вход по аккаунту



код для вставкиСкачать
Accepted Manuscript
Dual-Task and anticipation impact lower limb biomechanics during a single-leg
cut with body borne load
Kayla D. Seymore, Sarah E. Cameron, Jonathan T. Kaplan, John W. Ramsay,
Tyler N. Brown
BM 8422
To appear in:
Journal of Biomechanics
Accepted Date:
15 October 2017
Please cite this article as: K.D. Seymore, S.E. Cameron, J.T. Kaplan, J.W. Ramsay, T.N. Brown, Dual-Task and
anticipation impact lower limb biomechanics during a single-leg cut with body borne load, Journal of
Biomechanics (2017), doi:
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 proof before it is published in its final 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.
Dual-Task and anticipation impact lower limb biomechanics during a single-leg
cut with body borne load
Kayla D. Seymore1, Sarah E. Cameron2, Jonathan T. Kaplan2, John W. Ramsay2, Tyler N.
Boise State University, Boise, ID, USA
U.S. Army Natick Soldier Research Development and Engineering Center, Natick, MA, USA
Oak Ridge Institute for Science and Education (ORISE), Belcamp, MD, USA
Address for correspondence:
Kayla D. Seymore, MS
Center for Orthopaedic & Biomechanics Research
Boise State University
1910 University Drive
Boise, Idaho 83725
Phone: 1-208-426-5614
Keywords: kinematics, kinetics, decision-making, attention, load carriage
Word count: 3496
This study quantified how a dual cognitive task impacts lower limb biomechanics during
anticipated and unanticipated single-leg cuts with body borne load. Twenty-four males
performed anticipated and unanticipated cuts with and without a dual cognitive task with three
load conditions: no load (~6kg), medium load (15% of BW), and heavy load (30% of BW).
Lower limb biomechanics were submitted to a repeated measures linear mixed model to test the
main and interaction effects of load, anticipation, and dual task. With body borne load,
participants increased peak stance (PS) hip flexion (p = 0.004) and hip internal rotation (p =
0.001) angle, and PS hip flexion (p = 0.001) and internal rotation (p = 0.018), and knee flexion (p
= 0.016) and abduction (p = 0.001) moments. With the dual task, participants decreased PS knee
flexion angle (p < 0.001) and hip flexion moment (p = 0.027), and increased PS knee external
rotation angle (p = 0.034). During the unanticipated cut, participants increased PS hip (p = 0.040)
and knee flexion angle (p < 0.001), and decreased PS hip adduction (p = 0.001), and knee
abduction (p = 0.005) and external rotation (p = 0.026) moments. Adding body borne load
produces lower limb biomechanical adaptations thought to increase risk of musculoskeletal
injury, but neither anticipation nor dual task exaggerated those biomechanical adaptations. With
a dual task, participants adopted biomechanics known to increase injury risk; whereas,
participants used lower limb biomechanics thought to decrease injury risk during unanticipated
Musculoskeletal injuries commonly occur during military activities, affecting more than
600,000 soldiers each year (Army Medical Surveillance Activity, 2006). Over three quarters of
these musculoskeletal injuries are sustained in the lower extremity (Almeida et al., 1999),
producing damage to soft-tissue structures (Kaufman et al., 2000). These lower limb injuries
routinely occur during landing and pivoting maneuvers that require a quick, dynamic change of
speed and/or direction (Olsen et al., 2004). Dynamic movements that require a vigorous or
forceful maneuver, such as the single-leg cut, are common military activities (Johnson, 2003).
For a soldier to safely and successfully perform these vigorous maneuvers their musculoskeletal
system must adequately support the weight of their body (Miller et al., 2012), as well as body
borne load (including body armor, weapon systems, and rucksacks). During military activities,
soldiers routinely carry body borne loads that exceed 30% of their body weight (BW) (Task
Force Devil Combined Arms Assessment Team, 2003). The load increases their risk of
musculoskeletal injury (Knapik et al., 2011) and reduces their physical ability (Harman et al.,
2008) to perform routine tasks. This increased injury risk and reduced physical ability is
attributed to the adaptation in the lower limb biomechanics that soldiers exhibit when performing
military activities with body borne load (Patton et al., 1991).
