Paired nonlinear behavior of active and passive joint torques associated with preparation for walk-to-run gait transition
Introduction
Based on earlier studies, the mechanisms related to gait pattern changes from a walk-to-run gait transition (WR) were hypothesized as minimizing metabolic energy use (Cavagna et al., 1977, Hreljac, 1993a) as well as reducing muscle stress (Bartlett and Kram, 2008, Hreljac et al., 2001). Alternatively, patterns of lower extremity kinematic and kinetic variables could also be directly associated with WR. However, WR occurred as an instantaneous or self-reorganizational events remain unclear based on incremental protocol or continuous protocols (Farris and Sawicki, 2012a, Farris and Sawicki, 2012b, Hreljac, 1993b, Hreljac et al., 2007, Hreljac et al., 2008, Li and Hamill, 2002, Nimbarte and Li, 2011, Pires et al., 2014, Pires et al., 2018, Raynor et al., 2002, Zhang et al., 2018).
Evidence from incremental protocol supported that WR is a spontaneous event in response to external kinematic and kinetic triggers (Farris and Sawicki, 2012b, Hreljac et al., 2008, Pires et al., 2014, Pires et al., 2018; Raynor et al., 2002). Farris and Sawicki (2012b) reported that the medial gastrocnemius muscle fascicles shortening during the time of peak force production shifted to much slower velocities during WR at 2.0 m/s. Furthermore, it was also suggested that WR might display a relationship of the kinetic chain starting at the ankle, which leads to an unfavorable compensation at the hip (Hreljac et al., 2008, Pires et al., 2014). However, Hreljac et al. (1993b) failed to observe the kinetic factors triggering the WR. On the other hand, there was consistent evidence based on the continuous protocol to suggest that the gait transition is not a spontaneous event in response to any type of kinematic and kinetic triggers (Hreljac et al., 2007, Li and Hamill, 2002, Nimbarte and Li, 2011, Zhang et al., 2018). As walking speed increases, hip and ankle joint angular velocity of the last walking stride before WR resembled their patterns during running. Nonlinear quadratic trends of joint torque and power were observed within the last five strides before WR. This evidence suggested that gait transition is a reorganization process rather than a passive instantaneous reaction to a specific mechanical trigger (Hreljac et al., 2007, Zhang et al., 2018). Increased walking velocity served as a control parameter during WR, leading to the bifurcation of coordinative patterns between the different walk or run attractor states (Li and Ogden, 2012). Hence, the continuous protocol is often used to detect system behavior change during WR.
Joint torques have been used to estimate the primary joint flexor and extensor muscle groups' activity patterns with the strides leading up to WR based on a continuous protocol to provide information on the nonlinear relationship between lower extremity joint torques walking speed during WR (Zhang et al., 2018). This nonlinear tendency has been explained using joint torques generated by muscle contractions. However, several researchers suggested intersegmental dynamics would be better to describe the multi-joint locomotion mechanisms such as walking and running since the human body is configured as a kinematic chain (Kim and Kim, 2011, Smith and Zernicke, 1987, Winter, 1991). Generally, intersegmental dynamics represents both the active torques and the passive torques modulated by the body's interaction with the environment (Smith and Zernicke, 1987, Winter, 1991). The active torques are the generalized muscle torque (MST), where the passive torques are the gravitational (GTT), motion-dependent (MDT), and contact torque (EXT) (Sun et al., 2015). Intersegmental dynamical variables were deemed as neurological measures to present central nervous system control processes (Smith and Zernicke, 1987, Zernicke et al., 1991). They were identified as the appropriate approach to investigate the mechanism of locomotion and injury supported by previous researches related to walking and running (Hoy and Zernicke, 1985, Huang et al., 2013, Hunter et al., 2004, Smith et al., 2013a, Smith et al., 2013b, Sun et al., 2015, Zernicke et al., 1991). Previous WR studies only reported the net joint torque, the sum of all active and passive torque. Intersegmental dynamics could provide important insights into the mechanisms of WR.
This study aimed to understand the interactions of active and passive torques during WR at continuously increased walking speed. We hypothesized that partly active and passive torques represent increasing/decreasing at the last stride compared to the other four strides. It is also hypothesized that active and passive torques might present a similar tendency during the five steps leading up to WR.
Section snippets
Participants
The local ethical review board approved the project for human subjects. Eleven male and three female participants were recruited. Mean ± SD for age, body mass, and height were 22.6 ± 1.9 years old, 75.4 ± 12.8 kg, and 1.73 ± 0.08 m, respectively. The participants had to have no history of lower extremity injury, understood the potential risks, and had running experience on the treadmill to be included in this experiment. Participants were informed of the testing protocols and signed the consent
MANOVA results
No Left/Right by Strides interaction nor Left/Right main effect detected at any of the three joints. The MANOVA results revealed significant Strides effects on the outcome variables at the hip (F60, 201 = 3.519, p < .05; Wilk’s Λ = 0.061), knee (F76, 187 = 3.150, p < .05; Wilk’s Λ = 0.020), and ankle (F44, 212 = 5.774, p < .05; Wilk’s Λ = 0.049) joints. Specific significant differences in peak torques and time to corresponding peak torques are presented in Table 1, Table 2.
Hip joint
Post-hoc pairwise
Discussion
We investigated the changes of net joint torque (NET) and its synergy with its components (MST, GTT, MDT, and EXT) among the five strides leading up to walk-to-run gait transition (WR). We hypothesized that partly active and passive torques represent increasing/decreasing at the last stride compared to the other four strides. Twenty-three dependent variables of the last stride before WR were significantly different than the other four strides (Table 1, Table 2). We further hypothesized that
Conclusion
We observed nonlinear changes (quadratic trends) in peak magnitudes and relative timing of active and passive torques during steps leading up to WR through increased walking. Intersegment dynamics revealed additional details to the change of joint torques and the contributions of different components. Gait transition might occur at the stance phase of the last stride before gait transition. Active and passive torques can demonstrate the lower extremity kinetic chain's detailed features, which
Declaration of Competing Interest
This project was not funded. Therefore, the authors have no funding resources to disclose. The authors also declare they have no conflict-of-interest concerning this publication.
Jiahao Pan graduated with a master’s degree from the Key Laboratory of Exercise and Health Sciences of Ministry of Education, Shanghai University of Sport, Shanghai, 2000438, China. He is currently a doctoral student in the Center for Orthopaedic & Biomechanics Research, Boise State University, Boise, ID, 83725, USA
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Cited by (1)
Kinematic analysis of speed transitions within walking in younger and older adults
2022, Journal of BiomechanicsCitation Excerpt :Joint kinematic timing may be a contributor to changing walking speed. Indeed, the timing of peak joint angles, moments, and powers have been implicated in walk-to-run transitions (Diedrich and Warren, 1995; Pan et al., 2021; Seay et al., 2006), thus further analysis of joint work and electromyographic analysis of the lower limb muscles is necessary. We observed age differences in both NS and NF conditions.
Jiahao Pan graduated with a master’s degree from the Key Laboratory of Exercise and Health Sciences of Ministry of Education, Shanghai University of Sport, Shanghai, 2000438, China. He is currently a doctoral student in the Center for Orthopaedic & Biomechanics Research, Boise State University, Boise, ID, 83725, USA
Shuqi Zhang is a professor in the Center for Orthopaedic & Biomechanics Research, Boise State University, Boise, ID, 83725, USA
Li Li is a professor in the Department of Health Sciences and Kinesiology, Georgia Southern University, Statesboro, GA 30460, USA