Adaptability of stride-to-stride control of stepping movements in human walking

详细信息    查看全文

• 作者：Nicole K. Bohnsack-McLagan^a ; Joseph P. Cusumano^b ; Jonathan B. Dingwell^a ; ^{jdingwell@austin.utexas.edu" class="auth_mail" title="E-mail the corresponding author} ;
• 关键词：Walking ; Motor control ; Variability ; Redundancy ; Equifinality
• 刊名：Journal of Biomechanics
• 出版年：2016
• 出版时间：25 January 2016
• 年：2016
• 卷：49
• 期：2
• 页码：229-237
• 全文大小：607 K

文摘

Humans continually adapt their movements as they walk on different surfaces, avoid obstacles, etc. External (environmental) and internal (physiological) noise-like disturbances, and the responses that correct for them, each contribute to locomotor variability. This variability may sometimes be detrimental (perhaps increasing fall risk), or sometimes beneficial (perhaps reflecting exploration of multiple task solutions). Here, we determined how humans regulated stride-to-stride fluctuations in walking when presented different task goals that allowed them to exploit inherent redundancies in different ways. Fourteen healthy adults walked on a treadmill under each of four conditions: constant speed only (SPD), constant speed and stride length (LEN), constant speed and stride time (TIM), or constant speed, stride length, and stride time (ALL). Multiple analyses tested competing hypotheses that participants might attempt to either equally satisfy all goals simultaneously, or instead adopt systematic intermediate strategies that only partly satisfied each individual goal. Participants exhibited similar average stepping behavior, but significant differences in variability and stride-to-stride serial correlations across conditions. Analyses of the structure of stride-to-stride fluctuation dynamics demonstrated humans resolved the competing goals presented not by minimizing errors equally with respect to all goals, but instead by trying to only partly satisfy each goal. Thus, humans exploit task redundancies even when they are explicitly removed from the task specifications. These findings may help identify when variability is predictive of, or protective against, fall risk. They may also help inform rehabilitation interventions to better exploit the positive contributions of variability, while minimizing the negative.