Single-leg cutting is a dynamic maneuver that requires a forceful change of direction.
When performing a single-leg cut, participants increase knee joint motions (McLean et al.,1998),
and frontal and transverse plane knee joint loads (Besier et al., 2001) compared to running,
particularly with the addition of body borne load (Brown et al., 2014). Brown et al. (2014)
reported soldiers exhibit biomechanical patterns, including larger moments and reduced flexion
of the lower limb, that limit their ability to perform a single-leg cut with body borne load. The
performance of an unanticipated single-leg cut has been reported to produce alterations in lower
limb biomechanics, including reduced hip flexion angle (Brown et al., 2009), and larger frontal
plane hip and knee motions and loads (Besier et al., 2001; Borotikar et al., 2008), compared to an
anticipated cut. These adaptations are thought to be a hazardous biomechanical response (Besier
et al., 2003), increasing strain on the musculoskeletal system (Borotikar et al., 2008). Soldiers,
however, did not exhibit the expected hip and knee biomechanical adaptations when performing
an unanticipated single-leg cut with heavy body borne loads (Brown et al. 2014). It is unknown if
soldiers similarly mitigate musculoskeletal injury risk during loaded single-leg cuts typical of
military activity.
During military activities, soldiers simultaneously execute physical and cognitive tasks.
Yet, performing a dual task (combined physical and cognitive) divides an individual’s attention,
leading to negative performance of either task (Lin and Lin, 2016; Navon and Miller, 1987)
during activities involving gait (Al-Yahya et al., 2009), gait initiation (Nocera et al., 2013) and
stair negotiation (Vallabhajosula et al., 2015). During gait, a dual cognitive task, such as serial
subtraction, increases stance time, and decreases step length and walking velocity which may
reduce a participant’s physical ability (Al-Yahya et al., 2009; Lin and Lin, 2016). Considering
soldiers simultaneously perform physical and cognitive tasks during military activities, it is
crucial to understand how adding a dual cognitive load impacts their performance and injury risk
during routine activities, such as single-leg cutting. When a soldier’s attention is compromised,
they may exhibit significant adaptations of lower limb biomechanics, including larger frontal
plane motions and loads, known to reduce performance and increase injury risk. It may be these
biomechanical adaptations are further exacerbated by the addition of body borne load. However,
to date, the impact of a cognitive task on the lower-limb biomechanics exhibited during single-
leg cutting is unknown. The purpose of this study was to quantify how a dual cognitive task
impacts the lower body biomechanics exhibited when performing anticipated and unanticipated
single-leg cuts with body borne load. We hypothesized that body borne load would increase
lower limb joint moments and decrease lower limb flexion angle during the single-leg cut, and
these adaptations would significantly increase with the addition of a cognitive task. Further, we
hypothesized no significant reduction in flexion angle or increase in hip and knee joint moments
would be evident during the unanticipated compared to anticipated cuts, even when performing
the unanticipated cut with a dual cognitive task.
Twenty-four male active-duty military personnel (20.2 ± 3 yrs, 1.8 ± 0.1 m, 80.3 ± 11.1
kg) participated. An a priori power analysis of frontal plane lower limb kinematics exhibited
during previous loaded single-leg cuts indicated that 20 participants were needed to achieve 80%
statistical power with alpha 0.05 (Brown et al., 2014). Potential participants who reported current
pain or recent injury to the back or lower extremity (previous 6 months), history of back or lower
extremity injury or surgery, and/or any known neurological disorder were excluded. Prior to
testing, all participants gave written consent and research approval was obtained from the local
institutional review board.
Participants performed three test sessions. For each session, participants wore a different
body borne load condition: no load (NL), medium load (ML, 15% of BW), and heavy load (HL,
30% of BW). The NL condition required each participant wear common combat equipment,
including ACH helmet, personal combat boots, and mock M16 weapon, with a total weight of ~6
kg. The ML and HL conditions required participants wear a weighted vest (V-Force®, Inc. Rexburg, ID, USA), in addition to combat equipment, that was
systematically adjusted to have the total load (vest plus combat equipment) equal either: 15 %
(ML) or 30 % (HL) of the participant’s BW (Fig. 1). Each participant was randomly assigned a
testing sequence from a 3 x 3 Latin Square prior to testing.
