Fig 1.
Participant outfitted with equipment (unloaded condition).
(a) Participant wearing an array of IMUs (red rectangles) attached to major body segments and in the approximate locations shown (sacrum IMU on posterior). (b) Participant with the mock rifle slung over the shoulder with additional IMU nodes attached to the mock rifle and embedded in the ammo can. (c) Image of single IMU node with integrated Velcro strap.
Fig 2.
Outdoor obstacle course layout.
Plan view of ten obstacles for a modified LEAP obstacle course [30–31].
Table 1.
Minimum, mean, maximum, and standard deviation (STD) of additional loads (in kg) secured to the participants.
Table 2.
Relative magnitudes for the effect sizes for the ANOVA () and Tukey (d) analyses [40].
Fig 3.
Boxplots depicting the results from the Tukey post hoc analysis for a) sprint time, b) maximum speed, and c) maximum acceleration. The bars denote significant differences between loading conditions at a significance level α = 0.05*, 0.01**, 0.001***.
Fig 4.
Vertical jump statistical results.
Boxplots depicting the results from the Tukey post hoc analysis of vertical jump metrics for a) jump countermovement velocity, b) jump countermovement depth, c) jump propulsion phase acceleration, and d) jump takeoff velocity. The bars denote significant differences between loading conditions at a significance level α = 0.05*, 0.01**, 0.001***.
Fig 5.
a) The layout for the casualty drag obstacle defined by two cones separated by 10m. Participants drag a heavy load (bag) in a loop around the cones as shown by the dashed lines. Blue and red sections of the path indicate turn and straightaway phases, respectively. b) A photo illustrating a participant dragging the load near the start.
Fig 6.
Casualty drag statistical results.
Boxplots depicting the results from the Tukey post hoc analysis for a) average body speed, b) average turn body speed, c) average straightaway body speed, and d) obstacle time.
Fig 7.
Drift-corrected vertical velocity of the sacrum IMU for a sample trial.
Maximum vertical velocity (black star) corresponds to the participant jumping up onto the window. Minimum vertical velocity (gray square) corresponds to the participant jumping down off of the window. Time through the window is the interval between these points.
Fig 8.
Boxplots depicting the results from the Tukey post hoc analysis of window obstacle metrics for a) time to pass through the window opening, b) horizontal approach velocity, and c) vertical takeoff velocity. The bars denote significant differences between loading conditions at a significance level α = 0.05*, 0.01**, 0.001***.
Fig 9.
The layout for the balance beam obstacle in both (a) a top-down view and (b) a side view (b). (c) A photo of a participant completing the obstacle. The balance beam obstacle is composed of five elevated aluminum planks (0.15 m wide, 3.05 m long). The first plank is level, whereas the other planks alternately slope up or down by 9 degrees. The junction between the first and second planks is straight, whereas the other junctions are alternating right and left 90 degree turns. Four boxes (0.20 X 0.20 X 0.76 m) are placed on the beam to create an additional challenge for participants. The boxes are placed 1.04 m, 1.02 m, 0.71 m, and 0.30 m from the leading edge of the second, third, fourth and fifth planks, respectively.
Fig 10.
Balance beam statistical results.
Boxplots depicting the results from the Tukey post hoc analysis of balance beam metrics for a) time to traverse the beam, b) average box step over time, c) standard deviation of step time, and d) ratio of root-mean squared (RMS) medial-lateral (M-L) acceleration to anterior-posterior (A-P) acceleration. The bars denote significant differences between loading conditions at a significance level α = 0.05*, 0.01**, 0.001***.
Fig 11.
Boxplots depicting the results from the Tukey post hoc analysis of wall obstacle metrics for a) horizontal approach velocity, b) vertical takeoff velocity, c) vertical takeoff power and d) vertical landing velocity. The bars denote significant differences between loading conditions at a significance level α = 0.05*, 0.01**, 0.001***.
Fig 12.
a) The layout for the agility run obstacle and an example of a participant performing the task. The photo (b) illustrates a subject cutting around the outside of a cone.
Fig 13.
Agility run statistical results.
Boxplots depicting the results from the Tukey post hoc analysis for a) acceleration range, b) (inverse) obstacle time, c) average maximum straightaway speed, and d) average body speed. The bars denote significant differences between loading conditions at a significance level α = 0.05*, 0.01**, 0.001***.
Fig 14.
a) The layout for the bounding rush obstacle and an example of a participant aiming and then executing a single bounding rush (b)-(f). The photos illustrate the aiming phases (b) and (f) that bookend each bounding rush that consists of: c) standing quickly, d) sprinting to the next cone, and e) dropping quickly to prone.
Fig 15.
Bounding rush statistical results.
Boxplots depicting the results from the Tukey post hoc analysis for a) rushing speed, b) standing speed, c) running speed, and d) dropping speed. The bars denote significant differences between loading conditions at a significance level α = 0.05*, 0.01**, 0.001***.
Fig 16.
(a) Layout of the high crawl obstacle, and (b) photograph of a participant completing the high crawl.
Fig 17.
High crawl statistical results.
Boxplots depicting the results from the Tukey post hoc analysis for a) crawl speed, b) crawl stride time, c) ipsilateral coordination, and d) contralateral coordination. The bars denote significant differences between loading conditions at a significance level α = 0.05*, 0.01**, 0.001***.
Fig 18.
Summary ANOVA and Tukey post hoc results for all performance metrics across all obstacles.
The circles under ANOVA indicate metrics exhibiting statistically significant relationships with load. Triangles under the three load comparisons (UL →15BW, UL →30BW, and 15BW →30BW) indicate statistically significant differences between load pairs (Tukey post hoc analysis). The direction of the triangle (up or down) indicates the direction of the change (increase or decrease) in the performance metric (from the first listed loading condition to the second listed loading condition). The gray scale for both symbols (circles and triangles) indicate the effect size defined in Table 2 (white = small effect size, gray = medium effect size, black = large effect size).