Orientation Correction for a 3D Hand Motion Tracking Interface Using Inertial Measurement Units

Author(s):  
Nonnarit O-larnnithipong ◽  
Armando Barreto ◽  
Sudarat Tangnimitchok ◽  
Neeranut Ratchatanantakit
Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6858
Author(s):  
Jaime Hislop ◽  
Mats Isaksson ◽  
John McCormick ◽  
Chris Hensman

Inertial Measurement Units (IMUs) are beneficial for motion tracking as, in contrast to most optical motion capture systems, IMU systems do not require a dedicated lab. However, IMUs are affected by electromagnetic noise and may exhibit drift over time; it is therefore common practice to compare their performance to another system of high accuracy before use. The 3-Space IMUs have only been validated in two previous studies with limited testing protocols. This study utilized an IRB 2600 industrial robot to evaluate the performance of the IMUs for the three sensor fusion methods provided in the 3-Space software. Testing consisted of programmed motion sequences including 360° rotations and linear translations of 800 mm in opposite directions for each axis at three different velocities, as well as static trials. The magnetometer was disabled to assess the accuracy of the IMUs in an environment containing electromagnetic noise. The Root-Mean-Square Error (RMSE) of the sensor orientation ranged between 0.2° and 12.5° across trials; average drift was 0.4°. The performance of the three filters was determined to be comparable. This study demonstrates that the 3-Space sensors may be utilized in an environment containing metal or electromagnetic noise with a RMSE below 10° in most cases.


2017 ◽  
Vol 3 (1) ◽  
pp. 7-10 ◽  
Author(s):  
Jan Kuschan ◽  
Henning Schmidt ◽  
Jörg Krüger

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.


2021 ◽  
pp. 1-19
Author(s):  
Thomas Rietveld ◽  
Barry S. Mason ◽  
Victoria L. Goosey-Tolfrey ◽  
Lucas H. V. van der Woude ◽  
Sonja de Groot ◽  
...  

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