During testing, participants had three-dimensional (3D) lower limb biomechanics
recorded during a series of single-leg cutting tasks. During each cut, a force platform (AMTI
Optima, Advanced Mechanical Technology Inc., Watertown, MA) recorded ground reaction
force (GRF) data (2400Hz) and twelve high-speed (240fps) optical cameras (Oqus, Qualisys AB,
Gothenburg, Sweden) recorded motion data. The single-leg cut task required the participant run
at 4.0 m/s down a 10 m walkway and respond to an external light stimulus. The light stimulus
randomly presented two pre-defined movements: either L1 or L2. Stimulus L1 required
participants planted their dominant limb on the force platform, and cut at 45° to their nondominant side, while stimulus L2 required participants continue running 4.0 m/s through the
capture volume. During all trials, run speed was recorded with two sets of infrared photocell
timing lights (Brower Timing, Draper, UT, USA) placed on the walkway prior to the force
platform. To prevent running speed from confounding the analysis, a trial was considered
successful if the participant ran within ± 5% of the target speed and did not alter their stride to
contact the force platform with their dominant limb. Prior to testing, all participants familiarized
themselves with the cutting maneuver until they could confidently execute. During testing,
participants were provided ample rest and water to minimize fatigue. Each participant selfreported their dominant limb prior to testing, as the leg they could kick a ball the farthest. Only
the single-leg cut (L1) were analyzed for this study.
Each cut was defined as either anticipated (AN) or unanticipated (UN), according to Brown et al.
(2014). The AN cuts required participants respond to the light stimulus presented prior to
initiating the trial, while UN cuts required participants responded to the light stimulus presented
during the trial approximately 500 ms prior to contact with the force platform. Each single-leg
cut was also performed with (DT) or without (Cut) an additional cognitive task. The cognitive
task required participants perform a serial subtraction task during each cutting trial (Al-Yahya et
al., 2009). Specifically, this required participants verbally subtract by three from a random
number announced to them at the beginning of each cutting trial. Participants were not given
instructions on which task to prioritize. The testing order of both anticipation and dual task were
randomized prior to testing. Participants performed single-leg cutting for the first condition (e.g.,
DT AN), before switching anticipation (e.g, DT UN) and then task (e.g., Cut AN and UN).
Participants continued cutting until three successful trials were recorded for every condition.
Biomechanical Analysis
Joint kinematics were quantified from the 3D coordinates of thirty-six (14 mm diameter)
reflective markers. After marker placement, participants stood in a stationary (neutral) position
for a video recording used to create a kinematic model in Visual 3D (v5.00, C-Motion,
Rockville, MD). The kinematic model had seven skeletal segments (bilateral foot, shank and
thigh, and pelvis). The pelvis segment was defined with respect to the global (laboratory)
coordinate system and assigned six (three translational and three rotational) degrees of freedom.
Knee and ankle joint centers and local (three degrees of freedom) coordinate systems were
calculated in accordance with previous literature by Visual 3D (Grood and Suntay, 1983; Wu et
al., 2002). Functional hip joint center was calculated from a method adapted from Schwartz and
Rozumalski (2005) and assigned a local coordinate system. For each trial, synchronous GRF data
and marker trajectories were low pass filtered with a fourth-order Butterworth filter (12 Hz).
Then Visual 3D processed the marker trajectories to solve for the hip and knee joint rotations at
each time frame and expressed the rotations relative to the stationary position.
Joint moments were quantified from the filtered kinematic and GRF data using traditional
inverse dynamics analysis (Winter, 2005). For the analysis, segmental inertial properties were
defined per Dempster et al. (1959). Resultant moments at the hip and knee were defined as
flexion-extension, abduction-adduction, and internal-external rotation. Each joint moment was
normalized to the product of body mass (kg) and height (m), and expressed as an external
moment. Biomechanical data were time normalized to stance phase (heel strike to toe off) and
resampled to 1 % increments (N = 101). Stance phase was defined the instant GRF first exceeded
(heel strike) and fell below 10 N (toe off), according to our previous work (Brown et al., 2014).
Statistical Analysis
Hip and knee biomechanical parameters were submitted to statistical treatment.
