Validation of Complementary Filter Based IMU Data Fusion for Tracking Torso Angle and Rifle Orientation

2014 ◽  
Author(s):  
Ryan S. McGinnis ◽  
Stephen M. Cain ◽  
Steven P. Davidson ◽  
Rachel V. Vitali ◽  
Scott G. McLean ◽  
...  
Keyword(s):  
Angular Rate ◽  
Error Sources ◽  
Inertial Measurement ◽  
Complementary Filter ◽  
Measurement Units ◽  
Filtering Technique ◽  
The Subject ◽  
Torso Angle ◽  
Maximal Effort ◽  
Remote Health

Up-down and rifle aiming maneuvers are common tasks employed by soldiers and athletes. The movements underlying these tasks largely determine performance success, which motivates the need for a noninvasive and portable means for movement quantification. We answer this need by exploiting body-worn and rifle-mounted miniature inertial measurement units (IMUs) for measuring torso and rifle motions during up-down and aiming tasks. The IMUs incorporate MEMS accelerometers and angular rate gyros that measure translational acceleration and angular velocity, respectively. Both sensors enable independent estimates of the orientation of the IMU and thus, the orientation of a subject’s torso and rifle. Herein, we establish the accuracy of a complementary filter which fuses these estimates for tracking torso and rifle orientation by comparing IMU-derived and motion capture-derived (MOCAP) torso pitch angles and rifle elevation and azimuthal angles during four up-down and rifle aiming trials for each of 16 subjects (64 trials total). The up-down trials consist of five maximal effort get-down-get-up cycles (from standing to lying prone back to standing), while the rifle aiming trials consist of rapidly aiming five times at two targets 15 feet from the subject and 180 degrees apart. Results reveal that this filtering technique yields warfighter torso pitch angles that remain within 0.55 degrees of MOCAP estimates and rifle elevation and azimuthal angles that remain within 0.44 and 1.26 degrees on average, respectively, for the 64 trials analyzed. We further examine potential remaining error sources and limitations of this filtering approach. These promising results point to the future use of this technology for quantifying motion in naturalistic environments. Their use may be extended to other applications (e.g., sports training and remote health monitoring) where noninvasive, inexpensive, and accurate methods for reliable orientation estimation are similarly desired.

scholarly journals Stride Lengths during Maximal Linear Sprint Acceleration Obtained with Foot-Mounted Inertial Measurement Units

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 376
Author(s):  
Cornelis J. de Ruiter ◽  
Erik Wilmes ◽  
Pepijn S. van Ardenne ◽  
Niels Houtkamp ◽  
Reinder A. Prince ◽  
...  
Keyword(s):  
Stride Length ◽  
Lower Limbs ◽  
Inertial Measurement Units ◽  
Reasonable Accuracy ◽  
Limits Of Agreement ◽  
Inertial Measurement ◽  
Video Cameras ◽  
Recreational Athletes ◽  
Measurement Units ◽  
Maximal Effort

Inertial measurement units (IMUs) fixed to the lower limbs have been reported to provide accurate estimates of stride lengths (SLs) during walking. Due to technical challenges, validation of such estimates in running is generally limited to speeds (well) below 5 m·s−1. However, athletes sprinting at (sub)maximal effort already surpass 5 m·s−1 after a few strides. The present study aimed to develop and validate IMU-derived SLs during maximal linear overground sprints. Recreational athletes (n = 21) completed two sets of three 35 m sprints executed at 60, 80, and 100% of subjective effort, with an IMU on the instep of each shoe. Reference SLs from start to ~30 m were obtained with a series of video cameras. SLs from IMUs were obtained by double integration of horizontal acceleration with a zero-velocity update, corrected for acceleration artefacts at touch-down of the feet. Peak sprint speeds (mean ± SD) reached at the three levels of effort were 7.02 ± 0.80, 7.65 ± 0.77, and 8.42 ± 0.85 m·s−1, respectively. Biases (±Limits of Agreement) of SLs obtained from all participants during sprints at 60, 80, and 100% effort were 0.01% (±6.33%), −0.75% (±6.39%), and −2.51% (±8.54%), respectively. In conclusion, in recreational athletes wearing IMUs tightly fixed to their shoes, stride length can be estimated with reasonable accuracy during maximal linear sprint acceleration.

scholarly journals Human Signature Identification Using IoT Technology and Gait Recognition

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 852
Author(s):  
Mihaela Hnatiuc ◽  
Oana Geman ◽  
Andrei George Avram ◽  
Deepak Gupta ◽  
K. Shankar
Keyword(s):  
Learning Algorithm ◽  
Gait Recognition ◽  
Training Data ◽  
Design System ◽  
Characteristic Parameters ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Subject Identification ◽  
The Subject ◽  
Gait Posture

This study aimed to develop an autonomous design system for recognizing the subject by gait posture. Gait posture is a type of non-verbal communication characteristic of each person, and can be considered a signature used in identification. This system can be used for diagnosis. The system helps aging or disabled subjects to identify incorrect posture to recover the gait. Gait posture gives information for subject identification using leg movements and step distance as characteristic parameters. In the current study, the inertial measurement units (IMUs) located in a mobile phone were used to provide information about the movement of the upper and lower leg parts. A resistive flex sensor (RFS) was used to obtain information about the foot contact with the ground. The data were collected from a target group comprising subjects of different age, height, and mass. A comparative study was undertaken to identify the subject after the gait posture. Statistical analysis and a machine learning algorithm were used for data processing. The errors obtained after training data are presented at the end of the paper and the obtained results are encouraging. This article proposes a method of acquiring data available to anyone by using indispensable devices purchased by all users such as mobile phones.

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.

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