Validation of an IMU Suit for Military-Based Tasks

• Published in: Sensors (Basel, Switzerland) Vol. 20; no. 15; p. 4280
• Main Authors: Mavor, Matthew P., Ross, Gwyneth B., Clouthier, Allison L., Karakolis, Thomas, Graham, Ryan B.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 31-07-2020; MDPI
• Subjects: army; Biomechanics; Coordinates; Correlation analysis; Correlation coefficients; Discriminant analysis; Inertial platforms; inertial sensors; joint kinematics; Kinematics; Load; Markers; Materials handling; Military personnel; Motion capture; PCA; principal component analysis; Principal components analysis; Reconstruction; Root-mean-square errors; Sensors; Validation studies; Walking; Xsens; United Kingdom > UK; Netherlands
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s20154280

Investigating the effects of load carriage on military soldiers using optical motion capture is challenging. However, inertial measurement units (IMUs) provide a promising alternative. Our purpose was to compare optical motion capture with an Xsens IMU system in terms of movement reconstruction using principal component analysis (PCA) using correlation coefficients and joint kinematics using root mean squared error (RMSE). Eighteen civilians performed military-type movements while their motion was recorded using both optical and IMU-based systems. Tasks included walking, running, and transitioning between running, kneeling, and prone positions. PCA was applied to both the optical and virtual IMU markers, and the correlations between the principal component (PC) scores were assessed. Full-body joint angles were calculated and compared using RMSE between optical markers, IMU data, and virtual markers generated from IMU data with and without coordinate system alignment. There was good agreement in movement reconstruction using PCA; the average correlation coefficient was 0.81 ± 0.14. RMSE values between the optical markers and IMU data for flexion-extension were less than 9°, and 15° for the lower and upper limbs, respectively, across all tasks. The underlying biomechanical model and associated coordinate systems appear to influence RMSE values the most. The IMU system appears appropriate for capturing and reconstructing full-body motion variability for military-based movements.