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Soldier-relevant body borne loads increase knee joint contact force during a run-to-stop maneuver
Author’s Accepted Manuscript Soldier-relevant body borne loads increase knee joint contact force during a run-to-stop maneuver John W. Ramsay, Clifford L. Hancock, Meghan P. O’Donovan, Tyler N. Brown, John W Ramsay www.elsevier.com/locate/jbiomech
PII: DOI: Reference:
S0021-9290(16)31120-4 http://dx.doi.org/10.1016/j.jbiomech.2016.10.022 BM7932
To appear in: Journal of Biomechanics Accepted date: 16 October 2016 Cite this article as: John W. Ramsay, Clifford L. Hancock, Meghan P. O’Donovan, Tyler N. Brown and John W Ramsay, Soldier-relevant body borne loads increase knee joint contact force during a run-to-stop maneuver, Journal of Biomechanics, http://dx.doi.org/10.1016/j.jbiomech.2016.10.022 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Run-to-Stop Knee Contact Forces Title of this Original Article: Soldier-relevant body borne loads increase knee joint contact force during a run-to-stop maneuver
Authors and Affiliations: Author 1: John W. Ramsay Natick Soldier Research, Development, and Engineering Center, Natick, MA 01760 Author 2; Clifford L. Hancock Natick Soldier Research, Development, and Engineering Center, Natick, MA 01760 Author 3: Meghan P. O’Donovan Natick Soldier Research, Development, and Engineering Center, Natick, MA 01760 Author 4: Tyler N. Brown Boise State University, Boise, ID, 83725 Oak Ridge Institute for Science and Education (ORISE), Belcamp, MD, USA Contact Information: John W, Ramsay, PhD U.S. Army Natick Soldier Research, Development, and Engineering Center 15 General Greene Avenue Natick, MA 01760 Email: [email protected] Fax: 508-233-6472 Phone: 508-233-4496 Keywords: load carriage, knee contact force, run to stop, OpenSim, leg stiffness Abstract: The purpose of this study was to understand the effects of load carriage on human performance, specifically during a run-to-stop (RTS) task. Using OpenSim analysis tools, knee joint contact force, grounds reaction force, leg stiffness and lower extremity joint angles and moments were determined for nine male military personnel performing a RTS under three load configurations (light, ~6 kg, medium, ~20 kg, and heavy, ~40 kg). Subject-based means for each Page 1
Run-to-Stop Knee Contact Forces biomechanical variable were submitted to repeated measures ANOVA to test the effects of load. During the RTS, body borne load significantly increased peak knee joint contact force by 1.2 BW (p<0.001) and peak vertical (p<0.001) and anterior-posterior (p=0.002) ground reaction forces by 0.6 BW and 0.3 BW, respectively. Body borne load also had a significant effect on hip (p=0.026) posture with the medium load and knee (p=0.046) posture with the heavy load. With the heavy load, participants exhibited a substantial, albeit non-significant increase in leg stiffness (p = 0.073 and d=0.615). Increases in joint contact force exhibited during the RTS were primarily due to greater GRFs that impact the soldier with each incremental addition of body borne load. The stiff leg, extended knee and large braking force the soldiers exhibited with the heavy load suggests their injury risk may be greatest with that specific load configuration. Further work is needed to determine if the biomechanical profile exhibited with the heavy load configuration translates to unsafe shear forces at the knee joint and consequently, a higher likelihood of injury. Introduction: A major concern for military populations is musculoskeletal injury (Kaufman et al., 2000). Musculoskeletal injuries cost the armed forces hundreds of millions of dollars in lost productivity and treatment each year (Ruscio et al., 2010). These injuries often result during military training-related activities (Jones et al., 2010; Hauret et al., 2010), when soldiers don heavy body borne loads (e.g. body armor, weapon systems, rucksacks) in excess of 45 kg (Task Force Devil Combined Arms Assessment Team, 2003). The resulting musculoskeletal injuries not only have an immediate and detrimental impact on soldiers’ health, but often result in reinjury (Hauret et al., 2001) that can end in long-term disability and subsequent discharge from the military (Gilchrist et al., 2000).
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Run-to-Stop Knee Contact Forces More than three quarters of musculoskeletal injuries sustained during military training occur in the lower extremity (Almeida et al., 1999). These injuries, including sprain, strain or rupture of a joint’s soft tissue, primarily occur at the knee (Hauret et al., 2010; Kaufman et al., 2000; Shaffer et al. 1999). These injuries often result during landing and pivoting maneuvers that require a quick change of speed and/or direction (Olsen et al., 2004), which are customary during military training (Johnson, 2003). One maneuver of particular interest is a run-to-stop (RTS), which occurs operationally when the soldier quickly avoids or reacts to enemy fire. To successfully perform a RTS, the soldier must rapidly and completely decelerate the body centerof-mass (CoM) by controlling the segment inertias as they pass down the lower extremity (McNitt-Gray, 1991). To prevent lower limb collapse during the RTS, the soldier may adopt a biomechanical profile that gives rise to unsafe joint loads, particularly at the knee, increasing risk of musculoskeletal injury. Donning body borne load may further elevate musculoskeletal injury risk during the RTS by altering the soldier’s lower limb biomechanical profile (Patton et al., 1991). While running, cutting, and landing with body borne load, the soldier exhibits larger joint moments and significant adaptations of the stance leg sagittal plane motions (Brown et al., 2014a; Brown et al., 2014b; Silder et al., 2015). These biomechanical adaptations may prevent stance leg collapse and aid with dissipating the increased ground reaction forces (GRF) evident with body borne load (Kinoshita et al., 1985; Silder et al., 2015; Silder et al., 2013). Adding body borne load reportedly increases both peak magnitude (Birrell et al., 2007; Harman et al., 2000; Polcyn et al., 2002; Wang et al., 2012) and transmission rate of the vertical GRF (Wang et al., 2012). The elevated GRF may result in larger knee joint compressive forces, which possibly increase risk of soft tissue damage and long term joint deterioration. While changes in GRFs have been well
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Run-to-Stop Knee Contact Forces documented during steady-state movements such as walking and running with body borne load, little is known about how they change during a sudden deceleration task with a body borne load. To safely prevent lower limb collapse during the RTS, the soldier may alter their stance leg stiffness
. Leg stiffness, i.e. resistance of the leg to deformation, is necessary to safely
perform dynamic maneuvers (McMahon and Cheng, 1990). As the demands of physical activity increase, such as by adding body borne load,
typically increases (Arampatzis et al., 1999;
Farley and González, 1996; Granata et al., 2002). While adequate
is necessary to
successfully complete maneuvers such as the RTS, exposure to atypical stiffness may increase musculoskeletal injury risk by requiring more rapid transmission of large forces through the lower limb (Burr et al., 1985; Grimston et al., 1991; Hennig and Lafortune, 1991; Radin et al., 1978). Leg stiffness reportedly increases with body borne load during walking (Caron et al., 2015) and running Silder et al. (2015), but it is unknown if
increases with the addition of
load during a dynamic military-relevant RTS task. Knee joint contact loads (i.e. tibiofemoral compressive forces) vary between 2-3 times body weight during normal daily activities such as walking (D'Lima et al., 2006; Kutzner et al., 2010; Mundermann et al., 2008), and may reach 15 times body weight during unloaded running (Edwards et al., 2008). During a RTS, the sudden deceleration may cause large tibiofemoral compressive forces, particularly with body borne loads in excess of 45 kg. Knarr et al. (2016) found knee joint contact force (JCF) increases with each incremental addition of body borne load. Therefore, it is of interest to quantify the changes in JCF due to the addition of body borne load, especially during quick deceleration tasks common during military training. These elevated loads can lead to joint pain, injury and cartilage degeneration (Eckstein et al., 2002) that results in long-term disability of the joint (Andriacchi, 2004).
