FysioHolland Twente, Enschede,The Netherlands.
Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen,The Netherlands.
Motor Control. 2022 Jan 1;26(1):15-35. doi: 10.1123/mc.2021-0047. Epub 2021 Nov 12.
The present study explores variations in the degree of automaticity and predictability of cyclical arm and leg movements. Twenty healthy adults were asked to walk on a treadmill at a lower-than-preferred speed, their preferred speed, and at a higher-than-preferred speed. In a separate, repetitive punching task, the three walking frequencies were used to cue the target pace of the cyclical arm movements. Movements of the arms, legs, and trunk were digitized with inertial sensors. Whereas absolute slope values (|β|) of the linear fit to the power spectrum of the digitized movements (p < .001, η2 = .676) were systematically smaller in treadmill walking than in repetitive punching, sample entropy measures (p < .001, η2 = .570) were larger reflecting the former task being more automated but also less predictable than the latter task. In both tasks, increased speeds enhanced automatized control (p < .001, η2 = .475) but reduced movement predictability (p = .008, η2 = .225). The latter findings are potentially relevant when evaluating effects of task demand changes in clinical contexts.
本研究探讨了周期性手臂和腿部运动的自动化和可预测性程度的变化。 要求 20 名健康成年人在跑步机上以低于、等于和高于其偏好的速度行走。 在一个单独的重复打孔任务中,使用这三种步行频率来提示周期性手臂运动的目标速度。 使用惯性传感器对手臂、腿部和躯干的运动进行数字化。 虽然数字运动的功率谱线性拟合的绝对值斜率值(|β|)(p <.001,η2 =.676)在跑步机行走中明显小于重复打孔,但样本熵测量值(p <.001,η2 =.570)更大,反映了前者任务比后者任务更自动化但也更不可预测。 在这两个任务中,速度的增加都增强了自动化控制(p <.001,η2 =.475),但降低了运动的可预测性(p =.008,η2 =.225)。 当在临床环境中评估任务需求变化的影响时,这些发现可能具有重要意义。