The effects of load carriage on joint work at different running velocities
Introduction
Load carriage has been investigated in occupational, ergonomic, injury and performance settings (Knapik et al., 2004), with current research focused on the effects of load magnitude on the biomechanical and metabolic demands while walking (Huang and Kuo, 2014). However, recent studies have investigated load carriage during running, jump-landing, and side-step cutting tasks, which highlights the growing importance of research into more dynamic tasks during load carriage (Brown et al., 2014a, Brown et al., 2014b, Brown et al., 2016). Running with load is not only relevant to military personnel (Brown et al., 2014b), but also to non-military personnel as an increasing number of people are commuting to work on foot (Zander et al., 2014), and participating in ultra-endurance races (Hoffman and Wegelin, 2009). All of these pursuits routinely require load carriage running (Marais and de Speville, 2004). With the growing prevalence of load carriage running as an activity, more research into the biomechanics of loaded running is needed (Brown et al., 2014b, Silder et al., 2015). This knowledge is essential for the future development of pre-conditioning programs for individuals needing to run with load.
An important area of research in many biomechanical studies is quantifying and explaining the “source” of mechanical work (or its time derivative: power) (Aleshinsky, 1986) and its alterations during load carriage (Brown et al., 2014b, Huang and Kuo, 2014). For example, the increased metabolic cost of walking during load carriage (Huang and Kuo, 2014), has been attributed to an increased ankle positive work during push-off (Huang and Kuo, 2014). Although an increase in metabolic cost during load carriage was observed in running (Teunissen et al., 2007), a recent investigation reported that the percentage average positive power of the hip, knee, and ankle joints during the stance phase of running did not alter with load carriage (Brown et al., 2014b). Differences in the effects of load on joint work between walking and running could be due to inherent differences in joint-level work distribution between varied gait patterns (Farris and Sawicki, 2012, Schache et al., 2015). In addition, a lack of change observed in the study could be that analysis was performed only on relative joint average power contributions, with no absolute metrics being reported (Brown et al., 2014b). Relative joint power provides no indication of the absolute effect of load carriage on joint work in running.
When load is added, greater mechanical work is performed to sustain gait velocity (Huang and Kuo, 2014). The increase in mechanical work with added load in running was only investigated in the stance phase of running (Brown et al., 2014b). Previous research into unloaded running (running with no external load) at 3.0 to 4.0 m/s reported that leg swing contributed only 7% of the net metabolic cost of unloaded running (Arellano and Kram, 2014). This dominant stance phase effect of load carriage on joint work was also demonstrated in walking (Huang and Kuo, 2014). Greater mechanical work during load carriage running may involve an increase in joint work magnitude in all three joints, and/or inter-joint work redistribution (Farris and Sawicki, 2012). The effect of load on running joint work may also differ depending on running velocity, which is an important but yet poorly investigated area, given that load running may occur at varying velocities (e.g. 3.0 m/s to 5.0 m/s is common in ultramarathon runners) (Senefeld et al., 2015).
To this end, no studies have adequately investigated the joint-level mechanical work involved in load carriage running at varying velocities. Hence, the primary aim of this study was to determine the effect of load magnitude on lower limb joint work across three running velocities. It was hypothesized that across the range of velocities, total joint work would increase with load magnitude and that individual joint contributions to total work would also increase with load.
Section snippets
Participants
Thirty-one healthy participants (16 males and 15 females) enrolled in this study [mean standard deviation (sd) age=30.8 (5.9) years old; height=1.70 (0.08) m; mass=66.4 (10.8) kg; hours run per week=3.73 (2.86) hrs. All participants provided written informed consent prior to participation and the study was approved by the Curtin University Human Research Ethics Committee (RD-41-14) prior to commencement.
Biomechanical model
Anatomical markers were taped to the following anatomical landmarks: bilateral first and
Spatio-temporal parameters
Stride duration (i.e. time between right to right initial contact) was significantly related to velocity (t(245)=−14.22, P<0.001) and load (t(245)=−9.03, P<0.001) (Table 1). The effect of load magnitude on stance duration was dependent on running velocity (βLoad:Speed: t(245)=−4.03, P<0.001). Increasing load increased stance duration but this increase was attenuated by increasing velocity. Increasing load increased step length (βLoad:Speed: t(245)=−4.99, P<0.001) and stride length (βLoad:Speed:
Discussion
This present investigation evaluated the effects of varying load magnitude on absolute joint work while running across three velocities. The main hypothesis of this study was supported in that load carriage running required greater total joint work, compared to unloaded running. The secondary hypothesis was not supported in that load carriage did not increase the magnitude of positive and negative work at all three joints.
This study provides the first evidence that running with load carriage
Conclusion
Carrying load while running increased the magnitude of all three lower limb joints’ negative work, while it only increased positive work at the ankle and knee joint. This study also found that inter-joint work redistribution played a less significant role compared to global alterations in all joints’ work magnitudes, during the stance phase of load carriage running, when carrying loads of up to 20% BW. The ankle joint contributed to the greatest role in work production, whilst the knee
Conflicts of interest statement and source of funding
No funds were received in support of this work. No benefits in any form have been or will be received from a commercial party related directly or indirectly to the subject of this manuscript. Mr Bernard Liew is currently under a postgraduate scholarship “Curtin Strategic International Research Scholarship (CSIRS)”.
Acknowledgement
The authors would like to acknowledge Scott W. Selbie of C-Motion, Inc., who provided support for the use of Visual 3D software programming and clarification of biomechanical concepts used for this work.
References (35)
An energy ׳sources׳ and ׳fractions׳ approach to the mechanical energy expenditure problem--I. Basic concepts, description of the model, analysis of a one-link system movement
J. Biomech.
(1986)- et al.
Prediction of hip joint centre location from external landmarks
Hum. Mov. Sci.
(1989) - et al.
Soldier-relevant loads impact lower limb biomechanics during anticipated and unanticipated single-leg cutting movements
J. Biomech.
(2014) - et al.
Lower limb flexion posture relates to energy absorption during drop landings with soldier-relevant body borne loads
Appl. Ergon.
(2016) - et al.
Body borne loads impact walk-to-run and running biomechanics
Gait Posture
(2014) - et al.
Musculoskeletal stiffness changes linearly in response to increasing load during walking gait
J. Biomech.
(2015) - et al.
Bone position estimation from skin marker co-ordinates using global optimisation with joint constraints
J. Biomech.
(1999) - et al.
Can the reliability of three-dimensional running kinematics be improved using functional joint methodology?
Gait Posture
(2010) - et al.
Running with a load increases leg stiffness
J. Biomech.
(2015) - et al.
A model for the calculation of mechanical power during distance running
J. Biomech.
(1983)