV CP and level V CP, which can affect many aspects of children's lives. The current visual assessment method for measuring head control ability and cervical range of motion (CROM) lacks accuracy and reliability. In this paper, a HeadUp system that is based on a low-cost, 9-axis, inertial measurement unit (IMU) is proposed to capture and evaluate the head control ability for children with CP. The proposed system wirelessly measures CROM in frontal, sagittal, and transverse planes during ordinary life activities. The system is designed to provide real-time, bidirectional communication with an Euler-based, sensor fusion algorithm (SFA) to estimate the head orientation and its control ability tracking. The experimental results for the proposed SFA show high accuracy in noise reduction with faster system response. The system is clinically tested on five typically developing children and five children with CP (age range: 2-5 years). The proposed HeadUp system can be implemented as a head control trainer in an entertaining way to motivate the child with CP to keep their head up.

关键词： head control cerebral palsy rehabilitation inertial measurement unit head movement measurement health disability sensor fusion algorithm

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A sensor fusion algorithm for Filtering Pyrometer Measurement Noise in the Czochralski Crystallization Process

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MODELING IDENTIFICATION AND CONTROL 2011年第1期32卷 17-32页

作者： Komperod, M. Bones, J. A. Lie, B. Ostfold Univ Coll Fac Engn N-1757 Halden Norway SINTEF Mat & Chem Dept Met N-7465 Trondheim Norway Telemark Univ Coll Fac Technol N-3901 Porsgrunn Norway

The Czochralski (CZ) crystallization process is used to produce monocrystalline silicon for solar cell wafers and electronics. Tight temperature control of the molten silicon is most important for achieving high crystal quality. SINTEF Materials and Chemistry operates a CZ process. During one CZ batch, two pyrometers were used for temperature measurement. The silicon pyrometer measures the temperature of the molten silicon. This pyrometer is assumed to be accurate, but has much high-frequency measurement noise. The graphite pyrometer measures the temperature of a graphite material. This pyrometer has little measurement noise. There is quite a good correlation between the two pyrometer measurements. This paper presents a sensor fusion algorithm that merges the two pyrometer signals for producing a temperature estimate with little measurement noise, while having significantly less phase lag than traditional lowpass-filtering of the silicon pyrometer. The algorithm consists of two sub-algorithms: (i) A dynamic model is used to estimate the silicon temperature based on the graphite pyrometer, and (ii) a lowpass filter and a highpass filter designed as complementary filters. The complementary filters are used to lowpass-filter the silicon pyrometer, highpass-filter the dynamic model output, and merge these filtered signals. Hence, the lowpass filter attenuates noise from the silicon pyrometer, while the graphite pyrometer and the dynamic model estimate those frequency components of the silicon temperature that are lost when lowpass-filtering the silicon pyrometer. The algorithm works well within a limited temperature range. To handle a larger temperature range, more research must be done to understand the process' nonlinear dynamics, and build this into the dynamic model.

关键词： Complementary filters Czochralski crystallization process Measurement noise filtering Pyrometer temperature measurement sensor fusion algorithm

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Measuring Human Joint Movement with IMUs Implementation in custom-made low cost wireless sensors 15

Measuring Human Joint Movement with IMUs Implementation in c...

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15th IEEE Student Conference on Research and Development (IEEE SCOReD)

作者： Xu, W. Ortega-Sanchez, C. Murray, I. Curtin Univ Elect & Comp Engn Dept Perth WA Australia

ISBN: (纸本)9781538621264

This paper presents a inertial measurement unit (IMU) based wireless, wearable sensor system and its algorithm to capture human joint orientation and movement. Many physiotherapy and kinematical studies require a precise analysis of human joint movements. The proposed system provides an economic and flexible solution to measure human joint movement. The system includes several customised low-cost, small, wireless IMU sensors (accelerometer and gyroscope combined) which can be easily attached on any part of the human body. A dongle connected to a computer receives data collected by the sensors in real-time. Data sets are stored in the computer for later analysis and visualization. The proposed algorithm can accurately extract human joint orientation from the raw measurements of two inertial sensors. Compared to other yaw, pitch and roll orientation algorithms, the presented algorithm only focuses on the relative angle between two sensors instead of using a ground plane reference. The algorithm can be easily embedded into a post data analysis system. With its light data load requirement, the algorithm can also be effectively built onto a real-time joint orientation capturing system. This paper provides a high-level description of both the hardware platform and the demonstration of the algorithm, and presents step by step plots verifying the algorithm's performance. The system is currently used in a cerebral palsy research study in Australia.

关键词： Inertial measuerment unit motion capture joint angle tracking sensor fusion algorithm wireless system

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