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Run-to-Stop Knee Contact Forces The current purpose was to investigate changes in lower limb (i.e., hip, knee and ankle) biomechanics and JCF with the addition of body borne load during a RTS maneuver. While typical motion capture techniques allow for the quantification of lower limb mechanics, noninvasive measurement of internal joint compressive forces can be difficult to obtain in vivo. Recent developments in musculoskeletal modeling and simulation, however, have enabled the prediction of internal joint forces experienced during a dynamic task (Demers et al., 2014; Knarr and Higginson, 2015). In this study, musculoskeletal models simulated the effect that external body borne load has on JCF. We hypothesized that during the RTS, hip, knee and ankle flexion angles and moments, vertical GRF,
, impulse and knee JCF would increase as body borne
load increases. Methods: Subjects: Nine male military personnel (21.1 ± 3.8 yrs, 72.5 ± 9.4 kg, 1.8 ± 0.1 m) participated in this study. Each participant self-reported the ability to safely carry body borne loads heavier than 40 kg. Participants were excluded from the study if they reported current pain or recent injury to the back or lower extremity (within six months), had a history of back or lower extremity injury or surgery, and/or any known neurological disorders. All subjects provided written consent, approved by the local (United States Army Research Institute of Environmental Medicine) institutional review board, prior to testing. Experimental Protocol: Three test sessions were completed by each participant. During each test session, participants donned a different body borne load configuration (light, medium, or heavy) (Figure 1). The light load (~6 kg; Figure 1A) was composed of a helmet, mock weapon, combat boots,
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Run-to-Stop Knee Contact Forces socks and spandex shirt and shorts. The medium load (~20 kg; Figure 1B) required the participant don body armor with a fabric ammo panel attached on the anterior, in addition to the light load. The heavy load (~40 kg; Figure 1C) required the participant don a standard issue military backpack, in addition to the medium load. To randomize the testing order for each participant, the testing sequence of each load configuration was predetermined by a 3x3 Latin Square scheme. During each test session, the participant performed three successful RTS maneuvers. The RTS required the participant to run down a 10 m walkway at 3.5 m/s (7.8 mph) and plant their dominant limb on a force platform embedded in the floor, immediately stopping in a low ready position (i.e. eyes forward, weapon pointed downward at ~45°, legs wide and slightly bent). The dominant limb was defined as the leg each participant self-reported they could kick a ball the farthest. The running speed was set at 3.5 m/s to remain consistent with our previous load carriage work (Brown et al., 2014a & 2014b). Additionally, to minimize fatigue during data collection, all subjects were given ample time to rest between trials and were provided water to maintain adequate hydration. During each RTS, three-dimensional joint (i.e. hip, knee, and ankle) kinetic and kinematic data were recorded. A force platform (AMTI Optima, Advanced Mechanical Technology Inc., Watertown, MA, USA) captured GRF data at 1200 Hz, while twelve highspeed (240 fps) cameras (Oqus, Qualisys AB, Gothenburg, Sweden) captured synchronous motion capture data. Running speed was monitored by two sets of timing gates (Brower Timing, Draper, UT, USA). A trial was successful if the dominant limb contacted only the force platform and the running speed remained within ± 5% of the target.
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Run-to-Stop Knee Contact Forces Joint kinematics were quantified from the trajectories of thirty-six (14 mm diameter) reflective skin markers, placed in accordance with our previous work (Brown et al. 2014a, 2014b & 2016, Appendix A). Initially, the participant stood stationary in a neutral anatomical position while a high-speed (240 fps) recording was taken. This stationary recording was used to define an eight segment (bilateral foot, shank and thigh, and pelvis and torso) kinematic model using Visual 3D v4.00 (C-Motion, Rockville, MD). The knee and ankle joint centers were calculated in accordance with previous literature (Grood and Suntay, 1983; Wu et al., 2002), and the hip joint center was calculated from a method adapted from Schwartz and Rozumalski (2005). During each RTS, GRF data and marker trajectories were low pass filtered with a fourth-order Butterworth filter at a cut-off frequency of 12 Hz. Hip, knee and ankle joint angles were calculated during the single limb support phase of each RTS using Visual 3D and expressed relative to each participant’s stationary pose. Single limb support was defined as the time from dominant limb heel contact to heel contact of the contralateral, non-dominant limb (i.e. weight acceptance of the stopping phase of the RTS). Simulation Protocol: Subject-specific anthropometric scaling parameters, joint kinematics and GRFs for each RTS trial were exported into OpenSim 3.2 (Delp et al., 2007). For each subject, a generic musculoskeletal model containing 23 degrees-of-freedom and 92 muscle actuators was scaled to their anthropometrics. A residual reduction algorithm (RRA) accounted for dynamic inconsistencies between the GRF and experimental kinematics data. While the light load was considered negligible for modeling purposes, the additional mass for the medium and heavy load conditions were applied to the model prior to running RRA. The medium load assumed the 20 kg body borne load was evenly distributed across the torso and was applied at the torso CoM
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Run-to-Stop Knee Contact Forces (Figure 1B). For the heavy load, a second 20 kg mass, representing the backpack, was applied 10 cm posteriorly and 5 cm below the torso CoM (Figure 1C). Simulation trials were excluded from the analysis if any of the residuals estimated by RRA were outside the recommendations provided by OpenSim. A static optimization approach, with an objective function to minimize the sum of squared activations, resolved individual muscle forces from the net joint moments calculated by OpenSim. The Joint Reaction analysis tool in OpenSim estimated knee JCF, which represents the force applied on the knee due to all muscle, inertial, and external forces during the RTS. The compressive knee JCF was defined as the resultant force acting on the tibial plateau and parallel to the long axis of the tibia (Steele et al., 2012). Additionally, joint moments were calculated by OpenSim using the Inverse Dynamics tool. Dimensionless
was defined as the ratio of the normalized peak vertical GRF, ̃
to the normalized change in leg length during single limb support, ̃ (Silder et al., 2015): ̃ ̃ where
is the difference between leg length at initial heel contact and the minimum leg
length during single limb support. Vertical GRF was normalized to body weight. Leg length was estimated as the total three-dimensional distance between the foot center-of-pressure to the musculoskeletal model pelvis CoM, normalized to leg length at initial heel contact ( ). The pelvis CoM during the RTS was calculated using the Body Kinematics tool in OpenSim. Sagittal plane joint flexion angles ( ) and moments (
) were determined for the
dominant limb during the single limb support phase of the RTS (where represents hip, knee, and ankle) and were normalized to 101 points (0-100% of single limb support). Maximum joint angles and joint moments were calculated during single limb support. Peak knee JCF, Page 8
,
Run-to-Stop Knee Contact Forces anterior-posterior GRF (
), and
were also calculated as their maximum value during
single limb support. Vertical ( ) and anterior-posterior impulse (
) were calculated during
single limb support as the area under the respective ground reaction force curve, and represented the change in CoM momentum during the RTS. Forces and impulses were normalized to subject body weight (BW) and moments were normalized to BW and subject height. Bodyweight values used for normalization were each participants “nude” BW and excluded any body borne load. Statistical Analysis: The dependent variables were peak
,
, JCF,
,
,
,
,
during
single limb support. For each participant, each dependent variable was averaged across the three successful trials and submitted to a repeated measures ANOVA to test the effects of load configuration (light, medium, and heavy). In instances where statistically significant differences were observed, a Bonferroni correction was used for post-hoc comparisons between load configurations (light, medium, heavy) to reduce the probability of committing type I error. All statistical analyses were performed using SPSS v21 software (IBM, Armonk, NY, USA). An a priori alpha level of P < 0.05 denoted statistical significance. If results approached significance, effect size was calculated using Cohen’s d (Cohen, 1992). Results: Mean data for each dependent variable can be found in Table 1. During the RTS, body borne load significantly increased peak JCF (p<0.001) (Figure 2) across load conditions. Specifically, JCF was significantly larger with the heavy compared to medium by 0.6 BW (p=0.027) and light (p<0.001) load by 1.2 BW, and for the medium compared to the light load (p=0.024) by 0.6 BW. Body borne load also had a significant effect on peak and
(p=0.002) (Figure 3). Peak
(p<0.001)
was significantly larger with the heavy load
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Run-to-Stop Knee Contact Forces compared to the medium by 0.4 BW (p=0.040) and light (p<0.001) load by 0.6 BW, but similar differences were not observed between the medium and light loads (p=0.131). Peak
was
significantly larger with heavy compared to light load (p=0.001), but significant differences were not evident between the medium and light (p=0.259) or heavy loads (p=0.298), respectively. Body borne load had no statistically significant effect on revealed an increase in medium load (
(p=0.073). Further analysis
with the heavy compared to the light (
= 2.3; d = 0.615) and
= 1.7; d = 0.490), respectively (Cohen, 1992). Considering the small sample
size (n=9), significant changes in
may have been detected if more subjects were recruited
for this study. There was a significant increase in both conditions.
