Consistency of vertebral motion and individual characteristics in gait sequences.

Vertebral motion reveals complex patterns, which are not yet understood in detail. This applies to vertebral kinematics in general but also to specific motion tasks like gait. For gait analysis, most of existing publications focus on averaging characteristics of recorded motion signals. Instead, this paper aims at analyzing intra- and inter-individual variation specifically and elaborating motion parameters, which are consistent during gait cycles of particular persons. For this purpose, a study design was utilized, which collected motion data from 11 asymptomatic test persons walking at different speed levels (2, 3, and 4 km/h). Acquisition of data was performed using surface topography. The motion signals were preprocessed in order to separate average vertebral orientations (neutral profiles) from basic gait cycles. Subsequently, a k-means clustering technique was applied to figure out, whether a discrimination of test persons was possible based on the preprocessed motion signals. The paper shows that each test sequence could be assigned to the particular test person without additional prior information. In particular, the neutral profiles appeared to be highly consistent intra-individually (across the gait cycles as well as speed levels), but substantially different between test persons. A full discrimination of test persons was achieved using the neutral profiles with respect to flexion/extension data. Based on this, these signals can be considered as individual characteristics for the particular test persons.

Comprehensive visualization of spinal motion in gait sequences based on surface topography.

Analysis of spinal motion is considered to be important to assess function of the human spine. Surface topography (ST) is a method to record the vertebral orientation in 3D. Such measurements can be performed in static but also in dynamic situations like gait or other motion tasks. However, dynamic ST measurements are hard to interpret due to their complexity. The main goal of this paper is to provide comprehensive visualization tools which allow a more intuitive and comprehensive interpretation n of such measurements. In particular, juxtaposition and superimposition techniques are utilized to emphasize differences in motion characteristics. The method was applied to a test series of 12 healthy volunteers walking on a treadmill at various speed levels. It could be shown that the visualization tools are helpful to compare different motion sequences including an analysis of intra- and interindividual variation. Based on these techniques, it could be shown that the profiles of vertebral orientation remain considerable constant when one person was walking at different speed levels whereas they differed substantially between the different individuals. In contrast, the motion amplitudes contained high intra- and interindividual variation, i.e. between speed levels and different test persons. In summary, the paper demonstrates that appropriate visualization tools are helpful to interpret ST measurements and cope with the complexity of these data sets. In particular, they can be used to compare different motion sequences in a more comprehensive way.