Soancatl Aguilar V, Lamoth C J C, Maurits N M, Roerdink J B T M
University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science, The Netherlands.
University of Groningen, University Medical Center Groningen, Center of Human Movement Sciences, The Netherlands.
Gait Posture. 2018 Feb;60:235-240. doi: 10.1016/j.gaitpost.2017.12.015. Epub 2017 Dec 16.
Digital games controlled by body movements (exergames) have been proposed as a way to improve postural control among older adults. Exergames are meant to be played at home in an unsupervised way. However, only few studies have investigated the effect of unsupervised home-exergaming on postural control. Moreover, suitable methods to dynamically assess postural control during exergaming are still scarce. Dynamic postural control (DPC) assessment could be used to provide both meaningful feedback and automatic adjustment of exergame difficulty. These features could potentially foster unsupervised exergaming at home and improve the effectiveness of exergames as tools to improve balance control. The main aim of this study is to investigate the effect of six weeks of unsupervised home-exergaming on DPC as assessed by a recently developed probabilistic model. High probability values suggest 'deteriorated' postural control, whereas low probability values suggest 'good' postural control. In a pilot study, ten healthy older adults (average 77.9, SD 7.2 years) played an ice-skating exergame at home half an hour per day, three times a week during six weeks. The intervention effect on DPC was assessed using exergaming trials recorded by Kinect at baseline and every other week. Visualization of the results suggests that the probabilistic model is suitable for real-time DPC assessment. Moreover, linear mixed model analysis and parametric bootstrapping suggest a significant intervention effect on DPC. In conclusion, these results suggest that unsupervised exergaming for improving DPC among older adults is indeed feasible and that probabilistic models could be a new approach to assess DPC.
由身体动作控制的数字游戏（健身游戏）已被提议作为改善老年人姿势控制的一种方式。健身游戏旨在让人们在无人监督的情况下在家中玩。然而，只有少数研究调查了无人监督的家庭健身游戏对姿势控制的影响。此外，在健身游戏过程中动态评估姿势控制的合适方法仍然很少。动态姿势控制（DPC）评估可用于提供有意义的反馈并自动调整健身游戏的难度。这些特性可能会促进在家中无人监督的健身游戏，并提高健身游戏作为改善平衡控制工具的有效性。本研究的主要目的是通过最近开发的概率模型来研究六周无人监督的家庭健身游戏对DPC的影响。高概率值表明姿势控制“恶化”，而低概率值表明姿势控制“良好”。在一项试点研究中，十名健康的老年人（平均年龄77.9岁，标准差7.2岁）在家中每天玩半小时滑冰健身游戏，为期六周，每周三次。使用Kinect在基线和每隔一周记录的健身游戏试验来评估对DPC的干预效果。结果可视化表明概率模型适用于实时DPC评估。此外，线性混合模型分析和参数自举表明对DPC有显著的干预效果。总之，这些结果表明，在老年人中进行无人监督的健身游戏以改善DPC确实是可行的，并且概率模型可能是评估DPC的一种新方法。