(p<0.001) and
(p<0.001) across all load
was 1.4 BW larger with the heavy load compared to the light load (p<0.001), and
1.0 BW larger compared to the medium load (p=0.001). Additionally, the medium load was significantly larger (p=0.040) than the light load by 0.4 BW.
was significantly larger with the
heavy load compared to the medium by 0.3 BW (p=0.008) and light (p<0.001) load by 0.4 BW, but similar differences were not observed between the medium and light loads (p=0.309). Across load conditions during the RTS, body borne load had a significant effect on hip (p=0.026) and knee (p=0.046) posture. Specifically, peak hip flexion decreased significantly with the medium compared to light load (p=0.037), but there was no difference between the heavy and light (p=0.405) or medium loads (p=0.798). Peak knee flexion decreased significantly with the heavy compared to medium load (p=0.047), but similar differences were not evident between light and medium (p=1.000) or heavy loads (p=0.106). Body borne load had no significant effect on ankle posture (p=0.150), or peak moments of the hip (p=0.298), knee (p=0.794) or ankle (p=0.409). Page 10
Run-to-Stop Knee Contact Forces Discussion: The rapid deceleration required during the RTS is common within many sports, recreational, and military activities. To successfully perform the RTS, the lower extremity must rapidly and safely decelerate the body CoM. For military populations, this requires decelerating the soldier’s bodyweight and any additional body borne load. In fact, increased body borne load is reported to impair a soldier’s locomotor ability (Brown et al., 2014b) and may increase their risk of suffering a musculoskeletal injury. The observed 1.2 BW significant increase in knee JCF across loading conditions supports this contention. Specifically, in agreement with Knarr et al. (2016), we found an incremental 0.6 BW increase in knee JCF between each body borne load (i.e., light, medium and heavy). Our knee JCF estimates for the light load (~ 2.4 BW) were comparable to in vivo measurements of peak tibial compressive forces (i.e. tibio-femoral contact force) reported for many daily activities (D'Lima et al., 2012), including gait (~2-2.5 BW) (Fregly et al., 2012). These “normal” loads are conducive for healthy joint growth and maintenance of the joint (Carter and Wong, 1988; Wong and Carter, 2003), but substantially greater forces may result in abnormal loading at the knee. In fact, the observed knee JCF for the medium and heavy load were upwards of 0.6 (25%) and 1.2 (50%) BW larger than reported during normal daily activities, respectively. This may cause elevated joint loading and lead to increased pain (Eckstein et al., 2002). Ultimately, the increase in joint loads apparent with body borne load may lead to degeneration of joint articular cartilage. Further research is warranted to determine whether soldiers are at greater risk of long-term joint degradation, such as osteoarthritis, as a result. The increased knee JCF evident with increased body borne load may stem from elevated GRFs. The GRF reportedly makes a substantial, linear contribution to JCF (Knarr et al., 2016).
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Run-to-Stop Knee Contact Forces During the RTS, peak vGRF increased 0.2 BW (12%) and 0.6 BW (35%) with the medium and heavy loads compared to the light load, respectively. This finding is consistent with previous studies that found peak vGRF increased with the addition of body borne load during walking (Kinoshita et al., 1985; Silder et al., 2013), running (Silder et al., 2015) and landing (Brown et al., 2016; Sell et al., 2010). Although the larger GRFs may increase the current knee JCFs, they are suggested to produce less than half the change in JCF during locomotion (Knarr et al., 2016). Muscle forces, which are necessary for joint stability are thought to be the primary contributor to JCF. However, contrary to our hypothesis and previous experimental evidence (Brown et al., 2014a & 2014b), lower limb (i.e., hip, knee and ankle) joint moments did not significantly increase across load conditions during the RTS. It may be an altered neuromuscular control strategy, such as co-contraction, was adopted when performing a loaded RTS task. During dynamic movements, muscle co-contraction is a potential neuromuscular control strategy used to stabilize and protect a joint (Ford et al., 2008). Co-contraction of various knee flexor and extensor muscles can result in increased JCF, without affecting overall joint moments. Further research is warranted to determine the precise contributors to the elevated knee JCF with body borne load. To help control the rapid deceleration of the RTS and slow the CoM’s momentum, the soldier needs adequate
. Yet, excessive
may also increase injury risk of such tasks by
transmitting large GRFs up the kinetic chain. While Caron et al. (2015) and Silder et al (2015) reported greater
with the addition of load during walking and running, the soldiers in the
present study did not exhibit a significant increase in
across the load conditions during the
RTS. Only when donning the heavy load did the participants exhibit a substantial, yet insignificant, increase in
compared to light (d=0.615) and medium loads (d=0.490). The
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Run-to-Stop Knee Contact Forces current discrepancy is likely due to the small sample size. Significant changes in
may be
detected if more subjects were analyzed, considering the current participants were required to produce a larger change in momentum (i.e., vertical and anterior-posterior impulse) to safely decelerate with body borne load during the RTS. To safely execute the RTS, the current load carriers exhibited a significant reduction in hip flexion posture with the medium load and a reduction in knee flexion posture with the heavy load, respectively. These kinematic differences may be due to the specific load configurations the soldiers donned. Specifically, the medium load created an anterior shift in torso CoM and required greater hip extensor control of deceleration; whereas, the heavy load created a posterior shift in torso CoM and greater knee extensor control of deceleration. It may be that the posterior borne, heavy load requires an extended knee and stiffer leg to safely and successfully dissipate the braking forces that impact the lower limb with that load configuration. In fact, peak posterior GRF (i.e., braking force) was significantly greater with the heavy as compared to light load configuration. Our findings suggest that with the heavy load condition, a soldier’s injury risk may be greatest due to the coupling of a stiff leg, an extended knee and a large braking force. This biomechanical profile may ultimately translate to unsafe shear forces at the knee, increasing the likelihood of injury. Further work is warranted to determine whether it is the specific load or load configuration that translates to the hazardous biomechanical profile exhibited by the soldier during the RTS. While previous studies have found changes in joint loading during simulated obesity (Knarr et al., 2015; Messier et al., 2005), their external load was evenly added across all segments. The soldier, however, primarily adds external load to their torso (i.e., body armor, rucksacks and ammo panels). To simulate military-relevant equipment configurations, the
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Run-to-Stop Knee Contact Forces current model added the external body borne load directly to the torso and the lower-extremity segment inertial properties remain the same for all loading conditions. It is likely that the musculoskeletal system has had time to compensate for the additional segmental mass gained with obesity, a soldier’s musculoskeletal system must adapt to intermittent load carriage during their service time. Therefore, this modeling method provides a better representation of both the internal and external changes a soldier experiences during the RTS. A limitation of the current study was the sample size. With a larger sample, the medium effect in increased
exhibited with the heavy load may have reached statistical significance.