Kinematic variables include peak of stance (PS, 0% - 100%) hip and knee flexion, hip adduction
and internal rotation, knee abduction and external rotation joint angles. Kinetic dependent
variables include PS external hip and knee flexion, hip adduction and internal rotation, and knee
abduction and external rotation joint moments. Subject-based mean was quantified for each
dependent measure. Then, submitted to a repeated measures linear mixed model with body borne
load (NL, ML, HL), anticipation (AN and UN), and dual task (Cut and DT) as fixed effects and
subject identity as random effects. To reduce the probability of committing type I error, a
Bonferroni correction was used for post-hoc comparisons between statistically significant
differences between body borne load configurations (NL, ML and HL). Statistical analyses were
performed using SPSS v22 software (IBM, Armonk, NY, USA). Alpha level was set a priori at P
< 0.05.
No significant interactions were observed. Thus, only the main effects are presented.
Body borne load had a significant effect on hip angle (Fig. 2 and Table 1). Body borne load
increased PS hip flexion (p=0.004) and hip internal rotation (p=0.001) angles. With the HL,
participants significantly increased PS hip internal rotation (p=0.038) angles compared to NL
condition, and PS hip flexion (p=0.003) angle compared to the ML. Post-hoc analysis revealed
no significant difference in PS hip flexion with the HL (p=0.314) or ML (p=0.818) compared to
NL. For PS hip internal rotation, there were no differences between HL and ML, and ML and NL
conditions. No significant effect of body borne load (p>0.05) was observed for PS knee flexion,
abduction, or external rotation.
Hip and knee joint moments increased with body borne load (Figs. 2 and 3, and Table 2).
Body borne load had a significant effect on PS hip flexion (p=0.001) and internal rotation
(p=0.018), and knee flexion (p=0.016) and abduction (p=0.001) moments. With the HL,
participants significantly increased PS hip flexion (p=0.002) and internal rotation (p=0.019), and
knee flexion (p=0.023) and abduction (p=0.001) moments compared to the NL condition, and PS
hip flexion moment (p=0.006) compared to ML. No significant differences (p>0.05) between the
NL and ML conditions were evident for any PS hip or knee moments, or between ML and HL
for PS hip internal rotation, and knee flexion and abduction moments. No significant effect of
body borne load (p>0.05) on PS hip adduction or knee external rotation moments was evident.
The dual task had a significant effect on knee angle and hip moments during the singleleg cut (Table 1 and 2). Participants exhibited a significant decrease in PS knee flexion angle
(p<0.001) and hip flexion moment (p=0.027), and significant increase PS knee external rotation
angle (p=0.034) with the addition of a dual task during the single-leg cut. No significant effect of
dual task (p>0.05) was evident for PS hip flexion, adduction and internal rotation, and knee
abduction angles, or hip adduction and internal rotation, and knee flexion, abduction and external
rotation joint moments.
Anticipation had a significant effect on hip and knee joint angle and moments (Table 1
and 2). During the UN cuts, participants significantly increased PS hip (p=0.040) and knee
flexion (p<0.001) angle, and significantly decreased PS hip adduction (p=0.001), knee abduction
(p=0.005) and external rotation (p=0.026) moments compared to the AN cuts. No significant
effect of anticipation (p>0.05) was evident for PS hip adduction and internal rotation, knee
abduction and external rotation angles or hip flexion and internal rotation, and knee flexion
This study was the first to quantify how a dual cognitive task impacts the lower limb
biomechanics for a soldier performing anticipated and unanticipated single-leg cuts with body
borne load. Soldiers routinely execute simultaneous dual physical and cognitive tasks as part of
their military duties. The simultaneous performance of these tasks divides an individual’s
attention (Navon and Miller, 1987), producing adaptations in lower limb biomechanics known to
impair healthy adults’ physical ability (Al-Yahya et al., 2009; Lin and Lin, 2016). Yet, contrary
to our hypothesis, participants did not further increase the lower limb biomechanical adaptations
that result from body borne load with the addition of a dual task.
