A method for deriving displacement data during cyclical movement using an inertial sensor

Abstract

SUMMARY Biomechanical studies often employ optical motion capture systems for the determination of the position of an object in a room-based coordinate system. This is not ideal for many types of study in locomotion since only a few strides may be collected per `trial', and outdoor experiments are difficult with some systems. Here, we report and evaluate a novel approach that enables the user to determine linear displacements of a proprietary orientation sensor during cyclical movement. This makes experiments outside the constraints of the laboratory possible, for example to measure mechanical energy fluctuations of the centre of mass during over-ground locomotion. Commercial orientation sensors based on inertial sensing are small and lightweight and provide a theoretical framework for determining position from acceleration. In practice,the integration process is difficult to implement because of integration errors, integration constants and the necessity to determine the orientation of the measured accelerations. Here, by working within the constraints of cyclical movements, we report and evaluate a method for determining orientation and relative position using a modified version of a commercial inertial orientation sensor that combines accelerometers, gyroscopes and magnetometers, thus giving a full set of movement parameters (displacement,velocity and acceleration in three dimensions). The 35 g sensor was attached over the spine of a horse exercising on a treadmill. During canter locomotion(9.0 m s-1), the amplitudes of trunk movement in the x(craniocaudal), y (mediolateral) and z (dorsoventral)directions were 99.6, 57.9 and 140.2 mm, respectively. Comparing sensor displacement values with optical motion capture values for individual strides,the sensor had a median error (25th, 75th percentile) in the x, y and z directions of 0.1 (–9.7, +10.8), –3.8(–15.5, +13.7) and –0.1 (–6.3, +7.1) mm, respectively. High-pass filtering of the displacement data effectively separated non-cyclical from cyclical components of the movement and reduced the interquartile ranges of the errors considerably to (–3.6, 6.2),(–4.0, 3.8) and (–4.5, 5.1) for x, y and z displacement, respectively, during canter locomotion. This corresponds to (–3.2, 5.5)%, (–6.7, 6.3)% and (–3.3, 3.7)%of the range of motion.

The three-dimensional locomotor dynamics of African (Loxodonta africana) and Asian (Elephas maximus) elephants reveal a smooth gait transition at moderate speed

“…Hutchinson et al 2006), the motions of the head and forequarters largely move out of phase, which may cancel each other's motions out to some extent. Hence, we are confident that the errors induced by neglecting the head and limb motions in our method will be small (see also van den Bogert et al 1996;Pfau et al 2005Pfau et al , 2006 and should not change the major trends. These assumptions are validated by using multi-segment kinematic data (see electronic supplementary material).…”

“…However, our inertial sensor processing may slightly reduce the CM displacement, as the digital filtering process (see §2) will remove some signals when reducing the noise ( Winter 1990). Yet this is inevitable for all motion analysis methods even the multiple camera system ( Winter 1990;Pfau et al 2005) as the noises, e.g. skin movements, are in a similar frequency band as the useful motion signals.…”

“…It was previously demonstrated that using just one of the inertial sensors, the three-dimensional displacement of a horse's body CM can be captured with accuracy comparable to optical motion capture systems (Qualisys AB, Savedalen, Sweden) during trotting at up to 9.0 m s K1 (Pfau et al 2005). In this study, we use an improved new sensor method to estimate the body CM acceleration, by combining the data from multiple inertial sensors attached at different positions of the animal body, similar to Hayes et al (1983) and van den three-dimensional motion sensor GPS device foot accelerometer foot accelerometer three-dimensional motion sensor Figure 2.…”

“…We developed a novel multiple inertial sensor method, following Pfau et al (2005Pfau et al ( , 2006, incorporating three-dimensional accelerometers and gyroscopes to measure the three-dimensional body CM dynamics and the torso rotations of several elephants (here we use the term 'torso' to refer to the limbless body, rather than 'trunk', which in the case of elephants may confuse readers, or 'body', which we only use to refer to the whole body with all four limbs included). Hundreds of continuous strides were recorded as the elephants moved freely outside in open fields at a range of speeds (0.5-3.5 m s K1 ).…”

Thoracolumbar movement in sound horses trotting in straight lines in hand and on the lunge and the relationship with hind limb symmetry or asymmetry

“…Processing of IMU data followed published methods (Pfau et al, 2005) with 160 custom-written software in MATLAB (The Mathworks). 161…”