Centro Algoritmi, Campus Azurem, University of Minho, Guimarães.
Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga.
Clin Interv Aging. 2017 Nov 7;12:1843-1857. doi: 10.2147/CIA.S147428. eCollection 2017.
Imbalance and tripping over obstacles as a result of altered gait in older adults, especially in patients with Parkinson's disease (PD), are one of the most common causes of falls. During obstacle crossing, patients with PD modify their behavior in order to decrease the mechanical demands and enhance dynamic stability. Various descriptions of dynamic traits of gait that have been collected over longer periods, probably better synthesize the underlying structure and pattern of fluctuations in gait and can be more sensitive markers of aging or early neurological dysfunction and increased risk of falls. This confirmation challenges the clinimetric of different protocols and paradigms used for gait analysis up till now, in particular when analyzing obstacle crossing. The authors here present a critical review of current knowledge concerning the interplay between the cognition and gait in aging and PD, emphasizing the differences in gait behavior and adaptability while walking over different and challenging obstacle paradigms, and the implications of obstacle negotiation as a predictor of falls. Some evidence concerning the effectiveness of future rehabilitation protocols on reviving obstacle crossing behavior by trial and error relearning, taking advantage of dual-task paradigms, physical exercise, and virtual reality have been put forward in this article.
老年人(尤其是帕金森病患者)因步态改变而导致的平衡和绊倒,是跌倒的最常见原因之一。在跨越障碍物时,帕金森病患者会改变其行为,以降低机械需求并增强动态稳定性。对较长时间段内收集的步态动态特征的各种描述,可能更好地综合了步态波动的潜在结构和模式,并且可以更敏感地标记衰老或早期神经功能障碍以及跌倒风险增加。这一确认挑战了迄今为止用于步态分析的不同方案和范式的临床计量学,特别是在分析跨越障碍物时。本文作者对认知与衰老和帕金森病中的步态之间相互作用的当前知识进行了批判性回顾,强调了在不同且具有挑战性的障碍物范式下行走时步态行为和适应性的差异,以及作为跌倒预测因子的障碍物协商的意义。本文还提出了一些关于未来康复方案的有效性的证据,这些方案通过试错重新学习、利用双重任务范式、体育锻炼和虚拟现实来恢复跨越障碍物的行为。