Effect of local magnetic field disturbances on inertial measurement units accuracy

2017 ◽  
Vol 63 ◽  
pp. 123-132 ◽  
Author(s):  
Xavier Robert-Lachaine ◽  
Hakim Mecheri ◽  
Christian Larue ◽  
André Plamondon
Keyword(s):  
Magnetic Field ◽  
Local Magnetic Field ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Measurement Units

3D Magnetic Field Sensor Concept for Use in Inertial Measurement Units (IMUs)

2014 ◽  
Vol 23 (2) ◽  
pp. 324-333 ◽  
Author(s):  
Dirk Ettelt ◽  
Patrice Rey ◽  
Guillaume Jourdan ◽  
Arnaud Walther ◽  
Philippe Robert ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Magnetic Field Sensor ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Field Sensor

scholarly journals Validity of a Magnet-Based Timing System Using the Magnetometer Built into an IMU

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5773
Author(s):  
Carla Pérez-Chirinos Buxadé ◽  
Bruno Fernández-Valdés ◽  
Mónica Morral-Yepes ◽  
Sílvia Tuyà Viñas ◽  
Josep Maria Padullés Riu ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Short Duration ◽  
Wearable Sensors ◽  
The Other ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Future Studies ◽  
Sprint Running ◽  
Timing System ◽  
Measurement Units

Inertial measurement units (IMUs) represent a technology that is booming in sports right now. The aim of this study was to evaluate the validity of a new application on the use of these wearable sensors, specifically to evaluate a magnet-based timing system (M-BTS) for timing short-duration sports actions using the magnetometer built into an IMU in different sporting contexts. Forty-eight athletes (22.7 ± 3.3 years, 72.2 ± 10.3 kg, 176.9 ± 8.5 cm) and eight skiers (17.4 ± 0.8 years, 176.4 ± 4.9 cm, 67.7 ± 2.0 kg) performed a 60-m linear sprint running test and a ski slalom, respectively. The M-BTS consisted of placing several magnets along the course in both contexts. The magnetometer built into the IMU detected the peak-shaped magnetic field when passing near the magnets at a certain speed. The time between peaks was calculated. The system was validated with photocells. The 95% error intervals for the total times were less than 0.077 s for the running test and 0.050 s for the ski slalom. With the M-BTS, future studies could select and cut the signals belonging to the other sensors that are integrated in the IMU, such as the accelerometer and the gyroscope.

scholarly journals Analysis of ergonomic and unergonomic human lifting behaviors by using Inertial Measurement Units

2017 ◽  
Vol 3 (1) ◽  
pp. 7-10 ◽  
Author(s):  
Jan Kuschan ◽  
Henning Schmidt ◽  
Jörg Krüger
Keyword(s):  
Quality Of Life ◽  
Machine Learning ◽  
Angular Velocity ◽  
Musculoskeletal System ◽  
Occupational Diseases ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Main Components

Abstract:This paper presents an analysis of two distinct human lifting movements regarding acceleration and angular velocity. For the first movement, the ergonomic one, the test persons produced the lifting power by squatting down, bending at the hips and knees only. Whereas performing the unergonomic one they bent forward lifting the box mainly with their backs. The measurements were taken by using a vest equipped with five Inertial Measurement Units (IMU) with 9 Dimensions of Freedom (DOF) each. In the following the IMU data captured for these two movements will be evaluated using statistics and visualized. It will also be discussed with respect to their suitability as features for further machine learning classifications. The reason for observing these movements is that occupational diseases of the musculoskeletal system lead to a reduction of the workers’ quality of life and extra costs for companies. Therefore, a vest, called CareJack, was designed to give the worker a real-time feedback about his ergonomic state while working. The CareJack is an approach to reduce the risk of spinal and back diseases. This paper will also present the idea behind it as well as its main components.

scholarly journals Inertial measurement units to estimate drag forces and power output during standardised wheelchair tennis coast-down and sprint tests

2021 ◽  
pp. 1-19
Author(s):  
Thomas Rietveld ◽  
Barry S. Mason ◽  
Victoria L. Goosey-Tolfrey ◽  
Lucas H. V. van der Woude ◽  
Sonja de Groot ◽  
...  
Keyword(s):  
Power Output ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Drag Forces ◽  
Measurement Units

scholarly journals Measurement of respiratory rate with inertial measurement units

2020 ◽  
Vol 6 (3) ◽  
pp. 237-240
Author(s):  
Simon Beck ◽  
Bernhard Laufer ◽  
Sabine Krueger-Ziolek ◽  
Knut Moeller
Keyword(s):  
Air Pollution ◽  
Respiratory Rate ◽  
Frequency Analysis ◽  
Clinical Settings ◽  
Breathing Rate ◽  
Demographic Changes ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Respiratory Parameters ◽  
Measurement Units

AbstractDemographic changes and increasing air pollution entail that monitoring of respiratory parameters is in the focus of research. In this study, two customary inertial measurement units (IMUs) are used to measure the breathing rate by using quaternions. One IMU was located ventral, and one was located dorsal on the thorax with a belt. The relative angle between the quaternion of each IMU was calculated and compared to the respiratory frequency obtained by a spirometer, which was used as a reference. A frequency analysis of both signals showed that the obtained respiratory rates vary slightly (less than 0.2/min) between the two systems. The introduced belt can analyse the respiratory rate and can be used for surveillance tasks in clinical settings.

scholarly journals Camera and inertial sensor fusion for the PnP problem: algorithms and experimental results

2021 ◽  
Vol 32 (4) ◽  
Author(s):  
Luigi D’Alfonso ◽  
Emanuele Garone ◽  
Pietro Muraca ◽  
Paolo Pugliese
Keyword(s):  
Pose Estimation ◽  
Good Accuracy ◽  
Inertial Sensor ◽  
Experimental Tests ◽  
Inertial Measurement Units ◽  
Magnetic Vector ◽  
Inertial Measurement ◽  
The Earth ◽  
Measurement Units ◽  
Position And Orientation

AbstractIn this work, we face the problem of estimating the relative position and orientation of a camera and an object, when they are both equipped with inertial measurement units (IMUs), and the object exhibits a set of n landmark points with known coordinates (the so-called Pose estimation or PnP Problem). We present two algorithms that, fusing the information provided by the camera and the IMUs, solve the PnP problem with good accuracy. These algorithms only use the measurements given by IMUs’ inclinometers, as the magnetometers usually give inaccurate estimates of the Earth magnetic vector. The effectiveness of the proposed methods is assessed by numerical simulations and experimental tests. The results of the tests are compared with the most recent methods proposed in the literature.

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