Another limitation of the present study was our static optimization. Previously, musculoskeletal models were optimized with specific muscle weighting factors to agree with data collected from an instrumented knee implant within an elderly male (Haight et al., 2014; Knarr et al., 2016; Lerner et al., 2014; Steele et al., 2012). Considering our subjects were young, healthy military personnel, optimizing the musculoskeletal model with anthropometric data from an elderly male might not be suitable. Regardless, we believe our JCF is reasonably accurate and would significantly increase with the addition of body borne load using either optimization technique. Conclusion: In conclusion, body borne load resulted in larger knee JCFs, and potentially greater musculoskeletal injury risk, across all load conditions. The larger knee JCF exhibited during the RTS was primarily due to greater GRFs that impact the soldier with each incremental addition of body borne load. To safely execute the RTS with the medium or heavy loads, the soldier adopted an extended hip or knee, depending on the specific load configuration. Specifically, the medium load resulted in an extended hip, while the heavy load resulted in an extended knee and a substantial increase in stance
. The stiff leg, extended knee and large braking force the
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Run-to-Stop Knee Contact Forces soldiers exhibited with the heavy load suggests their injury risk may be greatest with that specific load configuration. Further work is needed to determine if the biomechanical profile exhibited with the heavy load configuration translates to unsafe shear forces at the knee and consequently, a higher likelihood of injury. Acknowledgements: This work was supported by a FY 2012–2014 Competitive In-house Laboratory Independent Research (ILIR) Award program from the Department of the Army, Office of the Assistant Secretary of the Army – Acquisition Logistics and Technology. The authors thank Ms. Marina Carboni and Mr. Albert Adams for their assistance with this study. Conflicts of Interest: The authors report no conflicts of interest.
Table 1. Mean values for each dependent variable. Forces and impulses are normalized to bodyweight (BW), and moments are normalized to bodyweight and total height (BWxHt).
(°) (°) (°)
Light
Medium
Heavy
P value
1.7 (± 0.4) 0.8 (± 0.2) 2.4 (± 0.6) 10.0 (± 4.5) 2.6 (± 0.4) 1.1 (± 0.3) 11.9 (± 6.3) 95.7 (± 7.7) 52.2 (± 17.1) 0.04 (± 0.02) 0.04 (± 0.02) 0.05 (± 0.04)
1.9 (± 0.4) 0.9 (± 0.2) 3.0 (± 0.5) 10.5 (± 4.3) 3.0 (± 0.5) 1.2 (± 0.2) 13.6 (± 5.5) 95.5 (± 7.9) 44.7 (± 13.3) 0.03 (± 0.01) 0.05 (± 0.02) 0.05 (± 0.04)
2.3 (± 0.4) 1.1 (± 0.2) 3.6 (± 0.7) 12.3 (± 2.5) 4.0 (± 0.7) 1.5 (± 0.3) 16.3 (± 5.0) 91.1 (± 7.5) 47.1 (± 10.1) 0.04 (± 0.02) 0.05 (± 0.04) 0.07 (± 0.05)
< 0.001 0.002 < 0.001 0.073 < 0.001 < 0.001 0.150 0.046 0.026 0.409 0.794 0.298
Figure 1. Load configurations used during experimental trials (top) and computer simulations (bottom).
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Run-to-Stop Knee Contact Forces Figure 2. Mean normalized knee joint contact forces across three different loads during the single limb support phase of the run-to-stop. Shaded regions represent standard deviations. Figure 3. Mean vertical (A) and anterior-posterior (B) ground reaction forces across three different loads during the single limb support phase of the run-to-stop. Shaded regions represent standard deviations.
Appendix: Table A.1: Retro-reflective marker (~ 14 mm) placement. Segment
Markers
Pelvis:
7th cervical vertebrae, acromion processes (bilateral), sternoclavicular notch, xiphoid process (virtual marker), 10th thoracic vertebrae (virtual marker) posterior superior iliac spine, anterior superior iliac spine, superior iliac crest
Thigh:
greater trochanter, medial and lateral femoral epicondyles, anterior thigh
Shank:
tibial tuberosity, lateral fibia, distal tibia
Foot:
medial and lateral malleoli, calcaneus, middle cuneiform, second and fifth metatarsal heads
Trunk:
Almeida, S.A., Trone, D.W., Leone, D.M., Shaffer, R.A., Patheal, S.L., Long, K., 1999. Gender differences in musculoskeletal injury rates: a function of symptom reporting. Medicine and Science in Sports and Exercise 31, 1807-1812. Andriacchi, T.P., Mündermann, A., Smith, R. L., Alexander, E. J., Dyrby, C. O., Koo, S., 2004. A framework for the in vivo pathomechanics of osteoarthritis at the knee. Annals of Biomedical Engineering 32, 447-457. Arampatzis, A., Brüggemann, G.P., Metzler, V., 1999. The effect of speed on leg stiffness and joint kinetics in human running. Journal of Biomechanics 32, 1349-1353. Birrell, S.A., Hooper, R.H., Haslam, R.A., 2007. The effect of military load carriage on ground reaction forces. Gait and Posture 26, 611-614. Brown, T.N., O'Donovan, M., Hasselquist, L., Corner, B., Schiffman, J.M., 2014a. Soldierrelevant loads impact lower limb biomechanics during anticipated and unanticipated single-leg cutting movements. Journal of Biomechanics 47, 3494-3501.
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Run-to-Stop Knee Contact Forces Brown, T.N., O'Donovan, M., Hasselquist, L., Corner, B., Schiffman, J.M., 2016. Lower limb flexion posture relates to energy absorption during drop landings with soldier-relevant body borne loads. Applied Ergonomics 52, 54-61. Brown, T.N., O'Donovan, M., Hasselquist, L., Corner, B.D., Schiffman, J.M., 2014b. Body borne loads impact walk-to-run and running biomechanics. Gait and Posture 40, 237-242. Burr, D.B., Martin, R.B., Schaffler, M.B., Radin, E.L., 1985. Bone remodeling in response to in vivo fatigue microdamage. Journal of Biomechanics 18, 189-200. Caron, R.R., Lewis, C.L., Saltzman, E., Wagenaar, R.C., Holt, K.G. 2015. Musculoskeletal stiffness changes linearly in response to increasing load during walking gait. Journal of Biomechanics 48, 1165-1171. Carter, D. R., Wong, M., 1988. The role of mechanical loading histories in the development of diarthrodial joints. Journal of Orthopaedic Research 6, 804-816. Cohen, J., 1992. A power primer. Psychological Bulletin 112, 155-159. D'Lima, D.D., Fregly, B.J., Patil, S., Steklov, N., Colwell, C.W., 2012. Knee joint forces: prediction, measurement, and significance. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 226, 95-102. D'Lima, D.D., Patil, S., Steklov, N., Slamin, J.E., Colwell, C.W., Jr., 2006. Tibial forces measured in vivo after total knee arthroplasty. The Journal of Arthroplasty 21, 255-262. Delp, S.L., Anderson, F.C., Arnold, A.S., Loan, P., Habib, A., John, C.T., Guendelman, E., Thelen, D.G., 2007. OpenSim: open-source software to create and analyze dynamic simulations of movement. IEEE Transactions on Biomedical Engineering 54, 1940-1950. Demers, M.S., Pal, S., Delp, S.L., 2014. Changes in tibiofemoral forces due to variations in muscle activity during walking. Journal of Orthopaedic 32, 769-776. Eckstein, F., Faber, S., Muhlbauer, R., Hohe, J., Englmeier, K.H., Reiser, M., Putz, R., 2002. Functional adaptation of human joints to mechanical stimuli. Osteoarthritis and Cartilage 10, 4450. Edwards, W.B., Gillette, J.C., Thomas, J.M., Derrick, T.R., 2008. Internal femoral forces and moments during running: implications for stress fracture development. Clinical Biomechanics 23, 1269-1278. Farley, C.T., González, O., 1996. Leg stiffness and stride frequency in human running. Journal of Biomechanics 29, 181-186.
