The validity of spatiotemporal gait analysis using dual laser range sensors: a cross-sectional study

Abstract

Background The spatiotemporal parameters were used for sophisticated gait analysis in widespread clinical use. Recently, a laser range sensor has been proposed as a new device for the spatiotemporal gait measurement. However, measurement using a single laser range sensor can only be used for short-range gait measurements because the device irradiates participants with lasers in a radial manner. For long-range gait measurement, the present study uses a modified method using dual laser range sensors installed at opposite ends of the walking path. The aim of present study was to investigate the concurrent validity of the proposed method for spatiotemporal gait measurement by comparison to a computer-based instrumented walkway system. Methods Ten healthy participants were enrolled in this study. Ten-meter walking tests at 100, 75, and 50% of the comfortable speed were conducted to determine the concurrent validity of the proposed method compared to instrumented walkway measurements. Frequency distributions of errors for foot-contact (FC) and foot-off (FO) estimated times between the two systems were also calculated to determine the adequacy of estimation of FC and FO from three perspectives: accuracy (smallness of mean error), precision (smallness of variability), and unambiguity (monomodality of histogram). Intra-class correlation coefficient (2,1) was used to determine the concurrent validity of spatiotemporal parameters between the two systems. Result The results indicate that the detection times for FC and FO estimated by the proposed method did not differ from those measured by the instrumented walkway reference system. In addition, histogram for FC and FO showed monomodality. Intra-class correlation coefficients of the spatiotemporal parameters (stance time: 0.74; double support time: 0.56; stride time: 0.89; stride length: 0.83; step length: 0.71; swing time: 0.23) were not high enough. The mean errors of all spatiotemporal parameters were small. Conclusions These results suggest that the proposed lacks sufficient concurrent validity for spatiotemporal gait measurement. Further improvement of this proposed system seems necessary. Trial registration UMIN000032710 . Registered 24 May 2018. Retrospectively registered.

Spatiotemporal Gait Measurement With a Side-View Depth Sensor Using Human Joint Proposals

“…Participants in [16] completed walking trials at 100, 75, and 50 percent of comfortable speed. However, they only reported results with all walking types grouped together, so we compare our normal walking and dual-task results to their grouped results.…”

“…Recently, Zago et al [15] measured spatiotemporal parameters without markers using two RGB cameras for stereoscopic vision. Iwai et al [16] used 2D laser range sensors placed at shin height to estimate where the foot contacts the ground, but required subjects to walk barefoot with shins exposed (e.g., wearing shorts). Castelli et al [17] used a single RGB camera to measure spatiotemporal parameters without conventional markers, but this still required subjects to wear white undergarments to mark the pelvis and foot segments, and the subjects had to walk in front of a homogeneous blue background.…”

Evaluation of balance functions using temporo-spatial gait analysis parameters in patients with brain lesions

“…A computer-based instrumented gait analysis system (Walkway MG-1000, Anima, Japan) was used as the gait analysis system herein 24 . This gait analysis system can measure the spatiotemporal parameters of gait from on/off signals between the patients’ foot and the surface of the sensors at a sampling frequency of 100 Hz.…”

“…This gait analysis system can measure the spatiotemporal parameters of gait from on/off signals between the patients’ foot and the surface of the sensors at a sampling frequency of 100 Hz. The width and length of the walkway system are 0.82 m and 4.8 m, respectively 24 . In the walkway system, data were obtained and processed using the software embedded in the system.…”

Assessing the Mobility of Elderly People in Domestic Smart Home Environments

“…Motion sensors can, for example, are mounted on the ceiling of a frequently used passageway and determine the walking speed of a person [28]. Further approaches analyse the transition times between the coverage areas of different sensors [29][30][31] Other sensor-based approaches detect the movements of lower limbs by means of radar [32,33], laser scanner [34,35] or ultrasonic sensors [36,37].…”