With body borne load, participants exhibited lower limb biomechanical patterns that may
limit their physical ability and increase their risk of musculoskeletal injury. In agreement with
previous research, the current participants adopted larger hip and knee sagittal plane joint
moments to maintain stability during the single-leg cut with body borne load (Brown et al.,
2014). The current participants exhibited a significant increase in peak hip (21%) and knee
flexion (7%) moments with the HL, and peak hip flexion (15%) moment with the ML compared
to the NL condition. These elevated joint moments may provide the lower limb stability and
counteract the 5% to 10% increase in vertical GRF commonly evident during load carriage
(Brown et al., 2016; Silder et al, 2015). Additionally, to maintain lower limb stability,
participants adopted greater hip flexion angle with the HL condition. The flexed hip may
counteract the forward shift in center of mass during body borne load carriage (Muslim and
Nussbaum, 2016) and aid with the attenuation of elevated GRFs and joint moments (Brown et
al., 2016) during the single leg cut. These sagittal plane adaptations may hinder soldiers by
decreasing their speed and ability to perform a quick change of direction, such as the chosen
cutting task (Brown et al., 2014; Havens and Sigward, 2015). Additionally, the out of plane
biomechanical adaptations exhibited during the loaded cuts may further increase the soldier’s
risk of suffering a musculoskeletal injury (Borotikar et al., 2008).
During the single-leg cut, participants exhibited larger hip internal rotation angle and
moment, and larger knee abduction moment with the addition of body borne load. These frontal
and transverse plane adaptations may put soldiers at higher risk for knee injury (McLean et al.,
2004), as both excessive hip internal rotation and knee abduction moments are implicated in
ACL injury (Hewett et al., 2005; Hewett et al., 2006). However, contrary to our hypothesis and
existing literature, participants did not adopt explicit knee angles thought to increase risk of
injury during the single-leg cut. Participants reportedly exhibit frontal and transverse plane knee
joint rotations linked with potential injury risk during unloaded cutting (Besier et al., 2001;
McLean et al., 1998) and reduce peak knee flexion angle when cutting with heavy (40 kg) body
borne loads (Brown et al., 2014). But, with the chosen ML (12.0 ± 1.7 kg) and HL (24.1 ± 3.3
kg) load conditions, the current participants did not exhibit a substantial alteration in knee joint
angle. The reason for the current discrepancy is not immediately evident, but it is plausible
soldiers placed their attention on attenuating impact force, rather than forcefully performing the
single-leg cut with the chosen loads. Nonetheless, these loads may not be heavy enough to
require a soldier to reduce knee flexion to prevent collapse of the lower limb and successfully
complete the maneuver, as previously reported (Brown et al. 2014).
The addition of dual cognitive task increases attentional demand (Navon and Miller, 1987)
manifesting in biomechanical adaptations, such as increased stance time, disrupted lower limb
coordination, and reduced walking velocity. Therefore, we hypothesized the additional dual task
would exaggerate the aforementioned biomechanical alterations evident during the single-leg cut
with body borne load. The present outcomes, however, do not support this hypothesis. The
simultaneous performance of the physical and cognitive tasks may require our participants to
prioritize successful completion of the single leg cut over the speed or accuracy of a cognitive
task (Cho et al., 2008; Tavakoli et al., 2016). This limitation may explain why no significant
interaction between body borne load and dual task was currently observed, but direct comparison
with existing dual task research may be obfuscated as it primarily analyzed steady-state walking
(Al-Yahya et al., 2009; Lin and Lin, 2016). Still, significant changes in lower limb biomechanics
were apparent during the dual task cuts. During the dual task cuts, participants exhibited a
significant reduction in knee flexion angle and hip flexion moment, and increased knee external
rotation angle. Adopting an extended knee may aid with joint stabilization (McNitt-Gray, 1991),
but reduces the lower limb musculature’s ability to absorb the impact force produced during
weight acceptance of stance (Brown et al., 2016). Further, the extended knee could potentially
increase compressive load being transmitted across the joint (Ramsay et al., 2016), and when
coupled with the currently observed knee axial rotation, may significantly increase risk of injury
(Markolf et al., 1993). Future work is warranted to determine how a dual cognitive task impacts
the allocation of soldiers’ attention and translates to their performance during military activities.