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Run-to-Stop Knee Contact Forces Ford, K.R., van den Bogert, J., Myer, G.D., Shapiro, R., Hewett, T.E. 2008. The effects of age and skill level on knee musculature co-contraction during functional activities: a systematic review. British Journal of Sports Medicine 42, 561-566. Fregly, B.J., Besier, T.F., Lloyd, D.G., Delp, S.L., Banks, S.A., Pandy, M.G., D'Lima, D.D., 2012. Grand challenge competition to predict in vivo knee loads. Journal of Orthopaedic Research 30, 503-513. Gilchrist, J., Jones, B.H., Sleet, D.A., Kimsey, C.D., 2000. Exercise-related injuries among women: strategies for prevention from civilian and military studies. MMWR Recommendations and Reports 49, 15-33. Granata, K.P., Padua, D.A., Wilson, S.E., 2002. Gender differences in active musculoskeletal stiffness. Part II. Quantification of leg stiffness during functional hopping tasks. Journal of Electromyography and Kinesiology 12, 127-135. Grimston, S. K., Engsberg, J. R., Kloiber, R., Hanley, D. A., 1991. Bone Mass, External Loads, and Stress Fracture in Female Runners. Journal of Applied Biomechanics 7, 293-302. Grood, E.S., Suntay, W.J., 1983. A Joint Coordinate System for the Clinical Description of Three-Dimensional Motions: Application to the Knee. Journal of Biomechanical Engineering 105, 136-144. Haight, D.J., Lerner, Z.F., Board, W.J., Browning, R.C., 2014. A comparison of slow, uphill and fast, level walking on lower extremity biomechanics and tibiofemoral joint loading in obese and nonobese adults. Journal of Orthopaedic 32, 324-330. Harman, E.A., Han, K., Frykman, P.N., Pandorf, C., 2000. The effects of backpack weight on the biomechanics of load carriage. USARIEM Technical Report, Natick, MA. Hauret, K.G., Shippey, D.L., Knapik, J.J., 2001. The Physical Training and rehabilitation program: Duration of rehabilitation and final outcome of injuries in basic combat training. Military Medicine, 166, 820-826. Hauret, K.G., Jones, B.H., Bullock, S.H., Canham-Chervak, M., Canada, S., 2010. Musculoskeletal injuries description of an under-recognized injury problem among military personnel. American Journal of Preventive Medicine 38, S61-70. Hennig, E.M., Lafortune, M.A., 1991. Relationships between ground reaction force and tibial bone acceleration parameters. Journal of Applied Biomechanics, 7, 303-309. Johnson, K.J. 2003. Tears of cruciate ligaments of the knee: US Armed Forces: 1990–2002. Med Surveillance Monthly 9, 2-6. Jones, B.H., Cowan, D.N., Knapik, J.J. 1994. Exercise, training and injuries. Sports Medicine 18, 202-214. Page 18
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Jones, B.H., Canham-Chervak, M., Sleet, D.A., 2010. An evidence-based public health approach to injury priorities and prevention recommendations for the U.S. Military. American Journal of Preventive Medicine 38, S1-10. Kaufman, K.R., Brodine, S., Shaffer, R., 2000. Military training-related injuries: surveillance, research, and prevention. American Journal of Preventive Medicine 18, 54-63. Kellis, E., Arabatzi, F., Papadopoulos, C., 2003. Muscle co-activation around the knee in drop jumping using the co-contraction index. Journal of Electromyography and Kinesiology 13, 229238. Kinoshita, H., 1985. Effects of different loads and carrying systems on selected biomechanical parameters describing walking gait. Ergonomics 28, 1347-1362. Knapik, J.J., Hauret, K.G., Canada, S., Marin, R., Jones, B.H., 2011. Association between ambulatory physical activity and injuries during United States Army Basic Combat Training. Journal of Physical Activity and Health 8, 496-502. Knarr, B.A., Higginson, J.S., 2015. Practical approach to subject-specific estimation of knee joint contact force. Journal of Biomechanics 48, 2897-2902. Knarr, B.A., Higginson, J.S., Zeni, J.A., 2016. Change in knee contact force with simulated change in body weight. Computer Methods in Biomechanics and Biomedical Engineering 19, 320-323. Kutzner, I., Heinlein, B., Graichen, F., Bender, A., Rohlmann, A., Halder, A., Beier, A., Bergmann, G., 2010. Loading of the knee joint during activities of daily living measured in vivo in five subjects. Journal of Biomechanics 43, 2164-2173. Lerner, Z.F., Haight, D.J., DeMers, M.S., Board, W.J., Browning, R.C., 2014. The effects of walking speed on tibiofemoral loading estimated via musculoskeletal modeling. Journal of Applied Biomechanics 30, 197-205. McMahon, T.A., Cheng, G.C., 1990. The mechanics of running: How does stiffness couple with speed. Journal of Biomechanics 23, 65-78. McNitt-Gray, J. L., 1991. Kinematics and impulse characteristics of drop landing from three heights. International Journal of Sport Biomechanics 7, 201-224. Mundermann, A., Dyrby, C.O., D'Lima, D.D., Colwell, C.W., Jr., Andriacchi, T.P., 2008. In vivo knee loading characteristics during activities of daily living as measured by an instrumented total knee replacement. Journal of Orthopaedic 26, 1167-1172.
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Run-to-Stop Knee Contact Forces Wong, M., Carter, D.R., 2003. Articular cartilage functional histomorphology and mechanobiology: a research perspective. Bone 33, 1-13. Wu, G., Siegler, S., Allard, P., Kirtley, C., Leardini, A., Rosenbaum, D., Whittle, M., D'Lima, D.D., Cristofolini, L., Witte, H., Schmid, O., Stokes, I., 2002. ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motion-Part I: ankle, hip, and spine. Journal of Biomechanics 35, 543-548.
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PII: DOI: Reference:
S0021-9290(16)31120-4 http://dx.doi.org/10.1016/j.jbiomech.2016.10.022 BM7932
To appear in: Journal of Biomechanics Accepted date: 16 October 2016 Cite this article as: John W. Ramsay, Clifford L. Hancock, Meghan P. O’Donovan, Tyler N. Brown and John W Ramsay, Soldier-relevant body borne loads increase knee joint contact force during a run-to-stop maneuver, Journal of Biomechanics, http://dx.doi.org/10.1016/j.jbiomech.2016.10.022 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Run-to-Stop Knee Contact Forces Title of this Original Article: Soldier-relevant body borne loads increase knee joint contact force during a run-to-stop maneuver
Authors and Affiliations: Author 1: John W. Ramsay Natick Soldier Research, Development, and Engineering Center, Natick, MA 01760 Author 2; Clifford L. Hancock Natick Soldier Research, Development, and Engineering Center, Natick, MA 01760 Author 3: Meghan P. O’Donovan Natick Soldier Research, Development, and Engineering Center, Natick, MA 01760 Author 4: Tyler N. Brown Boise State University, Boise, ID, 83725 Oak Ridge Institute for Science and Education (ORISE), Belcamp, MD, USA Contact Information: John W, Ramsay, PhD U.S. Army Natick Soldier Research, Development, and Engineering Center 15 General Greene Avenue Natick, MA 01760 Email: [email protected] Fax: 508-233-6472 Phone: 508-233-4496 Keywords: load carriage, knee contact force, run to stop, OpenSim, leg stiffness Abstract: The purpose of this study was to understand the effects of load carriage on human performance, specifically during a run-to-stop (RTS) task. Using OpenSim analysis tools, knee joint contact force, grounds reaction force, leg stiffness and lower extremity joint angles and moments were determined for nine male military personnel performing a RTS under three load configurations (light, ~6 kg, medium, ~20 kg, and heavy, ~40 kg). Subject-based means for each Page 1
Run-to-Stop Knee Contact Forces biomechanical variable were submitted to repeated measures ANOVA to test the effects of load. During the RTS, body borne load significantly increased peak knee joint contact force by 1.2 BW (p<0.001) and peak vertical (p<0.001) and anterior-posterior (p=0.002) ground reaction forces by 0.6 BW and 0.3 BW, respectively. Body borne load also had a significant effect on hip (p=0.026) posture with the medium load and knee (p=0.046) posture with the heavy load. With the heavy load, participants exhibited a substantial, albeit non-significant increase in leg stiffness (p = 0.073 and d=0.615). Increases in joint contact force exhibited during the RTS were primarily due to greater GRFs that impact the soldier with each incremental addition of body borne load. The stiff leg, extended knee and large braking force the soldiers exhibited with the heavy load suggests their injury risk may be greatest with that specific load configuration. Further work is needed to determine if the biomechanical profile exhibited with the heavy load configuration translates to unsafe shear forces at the knee joint and consequently, a higher likelihood of injury. Introduction: A major concern for military populations is musculoskeletal injury (Kaufman et al., 2000). Musculoskeletal injuries cost the armed forces hundreds of millions of dollars in lost productivity and treatment each year (Ruscio et al., 2010). These injuries often result during military training-related activities (Jones et al., 2010; Hauret et al., 2010), when soldiers don heavy body borne loads (e.g. body armor, weapon systems, rucksacks) in excess of 45 kg (Task Force Devil Combined Arms Assessment Team, 2003). The resulting musculoskeletal injuries not only have an immediate and detrimental impact on soldiers’ health, but often result in reinjury (Hauret et al., 2001) that can end in long-term disability and subsequent discharge from the military (Gilchrist et al., 2000).
