Literature DB >> 24344898

Driving a musculoskeletal model with inertial and magnetic measurement units.

Bart H W Koning1, Marjolein M van der Krogt, Chris T M Baten, Bart F J M Koopman.   

Abstract

We developed and evaluated a new kinematic driver for musculoskeletal models using ambulatory inertial and magnetic measurement units (IMMUs). The new driver uses the orientation estimates based on sensor fusion of each individual IMMU and benefits from two important properties of musculoskeletal models. First, these models contain more complex, anatomical, kinematic models than those currently used for sensor fusion of multiple IMMUs and are continuously improved. Second, they allow movement between segment and measured sensor. For three different tasks, the new IMMU driver, (optical) marker drivers and a combination of both were used to reconstruct the motion. Maximal root mean square (RMS) joint angle differences with respect to the silver standard (combined IMMU/marker drivers) were found for the hip joint; 4°, 2° and 5° during squat, gait and slideboard tasks for IMMU-driven reconstructions, compared with 6°, 5° and 5° for marker-driven reconstructions, respectively. The measured angular velocities corresponded best to the IMMU-driven reconstructions, with a maximal RMS difference of 66°/s, compared with 108°/s and 91°/s for marker-driven reconstructions and silver standard. However, large oscillations in global accelerations occurred during IMMU-driven reconstructions resulting in a maximal RMS difference with respect to measured acceleration of 23 m/s2, compared with 9 m/s2 for reconstructions that included marker drivers. The new driver facilitates direct implementation of IMMU-based orientation estimates in currently available biomechanical models. As such, it can help in the rapid expansion of biomechanical analysis based on outdoor measurements.

Keywords:  global optimisation; inertial and magnetic measurement units; joint constraints; kinematic driver; musculoskeletal models

Year:  2013        PMID: 24344898     DOI: 10.1080/10255842.2013.867481

Source DB:  PubMed          Journal:  Comput Methods Biomech Biomed Engin        ISSN: 1025-5842            Impact factor:   1.763


  2 in total

1.  Estimating Lower Extremity Running Gait Kinematics with a Single Accelerometer: A Deep Learning Approach.

Authors:  Mohsen Gholami; Christopher Napier; Carlo Menon
Journal:  Sensors (Basel)       Date:  2020-05-22       Impact factor: 3.576

2.  Upper Limb Kinematics Using Inertial and Magnetic Sensors: Comparison of Sensor-to-Segment Calibrations.

Authors:  Brice Bouvier; Sonia Duprey; Laurent Claudon; Raphaël Dumas; Adriana Savescu
Journal:  Sensors (Basel)       Date:  2015-07-31       Impact factor: 3.576

  2 in total

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