Assessing the spatio-temporal aspects of the gait pattern is relevant to the evaluation of human motor performance. The gait characteristics may be derived objectively from spatial or temporal parameters such as gait velocity, step length, step time or double support time, but a summarization of time series may result in the loss of valuable information.
During a clinical examination of the gait, the lack of a steady rhythm in the gait pattern will draw the attention of the clinician. Such an observation will often be interpreted as a deficit in the motor planning or in the postural control of the patient. Accordingly, several studies have observed that evaluation of stride variability may be important when characterizing the gait pattern [1, 2].
Gait variability has been addressed using a variety of means and methods [2, 3]. The variability of the gait pattern, based on a discrete time series analysis of a large number of gait cycles, has been proven to be significant and may reveal information about the maturation of gait function in children . Additionally, more advanced statistics have been used to analyse gait variability, including linear techniques such as the autocorrelation function  and non-linear approaches [6, 7] such as approximate entropy , sample entropy, the maximum Lyapunov exponent  or the detrended fluctuation analysis . However, in a daily clinical context, the gait pattern is most often evaluated by less sophisticated methods.
Interpretation of variability
An emerging perspective indicates that variability may be used to characterize the level of motor performance . An increase in the stride-to-stride time variability has been associated with fall risk in the elderly . Additionally, challenging dual-task situations and physical impairment may result in greater gait variability [13, 14]. Gait variability is therefore often regarded as an indicator of motor deficits. However, by assessing the complexity (the degree of irregularity using approximate or sample entropy) of a kinematic time series relative to pathology or impaired motor control, i.e., structural variability, both increased and decreased variability of movement characteristics have been reported [11, 15,16,17].
A given motor task can be performed using different combinations of movements owing to the redundancy of the motor system . When a motor task is repeated, the two actions will never be identical because a certain degree of variation in movement synergies is considered natural . Inherent biomechanical and neuro-motor redundancies are available within the context of the control processes involved , and these must also be considered when interpreting the gait pattern.
Elemental and performance variables in gait
According to a definition by Guthrie , skill “consists in the ability to bring about some end result with maximum certainty and minimum outlay of energy, or of time and energy”. A skilled movement strategy, when walking on a flat surface, would result in a steady gait with only natural intrinsic deviations . In terms of energy consumption, the whole-body momentum during walking should be preserved . A change in velocity implies that accelerations, according to Newton’s second law, require force and energy. Therefore, deviations in overall gait velocity or direction are not considered optimal .
From a clinical point of view, any tendency toward deviation in the gait pattern during one stride should be corrected at some point within the following strides. These ongoing corrections should be coordinated to ensure a steady gait. With this understanding, the gait performance is a result of the interaction of stride subsystems acting in synergy. A certain degree of stride-to-stride variation may be expected and may be a sign of good motor performance. Therefore, the interpretation of gait variability as an outcome measure is not trivial and subject to further scientific attention .
Latash and colleagues have been studying synergies in other settings, and their work with performance and elemental variables may provide inspiration for a new perspective on the variability of the gait pattern . We propose that the evaluation of gait variability may also be addressed with respect to both performance and elemental variances. The overall gait pattern (i.e., the whole-body propulsion expressed as velocity) may be seen as the performance variable. Body propulsion is a product of the ground reaction forces derived from the foot contact with the ground for each step or stride. These ground reaction forces may be modified by the timing and/or the placement of the feet on the ground and by joint torques generated in the body (especially the ankle, knee and hip joint). The impact of these forces from each foot contact may be regarded as elemental variables. The performance variable, as indicated by the overall gait velocity, is modified continuously by adjustments of the elemental variables, as expressed by the velocity of each step or stride.
A variation in the stride-to-stride sum (an unintended deviation in the overall gait velocity, i.e., performance variable) is regarded as “resulting” variance in the present study. A deviation in stride-to-stride differences (when a deviation in one stride is positively compensated within the following stride, i.e., elemental variables) is regarded as “adjusting” variance in the present study. If the resulting variance is a sign of a loss of energy and the adjusting variance is seen as a natural part of movement adjustments, the ratio between the adjusting and resulting variations may be expected to serve as an indicator of motor performance during gait.
This proof of concept study explored the relevance of a new approach to gait variability evaluations based on the existence of a meaningful ratio between the elemental (stride-to-stride difference) and the performance (stride-to-stride sum) variables of gait. The study also investigated the timing of such stride-to-stride correction mechanisms during treadmill walking.