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Run-to-Stop Knee Contact Forces More than three quarters of musculoskeletal injuries sustained during military training occur in the lower extremity (Almeida et al., 1999). These injuries, including sprain, strain or rupture of a joint’s soft tissue, primarily occur at the knee (Hauret et al., 2010; Kaufman et al., 2000; Shaffer et al. 1999). These injuries often result during landing and pivoting maneuvers that require a quick change of speed and/or direction (Olsen et al., 2004), which are customary during military training (Johnson, 2003). One maneuver of particular interest is a run-to-stop (RTS), which occurs operationally when the soldier quickly avoids or reacts to enemy fire. To successfully perform a RTS, the soldier must rapidly and completely decelerate the body centerof-mass (CoM) by controlling the segment inertias as they pass down the lower extremity (McNitt-Gray, 1991). To prevent lower limb collapse during the RTS, the soldier may adopt a biomechanical profile that gives rise to unsafe joint loads, particularly at the knee, increasing risk of musculoskeletal injury. Donning body borne load may further elevate musculoskeletal injury risk during the RTS by altering the soldier’s lower limb biomechanical profile (Patton et al., 1991). While running, cutting, and landing with body borne load, the soldier exhibits larger joint moments and significant adaptations of the stance leg sagittal plane motions (Brown et al., 2014a; Brown et al., 2014b; Silder et al., 2015). These biomechanical adaptations may prevent stance leg collapse and aid with dissipating the increased ground reaction forces (GRF) evident with body borne load (Kinoshita et al., 1985; Silder et al., 2015; Silder et al., 2013). Adding body borne load reportedly increases both peak magnitude (Birrell et al., 2007; Harman et al., 2000; Polcyn et al., 2002; Wang et al., 2012) and transmission rate of the vertical GRF (Wang et al., 2012). The elevated GRF may result in larger knee joint compressive forces, which possibly increase risk of soft tissue damage and long term joint deterioration. While changes in GRFs have been well
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Run-to-Stop Knee Contact Forces documented during steady-state movements such as walking and running with body borne load, little is known about how they change during a sudden deceleration task with a body borne load. To safely prevent lower limb collapse during the RTS, the soldier may alter their stance leg stiffness
. Leg stiffness, i.e. resistance of the leg to deformation, is necessary to safely
perform dynamic maneuvers (McMahon and Cheng, 1990). As the demands of physical activity increase, such as by adding body borne load,
typically increases (Arampatzis et al., 1999;
Farley and González, 1996; Granata et al., 2002). While adequate
is necessary to
successfully complete maneuvers such as the RTS, exposure to atypical stiffness may increase musculoskeletal injury risk by requiring more rapid transmission of large forces through the lower limb (Burr et al., 1985; Grimston et al., 1991; Hennig and Lafortune, 1991; Radin et al., 1978). Leg stiffness reportedly increases with body borne load during walking (Caron et al., 2015) and running Silder et al. (2015), but it is unknown if
increases with the addition of
load during a dynamic military-relevant RTS task. Knee joint contact loads (i.e. tibiofemoral compressive forces) vary between 2-3 times body weight during normal daily activities such as walking (D'Lima et al., 2006; Kutzner et al., 2010; Mundermann et al., 2008), and may reach 15 times body weight during unloaded running (Edwards et al., 2008). During a RTS, the sudden deceleration may cause large tibiofemoral compressive forces, particularly with body borne loads in excess of 45 kg. Knarr et al. (2016) found knee joint contact force (JCF) increases with each incremental addition of body borne load. Therefore, it is of interest to quantify the changes in JCF due to the addition of body borne load, especially during quick deceleration tasks common during military training. These elevated loads can lead to joint pain, injury and cartilage degeneration (Eckstein et al., 2002) that results in long-term disability of the joint (Andriacchi, 2004).
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Run-to-Stop Knee Contact Forces The current purpose was to investigate changes in lower limb (i.e., hip, knee and ankle) biomechanics and JCF with the addition of body borne load during a RTS maneuver. While typical motion capture techniques allow for the quantification of lower limb mechanics, noninvasive measurement of internal joint compressive forces can be difficult to obtain in vivo. Recent developments in musculoskeletal modeling and simulation, however, have enabled the prediction of internal joint forces experienced during a dynamic task (Demers et al., 2014; Knarr and Higginson, 2015). In this study, musculoskeletal models simulated the effect that external body borne load has on JCF. We hypothesized that during the RTS, hip, knee and ankle flexion angles and moments, vertical GRF,
, impulse and knee JCF would increase as body borne
load increases. Methods: Subjects: Nine male military personnel (21.1 ± 3.8 yrs, 72.5 ± 9.4 kg, 1.8 ± 0.1 m) participated in this study. Each participant self-reported the ability to safely carry body borne loads heavier than 40 kg. Participants were excluded from the study if they reported current pain or recent injury to the back or lower extremity (within six months), had a history of back or lower extremity injury or surgery, and/or any known neurological disorders. All subjects provided written consent, approved by the local (United States Army Research Institute of Environmental Medicine) institutional review board, prior to testing. Experimental Protocol: Three test sessions were completed by each participant. During each test session, participants donned a different body borne load configuration (light, medium, or heavy) (Figure 1). The light load (~6 kg; Figure 1A) was composed of a helmet, mock weapon, combat boots,
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Run-to-Stop Knee Contact Forces socks and spandex shirt and shorts. The medium load (~20 kg; Figure 1B) required the participant don body armor with a fabric ammo panel attached on the anterior, in addition to the light load. The heavy load (~40 kg; Figure 1C) required the participant don a standard issue military backpack, in addition to the medium load. To randomize the testing order for each participant, the testing sequence of each load configuration was predetermined by a 3x3 Latin Square scheme. During each test session, the participant performed three successful RTS maneuvers. The RTS required the participant to run down a 10 m walkway at 3.5 m/s (7.8 mph) and plant their dominant limb on a force platform embedded in the floor, immediately stopping in a low ready position (i.e. eyes forward, weapon pointed downward at ~45°, legs wide and slightly bent). The dominant limb was defined as the leg each participant self-reported they could kick a ball the farthest. The running speed was set at 3.5 m/s to remain consistent with our previous load carriage work (Brown et al., 2014a & 2014b). Additionally, to minimize fatigue during data collection, all subjects were given ample time to rest between trials and were provided water to maintain adequate hydration. During each RTS, three-dimensional joint (i.e. hip, knee, and ankle) kinetic and kinematic data were recorded. A force platform (AMTI Optima, Advanced Mechanical Technology Inc., Watertown, MA, USA) captured GRF data at 1200 Hz, while twelve highspeed (240 fps) cameras (Oqus, Qualisys AB, Gothenburg, Sweden) captured synchronous motion capture data. Running speed was monitored by two sets of timing gates (Brower Timing, Draper, UT, USA). A trial was successful if the dominant limb contacted only the force platform and the running speed remained within ± 5% of the target.