Limiting preparation time can also affect the performance of motor skills (Los and Schut,
2008), such as a single-leg cut (Brown et al., 2009). Performing an unanticipated single-leg cut
reportedly produces frontal plane hip and knee angles and loads thought to increase injury risk
(Besier et al., 2001; Borotikar et al., 2008). Yet, in contradiction to existing literature, the current
participants adopted lower limb biomechanics that may reduce injury risk during unanticipated
cutting. During the unanticipated cut, participants increased hip and knee flexion angle, and
decreased hip adduction angle, and knee abduction and external rotation moments compared to
the anticipated cut. Increasing lower limb flexion angle, and decreasing frontal plane hip and
knee angles and loads may reduce strain on the ACL and decrease the likelihood of suffering an
injury during an unanticipated movement (Cochrane et al., 2010). While it is not immediately
evident why the current participants adopted lower limb biomechanics thought to reduce injury
risk during the unanticipated cuts, it may be the study is limited by the temporal constraint
chosen for the unanticipated cuts (500 ms). Although, the temporal constraint has previously
produced adaptations of lower limb biomechanics during unanticipated single-leg cutting (Brown
et al., 2009), it is possible that the stimulus time may have afforded the participants sufficient
time to plan a movement strategy and reduce injury risk during cutting with body borne load.
Future work is warranted to determine whether reacting to shorter stimulus times are, indeed,
possible with body borne load and whether they are detrimental to lower limb biomechanics
during dynamic military tasks.
Adding body borne load increased participants’ hip and knee joint moments and altered hip
angles; biomechanical adaptations that may increase risk of musculoskeletal injury and limit
their physical ability during military activities. Yet, neither adding anticipation nor a dual task
exaggerated the biomechanical adaptations exhibited during loaded cutting. When attention was
compromised with a cognitive task, participants adopted an extended and externally rotated knee
that may reduce their performance and increase their injury risk. Conversely, participants
increased lower limb flexion, and reduced hip and knee frontal plane moments, biomechanical
patterns thought to decrease injury risk during unanticipated cutting. Providing soldiers the
ability to focus on a physical task may increase their performance and decrease their risk of
musculoskeletal injury during military activities.
Conflict of Interest
The authors have declared that no conflict of interest exists.
This research was supported in part by an appointment by the Postgraduate Research
Participation Program at the U.S. Army Natick Soldier Research, Development and Engineering
Center administered by the Oak Ridge Institute for Science and Education through an
interagency agreement between the U.S. Department of Energy and NSRDEC.
Almeida, S.A., Williams, K.M., Shaffer, R.A., Brodine, S.K., 1999. Epidemiological patterns of
musculoskeletal injuries and physical training. Med. Sci. Sports Exerc. 31, 1176–1182.
Al-Yahya, E., Dawes, H., Collett, J., Howells, K., Izadi, H., Wade, D. T., et al., 2009. Gait
adaptations to simultaneous cognitive and mechanical constraints. Exp. Brain Res. 199,
Army Medical Surveillance Activity, 2006. Estimates of absolute and relative health care
burdens attributable to various illnesses and injuries, U.S. Armed Forces, 2005. edited by
Besier, T.F., Lloyd, D.G., Ackland, T.R., 2003. Muscle activation strategies at the knee during
running and cutting maneuvers. Med. Sci. Sports Exerc. 35, 119–127.
Besier, T.F., Lloyd, D.G., Cochrane, J.L., Ackland, T.R., 2001. External loading of the knee joint
during running and cutting maneuvers. Med. Sci. Sports Exerc. 33, 1168–1175.
Borotikar, B.S., Newcomer, R., Koppes, R., McLean, S.G., 2008. Combined effects of fatigue
and decision making on female lower limb landing postures: central and peripheral
contributions to ACL injury risk. Clin. Biomech. 23, 81–92.
Brown, T.N., O'Donovan, M., Hasselquist, L., Corner, B., Schiffman, J.M., 2014. Soldierrelevant loads impact lower limb biomechanics during anticipated and unanticipated
single-leg cutting movements. J. Biomech. 47, 3494–3501.
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. Appl. Ergon. 52, 54–61.
Brown, T.N., Palmieri-Smith, R.M., McLean, S.G., 2009. Sex and limb differences in hip and
knee kinematics and kinetics during anticipated and unanticipated jump landings:
implications for anterior cruciate ligament injury. Br. J. Sports Med. 43, 1049–1056.
