Department of Physical Therapy, Winston-Salem State University, 346 FL Atkins Bldg., 601 Martin Luther King Drive, Winston-Salem, NC, 27110, USA.
Baylor Scott and White Institute for Rehabilitation, 909 N. Washington Ave, Dallas, TX, 75246, USA.
Aging Clin Exp Res. 2020 May;32(5):835-840. doi: 10.1007/s40520-019-01256-w. Epub 2019 Jul 3.
Walking for people with Parkinson's disease (PD) degrades during motor-cognitive interplay (i.e., dual task conditions). Declining gait mechanics and turning ability result in more frequent falls and an interruption of daily activities in persons with PD.
To determine the impact of dual-tasking on key mobility elements during a walking task in people with PD with 2D motion analysis.
Participants performed Timed Up and Go (TUG) single, dual task conditions (TUG, TUG, and TUG). 2D motion analysis application was used to quantify seven key mobility elements including: sit-to-walk (STW) (s), walking turn time (WTT) (s), number of turn steps, turn-to-sit (TTS) (s), total number of TUG steps, total TUG time and turn strategy (on-the-spot or u-shaped).
Thirty-one participants with PD completed this study [age M= 69 ± 8.19, UPDRSm M= 23.21 ± 10.03, HY MED= 2 (range 1-4)]. All key elements were significantly different between TUG conditions with the exception of sit-to-walk and turn strategy. Turn strategy was consistent across TUG tasks despite added cognitive loading. Repeated-measures MANOVA differences were observed in WTT (p = 0.01), number of turn steps (p = 0.03), TTS (p < 0.001), total number of TUG steps (p = 0.01), and total TUG time (p = 0.01). No significant relationships were found between disease severity (HY/UPDRSm) and turn strategy.
DISCUSSION/CONCLUSION: Key mobility elements were significantly affected across dual task walking conditions in persons with PD. The use of 2D motion analysis assisted with identification of key mobility elements impacted during the single and dual task conditions.
对于帕金森病(PD)患者来说,行走在运动认知相互作用(即双重任务条件)期间会恶化。步态力学和转弯能力下降会导致更多的跌倒,并中断 PD 患者的日常活动。
使用 2D 运动分析确定双重任务对 PD 患者行走任务中关键移动元素的影响。
参与者进行了计时起立行走(TUG)单任务、双重任务条件(TUG、TUG 和 TUG)。使用 2D 运动分析应用程序来量化七个关键移动元素,包括:从坐到站(STW)(s)、行走转弯时间(WTT)(s)、转弯步数、从站到站(TTS)(s)、TUG 总步数、TUG 总时间和转弯策略(原地或 U 形)。
31 名 PD 患者完成了这项研究[年龄 M=69±8.19,UPDRSm M=23.21±10.03,HY MED=2(范围 1-4)]。除了从坐到站和转弯策略外,所有关键元素在 TUG 条件之间均有显著差异。尽管认知负荷增加,但转弯策略在 TUG 任务中保持一致。重复测量 MANOVA 差异在 WTT(p=0.01)、转弯步数(p=0.03)、TTS(p<0.001)、TUG 总步数(p=0.01)和 TUG 总时间(p=0.01)方面均有观察到。在疾病严重程度(HY/UPDRSm)和转弯策略之间未发现显著关系。
讨论/结论:在 PD 患者的双重任务行走条件下,关键移动元素受到显著影响。使用 2D 运动分析有助于识别在单任务和双重任务条件下受到影响的关键移动元素。