Short CommunicationIMU: Inertial sensing of vertical CoM movement
Introduction
Optical motion capture systems (OCMS) are used for kinematic analyses of an object in a three-dimensional calibrated volume and seen as the gold standard (Wong et al., 2007). These systems are relatively expensive, time consuming and not easily applicable outside laboratory conditions (Mayagoitia et al., 2002). Accelerometers offer an alternative way to obtain kinematic data in a variety of environments (Refshauge et al., 1995; Schneck, 2000). However certain methodological problems need to be addressed (Kavanagh and Menz, 2008). During circular movements, such as in human gait, the 3D axes rotate.
Commercially available systems combining accelerometers, gyroscopes and magnetometers into an algorithm, known as inertial measurement units (IMU), can transpose translatory acceleration from the object system to the global system using a rotation matrix (Luinge, 2002; Roetenberg, 2006).
Conventional rotation matrices use Euler angle matrices to perform their rotations, but show singularities when using certain sequences of rotations (Pfau et al., 2006).
Quaternions are geometrical operators which represent rotations by using complex numbers forming an algebra (Gravelle, 2006).
This study investigated a lower spine point estimate of centre of mass (CoM), as a simple reference that indicates global gait quality (Meichtry et al., 2007). IMU over the lower spine has an increased risk of showing singularities using Euler angles, therefore quaternions have been chosen as rotation matrix operators (Moe-Nilssen and Helbostad, 2004). Quaternions allow fast computation and simple expressions to be developed for complex rotations and rotating reference frames (Spring, 1986; Hanson, 2006).
This study will investigate the application of an IMU and quaternion-based rotation matrix compared to an OMCS to measure the estimated CoM translatory acceleration during human walking. It also examines double integration of translatory acceleration to obtain relative change in position.
Section snippets
Materials and methods
Five subjects (age: 23.4±3.8 years, weight: 80.5±14.3 kg and height: 181±5.4 cm) participated. The IMU (MTx, Xsens, Netherlands) was fixed with adhesive tape, in an angle of ±90° (due to sensor design), over the fourth lumbar vertebra. A reflective marker was placed on the middle of the IMU to measure the displacement with the OMCS (Proflex, Qualisys, Sweden). Both systems were synchronized and measured at 100 Hz.
Baseline gravitational measurements were recorded before the subjects walked three
Results
Table 1 shows the average difference and standard deviation over three walks for five healthy subjects in the z-axis. Error between both systems of a random participant is plotted in Fig. 1
The data between IMU and OMCS acceleration shows good agreement. Z-axis amplitudes from IMU and OMCS were not significantly different (p⩾0.05). In addition ICC=0.952 and random error 0.176 ms−2 demonstrated strong agreement between systems.
A paired sample t-test between the relative change in speed (peak to
Discussion
We found that the mathematical transformation using quaternions in combination with double integration applied to IMU data resulted in accurate speed and relative position in the global z-axis during SSWS for short measurements. To the authors knowledge this technique provides more accurate CoM displacement data than previously obtained using Euler angles and step-by-step analysis method described in previous publications (Pfau et al., 2005, Pfau et al., 2006). For this method, the IMU used in
Conflict of interest
None.
Acknowledgement
The authors wish to acknowledge the UK Department of Health for providing funding through the LIFE program.
References (28)
- et al.
Soft tissue artefact assessment in humeral axial rotation
Gait Posture
(2005) - et al.
Technical note: comparison of the performance of 3D camera systems II
Gait Posture
(1997) - et al.
Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems
J. Biomech.
(2002) - et al.
Criterion validity of 3D trunk accelerations to assess external work and power in able-bodied gait
Gait Posture
(2007) - et al.
Estimation of gait cycle characteristics by trunk accelerometry
J. Biomech.
(2004) Euler parameter and the use of quaternion Algebra in the manipulation of finite rotations: a review
Mech. Mach. Theory
(1986)LabVIEW 8 Student Edition
(2007)- et al.
The static accuracy and calibration of intertial measurement unit for 3D orientation
Comput Methods Biomech. Biomed. Eng.
(2008) - et al.
Dynamic accuracy of inertial measurement units during simple pendulum motion
Comput. Methods Biomech. Biomed. Eng.
(2008) - et al.
The role of gravity in human walking: pendular energy exchange, external work and optimal speed
J. Physiol.
(2000)
Technical note: comparison of the performance of 3D camera systems
Gait Posture
The Global Positioning System and Intertial Navigation
Visualizing Quaternions
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