Cho, C.Y., Gilchrist, L., White, S., 2008. A Comparison between young and old adults in their
ability to rapidly sidestep during gait when attention is divided. Gerontology 54, 120–
Cochrane, J.L., Lloyd, D.G., Besier, T.F., Elliott, B.C., Doyle, T.L., Ackland, T.R., 2010.
Training affects knee kinematics and kinetics in cutting maneuvers in sport. 42, 15351544.
Dempster, W.T., Gabel, W.C., Felts, W.J., 1959. The anthropometry of the manual workspace
for the seated subject. Am. J. Phys. Anthropol. 17, 289–317.
Grood, E.S., Suntay, W.J., 1983. A joint coordinate system for the clinical description of threedimensional motions: application to the knee. J. Biomech. Eng. 105, 136–144.
Harman, E.A., Gutekunst, D.J., Frykman, P.N., Nindl, B.C., Alemany, J.A., Mello, R.P., Sharp,
M.A., 2008. Effects of two different eight-week training programs on military physical
performance. J. Strength Cond. Res. 22, 524–534.
Havens, K.L., Sigward, S.M., 2015. Joint and segmental mechanics differ between cutting
maneuvers in skilled athletes. Gait Posture. 41, 33–38.
Hewett, T.E., Ford, K.R., Myer, G.D., Wanstrath, K., Scheper, M., 2006. Gender differences in
hip adduction motion and torque during a single-leg agility maneuver. J. Orthop. Res. 24,
Hewett, T.E., Myer, G.D., Ford, K.R., et al., 2005. Biomechanical measures of neuromuscular
control and valgus loading of the knee predict anterior cruciate ligament injury risk in
female athletes: a prospective study. Am. J. Sports Med. 33, 492–501.
Johnson, K.J., 2003. Tears of cruciate ligaments of the knee: US armed Forces: 1990e2002. Med.
Surveill. Mon. Rep. 9, 2–6.
Knapik, J.J., Hauret, K.G., Canada, S., Marin, R., Jones, B., 2011. Association Between
Ambulatory Physical Activity and Injuries During United States Army Basic Combat
Training. J. Phys. Act. Health. 8, 496–502.
Kaufman, K.R., Brodine, S., Shaffer, R., 2000. Military training-related injuries - surveillance,
research, and prevention. Am. J. Prev. Med. 18, 54–63.
Lin, M.I., Lin, K.H., 2016. Walking while performing working memory tasks changes the
prefrontal cortex hemodynamic activations and gait kinematics. Front Behav. Neurosci.
10, 1–15.
Los, S. A., Schut, M.L., 2008. The effective time course of preparation. Cogn. Psychol. 57, 20–
Markolf, K.L., Wascher, D.C., Finerman, G.A., 1993. Direct in vitro measurement of forces in
the cruciate ligaments. Part II: the effect of section of the posterolateral structures. J Bone
Joint Surg Am. 75, 387–394.
McLean, S.G., Huang, X., Su, A., Van Den Bogert, A.J., 2004. Sagittal plane biomechanics
cannot injure the ACL during sidestep cutting. Clin. Biomech. 19, 828–838.
McLean, S.G., Myers, P.T., Neal, R.J., Walters, M.R., 1998. A quantitative analysis of knee joint
kinematics during the sidestep cutting maneuver. Implications for non-contact anterior
cruciate ligament injury. Bull. – Hosp. Joint Dis. 57, 30–38.
McNitt-Gray, J.L., 1991. Kinematics and impulse characteristics of drop landings from three
heights. Int. J. Sports Biomech. 7, 201–224.
Miller, R.H., Umberger, B.R., Caldwell, G.E., 2012. Sensitivity of maximum sprinting speed to
characteristic parameters of the muscle force–velocity relationship. J. Biomech. 45,
Muslim, K., Nussbaum, M.A., 2016. Traditional posterior load carriage: effects of load mass and
size on torso kinematics, kinetics, muscle activity and movement stability. Ergonomics
59, 99–111.
Navon, D., Miller, J., 1987. Role of outcome conflict in dual-task interference. J. Exp. Psychol.
Hum. Percept. Perform. 13, 435–448.
Nocera, J.R., Roemmich, R., Elrod, J., Altmann, L.J., Hass, C.J., 2013. Effects of cognitive task
on gait initiation in Parkinson disease: evidence of motor prioritization? J. Rehabil. Res.
