Intralimb coordination following obstacle clearance during running: the effect of obstacle height

Abstract

The purpose of this study was to investigate the different coordination strategies used following obstacle clearance during running. Ten subjects ran over a level surface and over obstacles of six different heights (10, 12.5, 15, 17.5, 20 and 22.5% of their standing height). Analysis based upon the dynamical systems theory (DST) was used and the phasing relationships between lower extremity segments were examined. The results demonstrated that the increasing obstacle height elicited behavioral changes. The foot and the leg became more independent in their actions, while the leg and the thigh strengthened their already stable relationship. The 15% obstacle height seems to be a critical height for the observed changes.

Introduction

Running is a very popular form of recreation and exercise. It is also a very complex motor skill that involves numerous interacting components or degrees of freedom. Mastering these degrees of freedom can lead to a stable, coordinated and skillful movement. Thus, coordination can be defined as the process by which the degrees of freedom are organized in time and in sequence to produce a functional movement pattern [1], [2]. In motor control, stable coordination patterns are considered a fundamental feature of consistent, functional action [2], [3], [4], [5]. A contemporary approach to understand the construction of, and subsequent change in, patterns of coordination comes from the dynamical systems theory (DST). In DST, coordinated patterns are constructed out of the constraints applied to the neuromotor system. These constraints come from the organism (e.g. joint flexibility, perceptual abilities), the environment (e.g. running on flat versus uneven terrain), and the task (e.g. running at slow or fast speeds). The constraints effectively reduce the number of degrees of freedom and simplify the management of the neuromotor system. The motor output is shaped by the constraints applied to the system. This approach to movement coordination contrasts with theories that suggest that all the details of a movement's execution are specified a priori by an action plan in the central nervous system.

Essential for DST is the notion of stability, which refers to the behavioral state of a system. Under the DST, when a system is slightly perturbed, it will return spontaneously to a stable state. These stable states of movement systems are known as attractors. Attractors are preferred patterns and they represent stable areas of movement around which behavior tends to occur when a system is allowed to operate in its preferred manner [2], [3]. Examples of such movement patterns are walking, running, etc. If one tries to walk at an extremely slow pace, the movement is highly dis-coordinated and of poor efficiency, thus unstable. DST emphasizes the identification of variables that can help us investigate the dynamics of the attractors. These variables are the order parameter and the control parameter. The order parameter is observed over time to determine whether it demonstrates a stable pattern. If it does indeed show a stable pattern, an attractor can be identified [2], [3], [5]. Thus, order parameters are functionally specific and define the overall behavior of the system. They allow a coordinated movement pattern to be reproduced and distinguished from other patterns. In gait, the relative phase between segments of the same limb that describes intralimb coordination has been suggested [2], [3], [5] as a reasonable choice of an order parameter.

While order parameters are functionally-specific to a coordinated movement pattern, nonspecific control parameters change freely according to the characteristics of the situation or environment. Under research conditions, an experimenter systematically alters a control parameter to see its effect on the stability of the order parameter. This allows for the determination of attractor states for patterns of limb movement. Change from one attractor state to another occurs when a control parameter reaches a critical threshold. For example, the change from walking to running in every individual occurs when speed reaches a specific value [3].

The scalar changes of the control parameter are reflected upon the order parameter and reveal the dynamics of the attractor in terms of stability. An attractor's stability is defined as the dynamic property that describes the variability of the order parameter. The size of the stability of an attractor can be measured by the variance or standard deviation of the order parameter. Large variations are synonymous with decreased stability or lack of coordination which can eventually result in a change to a new attractor state. A classic example of this abrupt change from one attractor state to another comes from the work of Kelso [3]. The task was the alternate, yet simultaneous, flexion and extension of the forefinger on each hand. The task began with the forefingers pointing in the same direction. Thus, one finger was flexed while the other was extended. Under slow oscillation speeds, the fingers maintained this orientation, an out-of-phase relationship with respect to one another. Upon scaling up on the oscillation speed, however, a behavioral transition occurred such that both fingers flexed at the same time and then went into extension at the same time, an in-phase relationship. Just prior to the transition, greater instability was observed in the phasing relationship between the fingers.

In running, it is the coordination and phasing relationships between the actions of the lower extremity segments that produce movements such as flexion and extension. However, limited research exists in the running literature where coordination between the interacting segments has been examined, especially under varied conditions. An example of such varied conditions can be the presence of obstacles in the running path. Past studies have examined how humans safely walk over obstacles [6], [7], [8], [9], [10]. These researchers focused on mechanisms used to clear different obstacle heights and/or widths and also observed how vision can influence the locomotor act. Less attention has been given to obstacle clearance by other modes of locomotion, such as running [11].

Research [12], [13] in running has identified, that 90% of the population use a heel strike landing pattern during jogging. Bates et al. [12] observed that most runners during a jogging pace contact the surface on the lateral side of the heel. However, during sprinting many of the heel strike runners change to a forefoot strike [14], [15]. It is possible that this change may be a mechanism to decrease impact forces and increase mechanical efficiency [16]. Research on landing after vertical jumps has also identified a forefoot strike landing which was attributed to the increased impact with the ground [17], [18]. No attention has been directed toward the evaluation of the kinematics of the leading leg while running over high enough obstacles to cause a heel strike runner to land on the forefoot. The investigation of the lower extremity coordination during running over obstacles may enhance understanding of control of locomotion.

The purpose of this study was to investigate the different strategies used following obstacle clearance during running. To accomplish this purpose, the subjects ran over obstacles of various heights and the data evaluation was based upon the DST. Thus, the phasing relationships between the foot, the leg, and the thigh motions in the sagittal plane were examined.