Leg soft tissue position and velocity data from skin markers can be obtained with good to acceptable reliability following heel impacts

Abstract

Quantifying soft tissue motion following impact is important in human motion analysis as soft tissues attenuate potentially injurious forces resulting from activities such as running and jumping. This study determined the reliability of leg soft tissue position and velocity following heel impacts. A grid of black dots was applied to the skin of the right leg and foot (n = 20). Dots were automatically detected (ProAnalyst(®)) from high-speed records of pendulum and drop impacts. Three trained measurers selected columns of dots on each participant for analysis; one measurer 6 months later. Between- and within-measurer differences in kinematic variables were all relatively small (<0.8 cm for position; <3.7 cm/s for velocity) between-measurers and (<0.5 cm for position; <2.6 cm/s for velocity) within-measurer. Good (coefficients of variation (CV) ≤ 10%) to acceptable (CV > 10% and ≤20%) reliability was shown for 95% of the position measures, with mean CVs of 10% and 11% within-measurers and between-measures, respectively. Velocity measures were less reliable; 40% of the measures showed good to marginal (CV > 20% and ≤30%) reliability. This study established that leg soft tissue position data from skin markers could be obtained with good to acceptable reliability following heel impacts. Velocity data were less reliable but still acceptable in many cases.

Quantifying Forearm Soft Tissue Motion from Massless Skin Markers following Forward Fall Hand Impacts

“…The marker design (2 x 2 cm grid of 0.5 cm diameter black dots) required no mechanical interaction with the leg, and was applied using flexible plastic stencils and a permanent black marker pen. Overall, Brydges et al (2015) reported good to acceptable reliability for this technique. Nonetheless, modifications to marker shape and contrast might help to further improve its capacity to automatically track soft tissue motion and reduce measurement error (Haddadi & Belhabib, 2008;Crammond, Boyd & Dulieu-Barton, 2013), especially across different skin pigmentations.…”

“…Schematic diagram of the SLU marker design (2 x 2 cm square grid of 0.5 cm diameter circular black dots) on the forearm from (a) posterior and (b) lateral views; schematic diagram of the SNU marker design (2 x 2 cm square grid of ~1 cm diameter circular white dots with ~0.5 cm diameter random black dots overlaid on top) on the forearm demonstrating the contrast for (c) light and (d) dark skin pigmentations. a calibration unit of 6 cm was applied between four adjacent markers (in the same row) that were directly distal to the elbow (Stefanczyk et al, 2013;Brydges et al, 2015); the planar (2D) axes of the coordinate system were aligned in two directions (x-axis: parallel with the long axis of the radius and ulna, running in the proximal-distal direction; y-axis: perpendicular to the long axis of the radius and ulna, running in the anterior-posterior direction of the forearm) ( Figure 4). A single image filter (Convolve: Sharpening (3 x 3 Center)) was applied using the default settings to slightly enhance the overall sharpness of the raw video footage for better contrast and marker edge detection.…”

“…The grid of markers on the forearm was segmented into four zones, similar to Brydges et al (2015) for the leg, wherein two columns of markers (A and B) were selected at 0 %, 25 %, 50 %, and 75 % of the distance from the styloid process of the ulna to the elbow joint ( Figure 4). Each marker location was manually selected by the investigator, ensuring that the rectangular boundary of the defined search region was as close to the marker edge as possible.…”

“…Therefore, the aims of this study were to: 1) quantify planar displacement and velocity of the forearm soft tissues following a forward fall impact, and assess if there were differences between sexes or as a function of forearm region measured; and 2) determine if a stacked, non-uniform (SNU) marker design (non-uniform, ~0.5 cm diameter black dots overlaid on top of a grid of contrasting ~1 cm diameter white dots; 2 cm inter-marker distance) produced significantly different kinematic results and/or improved automated marker tracking across different skin pigmentations compared to the single layer, uniform (SLU) marker design (grid of uniform, 0.5 cm diameter black dots; 2 cm inter-marker distance) previously established by Stefanczyk et al (2013) and Brydges et al (2015).…”

“…One such technique was presented in studies by Stefanczyk et al (2013) and Brydges, Burkhart, Altenhof and Andrews (2015), in which position and velocity data of leg soft tissue motion following pendulum and drop landing heel impacts was quantified using massless skin markers and motion capture software with automatic feature tracking capabilities (ProAnalyst ® ; Xcitex, Cambridge, MA, USA). The marker design (2 x 2 cm grid of 0.5 cm diameter black dots) required no mechanical interaction with the leg, and was applied using flexible plastic stencils and a permanent black marker pen.…”