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Run-to-Stop Knee Contact Forces Joint kinematics were quantified from the trajectories of thirty-six (14 mm diameter) reflective skin markers, placed in accordance with our previous work (Brown et al. 2014a, 2014b & 2016, Appendix A). Initially, the participant stood stationary in a neutral anatomical position while a high-speed (240 fps) recording was taken. This stationary recording was used to define an eight segment (bilateral foot, shank and thigh, and pelvis and torso) kinematic model using Visual 3D v4.00 (C-Motion, Rockville, MD). The knee and ankle joint centers were calculated in accordance with previous literature (Grood and Suntay, 1983; Wu et al., 2002), and the hip joint center was calculated from a method adapted from Schwartz and Rozumalski (2005). During each RTS, GRF data and marker trajectories were low pass filtered with a fourth-order Butterworth filter at a cut-off frequency of 12 Hz. Hip, knee and ankle joint angles were calculated during the single limb support phase of each RTS using Visual 3D and expressed relative to each participant’s stationary pose. Single limb support was defined as the time from dominant limb heel contact to heel contact of the contralateral, non-dominant limb (i.e. weight acceptance of the stopping phase of the RTS). Simulation Protocol: Subject-specific anthropometric scaling parameters, joint kinematics and GRFs for each RTS trial were exported into OpenSim 3.2 (Delp et al., 2007). For each subject, a generic musculoskeletal model containing 23 degrees-of-freedom and 92 muscle actuators was scaled to their anthropometrics. A residual reduction algorithm (RRA) accounted for dynamic inconsistencies between the GRF and experimental kinematics data. While the light load was considered negligible for modeling purposes, the additional mass for the medium and heavy load conditions were applied to the model prior to running RRA. The medium load assumed the 20 kg body borne load was evenly distributed across the torso and was applied at the torso CoM
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Run-to-Stop Knee Contact Forces (Figure 1B). For the heavy load, a second 20 kg mass, representing the backpack, was applied 10 cm posteriorly and 5 cm below the torso CoM (Figure 1C). Simulation trials were excluded from the analysis if any of the residuals estimated by RRA were outside the recommendations provided by OpenSim. A static optimization approach, with an objective function to minimize the sum of squared activations, resolved individual muscle forces from the net joint moments calculated by OpenSim. The Joint Reaction analysis tool in OpenSim estimated knee JCF, which represents the force applied on the knee due to all muscle, inertial, and external forces during the RTS. The compressive knee JCF was defined as the resultant force acting on the tibial plateau and parallel to the long axis of the tibia (Steele et al., 2012). Additionally, joint moments were calculated by OpenSim using the Inverse Dynamics tool. Dimensionless
was defined as the ratio of the normalized peak vertical GRF, ̃
to the normalized change in leg length during single limb support, ̃ (Silder et al., 2015): ̃ ̃ where
is the difference between leg length at initial heel contact and the minimum leg
length during single limb support. Vertical GRF was normalized to body weight. Leg length was estimated as the total three-dimensional distance between the foot center-of-pressure to the musculoskeletal model pelvis CoM, normalized to leg length at initial heel contact ( ). The pelvis CoM during the RTS was calculated using the Body Kinematics tool in OpenSim. Sagittal plane joint flexion angles ( ) and moments (
) were determined for the
dominant limb during the single limb support phase of the RTS (where represents hip, knee, and ankle) and were normalized to 101 points (0-100% of single limb support). Maximum joint angles and joint moments were calculated during single limb support. Peak knee JCF, Page 8
,
Run-to-Stop Knee Contact Forces anterior-posterior GRF (
), and
were also calculated as their maximum value during
single limb support. Vertical ( ) and anterior-posterior impulse (
) were calculated during
single limb support as the area under the respective ground reaction force curve, and represented the change in CoM momentum during the RTS. Forces and impulses were normalized to subject body weight (BW) and moments were normalized to BW and subject height. Bodyweight values used for normalization were each participants “nude” BW and excluded any body borne load. Statistical Analysis: The dependent variables were peak
,
, JCF,
,
,
,
,
during
single limb support. For each participant, each dependent variable was averaged across the three successful trials and submitted to a repeated measures ANOVA to test the effects of load configuration (light, medium, and heavy). In instances where statistically significant differences were observed, a Bonferroni correction was used for post-hoc comparisons between load configurations (light, medium, heavy) to reduce the probability of committing type I error. All statistical analyses were performed using SPSS v21 software (IBM, Armonk, NY, USA). An a priori alpha level of P < 0.05 denoted statistical significance. If results approached significance, effect size was calculated using Cohen’s d (Cohen, 1992). Results: Mean data for each dependent variable can be found in Table 1. During the RTS, body borne load significantly increased peak JCF (p<0.001) (Figure 2) across load conditions. Specifically, JCF was significantly larger with the heavy compared to medium by 0.6 BW (p=0.027) and light (p<0.001) load by 1.2 BW, and for the medium compared to the light load (p=0.024) by 0.6 BW. Body borne load also had a significant effect on peak and
(p=0.002) (Figure 3). Peak
(p<0.001)
was significantly larger with the heavy load
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Run-to-Stop Knee Contact Forces compared to the medium by 0.4 BW (p=0.040) and light (p<0.001) load by 0.6 BW, but similar differences were not observed between the medium and light loads (p=0.131). Peak
was
significantly larger with heavy compared to light load (p=0.001), but significant differences were not evident between the medium and light (p=0.259) or heavy loads (p=0.298), respectively. Body borne load had no statistically significant effect on revealed an increase in medium load (
(p=0.073). Further analysis
with the heavy compared to the light (
= 2.3; d = 0.615) and
= 1.7; d = 0.490), respectively (Cohen, 1992). Considering the small sample
size (n=9), significant changes in
may have been detected if more subjects were recruited
for this study. There was a significant increase in both conditions.
(p<0.001) and
(p<0.001) across all load
was 1.4 BW larger with the heavy load compared to the light load (p<0.001), and
1.0 BW larger compared to the medium load (p=0.001). Additionally, the medium load was significantly larger (p=0.040) than the light load by 0.4 BW.
was significantly larger with the
heavy load compared to the medium by 0.3 BW (p=0.008) and light (p<0.001) load by 0.4 BW, but similar differences were not observed between the medium and light loads (p=0.309). Across load conditions during the RTS, body borne load had a significant effect on hip (p=0.026) and knee (p=0.046) posture. Specifically, peak hip flexion decreased significantly with the medium compared to light load (p=0.037), but there was no difference between the heavy and light (p=0.405) or medium loads (p=0.798). Peak knee flexion decreased significantly with the heavy compared to medium load (p=0.047), but similar differences were not evident between light and medium (p=1.000) or heavy loads (p=0.106). Body borne load had no significant effect on ankle posture (p=0.150), or peak moments of the hip (p=0.298), knee (p=0.794) or ankle (p=0.409). Page 10
Run-to-Stop Knee Contact Forces Discussion: The rapid deceleration required during the RTS is common within many sports, recreational, and military activities. To successfully perform the RTS, the lower extremity must rapidly and safely decelerate the body CoM. For military populations, this requires decelerating the soldier’s bodyweight and any additional body borne load. In fact, increased body borne load is reported to impair a soldier’s locomotor ability (Brown et al., 2014b) and may increase their risk of suffering a musculoskeletal injury. The observed 1.2 BW significant increase in knee JCF across loading conditions supports this contention. Specifically, in agreement with Knarr et al. (2016), we found an incremental 0.6 BW increase in knee JCF between each body borne load (i.e., light, medium and heavy). Our knee JCF estimates for the light load (~ 2.4 BW) were comparable to in vivo measurements of peak tibial compressive forces (i.e. tibio-femoral contact force) reported for many daily activities (D'Lima et al., 2012), including gait (~2-2.5 BW) (Fregly et al., 2012). These “normal” loads are conducive for healthy joint growth and maintenance of the joint (Carter and Wong, 1988; Wong and Carter, 2003), but substantially greater forces may result in abnormal loading at the knee. In fact, the observed knee JCF for the medium and heavy load were upwards of 0.6 (25%) and 1.2 (50%) BW larger than reported during normal daily activities, respectively. This may cause elevated joint loading and lead to increased pain (Eckstein et al., 2002). Ultimately, the increase in joint loads apparent with body borne load may lead to degeneration of joint articular cartilage. Further research is warranted to determine whether soldiers are at greater risk of long-term joint degradation, such as osteoarthritis, as a result. The increased knee JCF evident with increased body borne load may stem from elevated GRFs. The GRF reportedly makes a substantial, linear contribution to JCF (Knarr et al., 2016).
