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ObjectiveTraditionally, gait analysis has been centered on the idea of average behavior and normality. On one hand, clinical diagnoses and therapeutic interventions typically assume that average gait patterns remain constant over time. On the other hand, it is well known that all our movements are accompanied by a certain amount of variability, which does not allow us to make two identical steps. The purpose of this study was to examine changes in the intra-individual gait patterns across different time-scales (i.e., tens-of-mins, tens-of-hours).MethodsNine healthy subjects performed 15 gait trials at a self-selected speed on 6 sessions within one day (duration between two subsequent sessions from 10 to 90 mins). For each trial, time-continuous ground reaction forces and lower body joint angles were measured. A supervised learning model using a kernel-based discriminant regression was applied for classifying sessions within individual gait patterns.Results and discussionDiscernable characteristics of intra-individual gait patterns could be distinguished between repeated sessions by classification rates of 67.8 ± 8.8% and 86.3 ± 7.9% for the six-session-classification of ground reaction forces and lower body joint angles, respectively. Furthermore, the one-on-one-classification showed that increasing classification rates go along with increasing time durations between two sessions and indicate that changes of gait patterns appear at different time-scales.ConclusionDiscernable characteristics between repeated sessions indicate continuous intrinsic changes in intra-individual gait patterns and suggest a predominant role of deterministic processes in human motor control and learning. Natural changes of gait patterns without any externally induced injury or intervention may reflect continuous adaptations of the motor system over several time-scales. Accordingly, the modelling of walking by means of average gait patterns that are assumed to be near constant over time needs to be reconsidered in the context of these findings, especially towards more individualized and situational diagnoses and therapy.

Individuality and Situatedness in Movement Patterns patterns could also be detected, indicating the occurrence of adaptations in individual movement patterns throughout the fatigue-related accumulation process. The results suggest that these adaptations can be modeled in terms of changes in patterns rather than increasing variance. Practical consequences are critically discussed.

Training consisting of numerous repetitions performed as closely as possible to ideal techniques is common in sports and every-day tasks. Little is known about fatigue-related technique changes that emerge at different timescales when repeating complex actions such as a karate front kick. Accordingly, 15 karatekas performed 600 kicks (1 pre-block and 9 blocks). The pre-block comprised 6 kicks (3 with each leg) at maximum intensity (K-100%). Each block comprised 60 kicks (10 with each leg) at 80% of their self-perceived maximum intensity (K-80%) plus 6 K-100%. In between blocks, the participants rested for 90 seconds. Right leg kinematics (peak joint angles, peak joint angular velocities, peak joint linear resultant velocities, and time of occurrence of peaks) and kick duration corresponding to the K-80% were measured resulting in numerous variations with fatigue. At the timescale of tens of seconds, the changes involved variables that were related to velocity of execution (slowed down), while variables related to movement form were hardly affected. At the timescale of tens of minutes, the opposite results were observed. These findings challenge the long-standing rationale underlying repetitive training, suggesting instead that such involuntary variations in technique might play a crucial role in motor skill training.

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