This study investigates the effects of treadmill control algorithms on spatiotemporal variables when walking on a self-paced (SP) treadmill. Ten healthy subjects walked at their preferred walking speed for 15 min under three different treadmill control modes. Stride time, stride length, and stride speed were measured using an inertial measurement unit. The mean, coefficient of variance, Poincaré descriptors, and gait dynamics were calculated for each parameter. The mean values of stride length and stride speed were significantly increased when the treadmill had a quick response speed to the user’s walking behavior. The long-term variability of stride length and stride speed was significantly affected by the treadmill control algorithms. A reduced strength of long-range correlations of stride time and stride speed was found when walking on the SP treadmill with suppressed treadmill accelerations and small velocity variations. We suggest that the suppression of treadmill acceleration provides more adaptability and less constraint to the user during SP treadmill walking. Although further research is required, the present work provides a basis for interpreting the influence of treadmill control algorithms on human gait.

这项研究调查了跑步机控制算法在自定速度（SP）跑步机上行走时对时空变量的影响。在三种不同的跑步机控制模式下，十名健康受试者以他们喜欢的步行速度行走了15分钟。使用惯性测量单元测量步幅时间，步幅长度和步幅速度。计算每个参数的均值，方差系数，庞加莱描述符和步态动力学。当跑步机对用户的步行行为具有快速响应速度时，步幅长度和步幅速度的平均值会显着增加。跑步机控制算法极大地影响了步幅和步幅的长期变化。当在SP跑步机上行走时，踏步时间和步速的长期相关性强度降低，跑步机加速度受到抑制，速度变化较小。我们建议在SP跑步机行走过程中抑制跑步机加速度为用户提供更大的适应性和更少的约束。尽管需要进一步的研究，但本工作为解释跑步机控制算法对人的步态的影响提供了基础。