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Run-to-Stop Knee Contact Forces During the RTS, peak vGRF increased 0.2 BW (12%) and 0.6 BW (35%) with the medium and heavy loads compared to the light load, respectively. This finding is consistent with previous studies that found peak vGRF increased with the addition of body borne load during walking (Kinoshita et al., 1985; Silder et al., 2013), running (Silder et al., 2015) and landing (Brown et al., 2016; Sell et al., 2010). Although the larger GRFs may increase the current knee JCFs, they are suggested to produce less than half the change in JCF during locomotion (Knarr et al., 2016). Muscle forces, which are necessary for joint stability are thought to be the primary contributor to JCF. However, contrary to our hypothesis and previous experimental evidence (Brown et al., 2014a & 2014b), lower limb (i.e., hip, knee and ankle) joint moments did not significantly increase across load conditions during the RTS. It may be an altered neuromuscular control strategy, such as co-contraction, was adopted when performing a loaded RTS task. During dynamic movements, muscle co-contraction is a potential neuromuscular control strategy used to stabilize and protect a joint (Ford et al., 2008). Co-contraction of various knee flexor and extensor muscles can result in increased JCF, without affecting overall joint moments. Further research is warranted to determine the precise contributors to the elevated knee JCF with body borne load. To help control the rapid deceleration of the RTS and slow the CoM’s momentum, the soldier needs adequate
. Yet, excessive
may also increase injury risk of such tasks by
transmitting large GRFs up the kinetic chain. While Caron et al. (2015) and Silder et al (2015) reported greater
with the addition of load during walking and running, the soldiers in the
present study did not exhibit a significant increase in
across the load conditions during the
RTS. Only when donning the heavy load did the participants exhibit a substantial, yet insignificant, increase in
compared to light (d=0.615) and medium loads (d=0.490). The
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Run-to-Stop Knee Contact Forces current discrepancy is likely due to the small sample size. Significant changes in
may be
detected if more subjects were analyzed, considering the current participants were required to produce a larger change in momentum (i.e., vertical and anterior-posterior impulse) to safely decelerate with body borne load during the RTS. To safely execute the RTS, the current load carriers exhibited a significant reduction in hip flexion posture with the medium load and a reduction in knee flexion posture with the heavy load, respectively. These kinematic differences may be due to the specific load configurations the soldiers donned. Specifically, the medium load created an anterior shift in torso CoM and required greater hip extensor control of deceleration; whereas, the heavy load created a posterior shift in torso CoM and greater knee extensor control of deceleration. It may be that the posterior borne, heavy load requires an extended knee and stiffer leg to safely and successfully dissipate the braking forces that impact the lower limb with that load configuration. In fact, peak posterior GRF (i.e., braking force) was significantly greater with the heavy as compared to light load configuration. Our findings suggest that with the heavy load condition, a soldier’s injury risk may be greatest due to the coupling of a stiff leg, an extended knee and a large braking force. This biomechanical profile may ultimately translate to unsafe shear forces at the knee, increasing the likelihood of injury. Further work is warranted to determine whether it is the specific load or load configuration that translates to the hazardous biomechanical profile exhibited by the soldier during the RTS. While previous studies have found changes in joint loading during simulated obesity (Knarr et al., 2015; Messier et al., 2005), their external load was evenly added across all segments. The soldier, however, primarily adds external load to their torso (i.e., body armor, rucksacks and ammo panels). To simulate military-relevant equipment configurations, the
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Run-to-Stop Knee Contact Forces current model added the external body borne load directly to the torso and the lower-extremity segment inertial properties remain the same for all loading conditions. It is likely that the musculoskeletal system has had time to compensate for the additional segmental mass gained with obesity, a soldier’s musculoskeletal system must adapt to intermittent load carriage during their service time. Therefore, this modeling method provides a better representation of both the internal and external changes a soldier experiences during the RTS. A limitation of the current study was the sample size. With a larger sample, the medium effect in increased
exhibited with the heavy load may have reached statistical significance.
Another limitation of the present study was our static optimization. Previously, musculoskeletal models were optimized with specific muscle weighting factors to agree with data collected from an instrumented knee implant within an elderly male (Haight et al., 2014; Knarr et al., 2016; Lerner et al., 2014; Steele et al., 2012). Considering our subjects were young, healthy military personnel, optimizing the musculoskeletal model with anthropometric data from an elderly male might not be suitable. Regardless, we believe our JCF is reasonably accurate and would significantly increase with the addition of body borne load using either optimization technique. Conclusion: In conclusion, body borne load resulted in larger knee JCFs, and potentially greater musculoskeletal injury risk, across all load conditions. The larger knee JCF exhibited during the RTS was primarily due to greater GRFs that impact the soldier with each incremental addition of body borne load. To safely execute the RTS with the medium or heavy loads, the soldier adopted an extended hip or knee, depending on the specific load configuration. Specifically, the medium load resulted in an extended hip, while the heavy load resulted in an extended knee and a substantial increase in stance
. The stiff leg, extended knee and large braking force the
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Run-to-Stop Knee Contact Forces soldiers exhibited with the heavy load suggests their injury risk may be greatest with that specific load configuration. Further work is needed to determine if the biomechanical profile exhibited with the heavy load configuration translates to unsafe shear forces at the knee and consequently, a higher likelihood of injury. Acknowledgements: This work was supported by a FY 2012–2014 Competitive In-house Laboratory Independent Research (ILIR) Award program from the Department of the Army, Office of the Assistant Secretary of the Army – Acquisition Logistics and Technology. The authors thank Ms. Marina Carboni and Mr. Albert Adams for their assistance with this study. Conflicts of Interest: The authors report no conflicts of interest.
Table 1. Mean values for each dependent variable. Forces and impulses are normalized to bodyweight (BW), and moments are normalized to bodyweight and total height (BWxHt).
(°) (°) (°)
Light
Medium
Heavy
P value
1.7 (± 0.4) 0.8 (± 0.2) 2.4 (± 0.6) 10.0 (± 4.5) 2.6 (± 0.4) 1.1 (± 0.3) 11.9 (± 6.3) 95.7 (± 7.7) 52.2 (± 17.1) 0.04 (± 0.02) 0.04 (± 0.02) 0.05 (± 0.04)
1.9 (± 0.4) 0.9 (± 0.2) 3.0 (± 0.5) 10.5 (± 4.3) 3.0 (± 0.5) 1.2 (± 0.2) 13.6 (± 5.5) 95.5 (± 7.9) 44.7 (± 13.3) 0.03 (± 0.01) 0.05 (± 0.02) 0.05 (± 0.04)
2.3 (± 0.4) 1.1 (± 0.2) 3.6 (± 0.7) 12.3 (± 2.5) 4.0 (± 0.7) 1.5 (± 0.3) 16.3 (± 5.0) 91.1 (± 7.5) 47.1 (± 10.1) 0.04 (± 0.02) 0.05 (± 0.04) 0.07 (± 0.05)
< 0.001 0.002 < 0.001 0.073 < 0.001 < 0.001 0.150 0.046 0.026 0.409 0.794 0.298
Figure 1. Load configurations used during experimental trials (top) and computer simulations (bottom).
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Run-to-Stop Knee Contact Forces Figure 2. Mean normalized knee joint contact forces across three different loads during the single limb support phase of the run-to-stop. Shaded regions represent standard deviations. Figure 3. Mean vertical (A) and anterior-posterior (B) ground reaction forces across three different loads during the single limb support phase of the run-to-stop. Shaded regions represent standard deviations.
Appendix: Table A.1: Retro-reflective marker (~ 14 mm) placement. Segment
Markers
Pelvis:
7th cervical vertebrae, acromion processes (bilateral), sternoclavicular notch, xiphoid process (virtual marker), 10th thoracic vertebrae (virtual marker) posterior superior iliac spine, anterior superior iliac spine, superior iliac crest
Thigh:
greater trochanter, medial and lateral femoral epicondyles, anterior thigh
Shank:
tibial tuberosity, lateral fibia, distal tibia
Foot:
medial and lateral malleoli, calcaneus, middle cuneiform, second and fifth metatarsal heads
Trunk:
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