Dev. 50, 699–708.
Olsen, O.E., Myklebust,G., Engebretsen, L., Bahr, R., 2004. Injury mechanisms for anterior
cruciate ligament injuries in team handball a systematic video analysis. Am. J. Sports
Med. 32, 1002–1012.
Patton, J.F., Kaszuba, J., Mello, R.P., Reynolds, K.L., 1991. Physiological responses to prolonged treadmill walking with external loads. Eur. J. Appl. Physiol. Occup. Physiol. 63,
Ramsay, J.W., Hancock, C.L., O'Donovan, M.P., Brown, T.N., 2016. Soldier-relevant body
borne loads increase knee joint contact force during a run-to-stop maneuver. J. Biomech.
49, 3868–3874.
Schwartz, M.H., Rozumalski, A., 2005. A new method for estimating joint parameters from
motion data. J. Biomech. 38, 107–116.
Silder, A., Besier, T., Delp, S.L., 2015. Running with a load increases leg stiffness. J. Biomech.
48, 1003–1008.
Tavakoli, S., Forghany, S., Nester, C., 2016. The effect of dual tasking on foot kinematics in
people with functional ankle instability. Gait Posture. 49, 364–370.
Task Force Devil Combined Arms Assessment Team, 2003. The modern warrior's combat load:
dismounted operations in Afghanistan (Draft 8-14-2003). U.S. Army Center for Army
Lessons Learned, Fort Leavenworth, KS, p.87.
Vallabhajosula, S., Tan, C.W., Mukherjee, M., Davidson, A.J., Stergiou N., 2015. Biomechanical
analyses of stairclimbing while dual-tasking. J. Biomech. 48, 921–929.
Winter, D.A., 2005. Biomechanics and Motor Control of Human Movement, 3 rd ed. John Wiley
& Sons, Hoboken, NJ.
Wu, G., Siegler, S., Allard, P., et al., 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. J. Biomech. 35, 543–548.
Figure 1: No (A), medium (B), and heavy (C) body borne load configurations.
Figure 2: Stance phase (0–100%) hip joint angles and moments for body borne load single-leg
cutting maneuvers.
Figure 3: Stance phase (0–100%) knee joint angles and moments for body borne load single-leg
cutting maneuvers.
Table 1: Mean (SEM) peak stance joint postures (°) during cutting maneuvers.
Hip Flexion (+) *†
Hip Adduction (+)
Hip Rotation (+) *
Knee Flexion (-)
Knee Adduction
Knee Rotation (-)
1.2 (1.2) 1.9 (1.2)
0.9 (1.2) 1.0 (1.4)
-1.9 (0.6) -1.9 (0.6)
-1.9 (0.6) -1.7 (0.7)
-6.1 (0.9) -5.9 (0.8)
-5.8 (0.9) -6.2 (0.9)
0.7 (1.2) -0.7 (1.2)
-0.1 (1.2) 0.7 (1.4)
-2.7 (0.6) -2.5 (0.6)
-2.6 (0.6) -2.1 (0.7)
-5.6 (0.8) -5.3 (0.9)
-5.9 (0.8) -6.8 (0.9)
* Denotes a significant effect (p < 0.05) of body borne load
# Denotes a significant effect (p < 0.05) of dual task
† Denotes a significant effect (p < 0.05) of anticipation
0.9 (1.2)
1.2 (1.3)
-2.7 (0.6)
-2.0 (0.7)
-5.8 (0.9)
-5.8 (0.9)
0.1 (1.2)
0.4 (1.5)
-1.9 (0.7)
-2.4 (0.8)
-6.0 (0.9)
-7.2 (1.0)
Table 2: Mean (SEM) peak stance joint moments (N·m/kg·m) during cutting maneuvers.
Hip Flexion (-)
Hip Adduction ()†
Hip Rotation (-)
Knee Flexion (+)
Knee Adduction
(+) *†
Knee Rotation
(+) †
* Denotes a significant effect (p < 0.05) of body borne load
# Denotes a significant effect (p < 0.05) of dual task
† Denotes a significant effect (p < 0.05) of anticipation
Без категории
Размер файла
902 Кб
2017, 021, jbiomech
Пожаловаться на содержимое документа