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

Dynamic Surface Topography for Thoracic and Lumbar Pain Patients-Applicability and First Results

Current routine diagnostic procedures for back pain mainly focus on static spinal analyses. Dynamic Surface Topography (DST) is an easy-to-use, radiation-free addition, allowing spine analyses under dynamic conditions. Until now, it is unclear if this method is applicable to back pain patients, and data reports are missing. Within a prospective observational study, 32 patients suffering from thoracic and lumbar back pain were examined while walking, randomized at four speeds (2, 3, 4, 5 km/h), using a DST measuring device (DIERS 4Dmotion® Lab). The measurement results were compared with those of a healthy reference group. We calculated the intrasegmental rotation for every subject and summed up the spinal motion in a standardized gait cycle. The Mann-Whitney U Test was used to compare the painful and healthy reference groups at the four different speeds. In a subgroup analysis, the painful group was divided into two groups: one with less pain (≤3 points on the Visual Analogue Scale) and one with more pain (>3 points on the Visual Analogue Scale). The Kruskal-Wallis Test was used to compare these subgroups with the healthy reference group. Of the 32 included patients, not all could walk at the intended speeds (5 km/h: 28/32). At speeds of 2-4 km/h, our results point to greater total segmental rotation of back pain patients compared to the healthy reference group. At a speed of 3 km/h, we observed more movement in the patients with more pain. Overall, we monitored small differences on average between the groups but large standard deviations. We conclude that the DST measuring approach is eligible for back pain patients when they feel confident enough to walk on a treadmill. Initial results suggest that DST can be used to obtain interesting therapeutic information for an individual patient.

Initial study on an expert system for spine diseases screening using inertial measurement unit

In recent times, widely understood spine diseases have advanced to one of the most urgetn problems where quick diagnosis and treatment are needed. To diagnose its specifics (e.g. to decide whether this is a scoliosis or sagittal imbalance) and assess its extend, various kind of imaging diagnostic methods (such as X-Ray, CT, MRI scan or ST) are used. However, despite their common use, some may be regarded as (to a level) invasive methods and there are cases where there are contraindications to using them. Besides, which is even more of a problem, these are very expensive methods and whilst their use for pure diagnostic purposes is absolutely valid, then due to their cost, they cannot rather be considered as tools which would be equally valid for bad posture screening programs purposes. This paper provides an initial evaluation of the alternative approach to the spine diseases diagnostic/screening using inertial measurement unit and we propose policy-based computing as the core for the inference systems. Although the methodology presented herein is potentially applicable to a variety of spine diseases, in the nearest future we will focus specifically on sagittal imbalance detection.

Dynamic surface topography data for assessing intra- and interindividual variation of vertebral motion

Spinal function is substantially related to the motion of the particular vertebrae and the spine as a whole. For systematic assessment of individual motion, data sets are required which cover the kinematics comprehensively. Additionally, the data should enable a comparison of inter- and intraindividual variation of vertebral orientation in dedicated motion tasks like gait. For this purpose, this article provides surface topography (ST) data which were acquired while the individual test persons were walking on a treadmill at three different speed levels (2 km/h, 3 km/h, 4 km/h). In each recording, ten full walking cycles were included per test case to enable a detailed analysis of motion patterns. The provided data reflects asymptomatic and pain-free volunteers. Each data set contains the vertebral orientation in all three motion directions for the vertebra prominens down to L4 as well as the pelvis. Additionally, spinal parameters like balance, slope, and lordosis / kyphosis parameters as well as an assignment of the motion data to single gait cycles are included. The complete raw data set without any preprocessing is provided. This allows to apply a broad range of further signal processing and evaluation steps in order to identify characteristic motion patterns as well as intra- and inter-individual variation of vertebral motion.

Reference values and functional descriptions of transverse plane spinal dynamics during gait based on surface topography

Spinal dynamics during gait have been of interest in research for many decades. Based on respective previous investigations, the pelvis is generally expected to be maximally forward rotated on the side of the reference leg at the beginning of each gait cycle and to reach its maximum counterrotation approximately at the end of the reference leg's stance phase. The pelvic-upper-thoracic-spine coordination converges towards an anti-phase movement pattern in high velocities during ambulation. The vertebral bodies around the seventh thoracic vertebra are considered to be an area of transition during human ambulation where no or at least little rotary motion can be observed. The respective cranial and caudal vertebrae meanwhile are expected to rotate conversely around this spinal point of intersection. However, these previous assumptions are based on scarce existing research, whereby only isolated vertebrae have been analyzed contemporaneously. Due to huge methodological differences in data capturing approaches, the results are additionally hardly comparable to each other and involved measurement procedures are often not implementable in clinical routines. Furthermore, none of the above-mentioned methods provided reference data for spinal motion during gait based on an appropriate number of healthy participants. Hence, the aim of this study was to present such reference data for spinal rotary motion of every vertebral body from C7 down to L4 and the pelvis derived from surface topographic back shape analyses in a cohort of 201 healthy participants walking on a treadmill at a given walking speed of 5 km/h. Additionally, the spine's functional movement behavior during gait should be described in the transverse plane based on data derived from this noninvasive, clinically suitable measurement approach and, in conclusion, the results shall be compared against those of previous research findings derived from other measurement techniques. Contrary to the previous functional understanding, the area of the mid-thoracic spine was found to demonstrate the largest amplitude of rotary motion of all investigated vertebrae and revealed an approximately counterrotated movement behavior compared to the rotary motion of the pelvis. In both directions, spinal rotation during gait seemed to be initiated by the pelvis. The overlying vertebrae followed in succession in the sense of an ongoing movement. Therefore, the point of intersection was not statically located in a specific anatomical section of the spine. Instead, it was found to be dynamic, ascending from one vertebra to the next from caudal to cranial in dependence of the pelvis's rotation initiation.

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.