IEEE Trans Neural Syst Rehabil Eng. 2018 Jan;26(1):171-180. doi: 10.1109/TNSRE.2017.2769701.
Improving balance performance among the elderly is of utmost importance because of the increasing number of injuries and fatalities caused by fall incidences. Digital games controlled by body movements (exergames) have been proposed as a way to improve balance among older people. However, the assessment of balance performance in real-time during exergaming remains a challenging task. This assessment could be used to provide instantaneous feedback and automatically adjust the exergame difficulty. Such features could potentially increase the motivation of the player, thus augmenting the effectiveness of exergames. As clear differences in balance performance have been identified between older and younger people, distinguishing between older and younger adults can help identifying measures of balance performance. We used generalized linear models to investigate whether the assessment of balance performance based on movement speed can be improved by incorporating curvature of the movement trajectory into the analysis. Indeed, our results indicated that curvature improves the performance of the models. Five-fold cross validation indicated that our method is promising for the assessment of balance performance in real-time by showing more than 90% classification accuracy. Finally, this method could be valuable not only for exergaming, but also for real-time assessment of body movements in sports, rehabilitation, and medicine.
提高老年人的平衡能力非常重要，因为跌倒导致的伤害和死亡人数不断增加。通过身体运动控制的数字游戏（体适能游戏）已被提出作为一种提高老年人平衡能力的方法。然而，在体适能游戏中实时评估平衡能力仍然是一项具有挑战性的任务。这种评估可以用于提供即时反馈并自动调整体适能游戏的难度。这些功能可以提高玩家的积极性，从而提高体适能游戏的效果。由于老年人和年轻人的平衡能力有明显差异，区分老年人和年轻人可以帮助确定平衡能力的衡量标准。我们使用广义线性模型来研究是否可以通过将运动轨迹的曲率纳入分析来提高基于运动速度的平衡能力评估。事实上，我们的结果表明曲率可以提高模型的性能。五折交叉验证表明，我们的方法具有很大的潜力，可以通过显示超过 90%的分类准确性，实现实时的平衡能力评估。最后，这种方法不仅在体适能游戏中很有价值，而且在运动、康复和医学领域实时评估身体运动中也很有价值。
