跌倒除了會造成的身體受傷嚴重時可能會造成致命傷害,因此預防跌倒已成為重視的議題,而靜態的平衡能力訓練可有效的增強身體平衡能力的維持以及降低跌倒的風險。本研究使用虛擬實境提供視覺輔助結合動作捕捉技術運用於平衡能力訓練,在進行平衡訓練時受測者需穿著動作捕捉衣並驅動虛擬場景中的虛擬人模,隨者虛擬場景提供人形框視覺輔助並與虛擬場景互動,讓受測者進行平衡能力訓練時受測者需讓虛擬人模維持於人形框內,以表示受測者的動作符合平衡能力訓練之動作姿勢,本研究設計人形框大小與人形框移動時間這兩項參數設計四種不同平衡能力訓練虛擬場景,並探討在不同人框參數設計之平衡能力訓練虛擬場景對於受測者維持於人形框內的時間與碰撞機率的影響,本研究所使用提出的平衡能力訓練方法有下列優點,第一,可客製化人形框參數設計調整訓練困難度,第二,提供視覺輔助讓動作姿勢更標準,第三,利用動作捕捉系統將能擷取受測者於平衡能力訓練過程的肢體動作,以進行量化分析。實驗結果為提供人形框視覺輔助下進行平衡能力訓練,不同人形框參數調整下可設計出平衡能力訓練的困難度。
Fall prevention has become a more and more important issue as fall-down has been cited as the number one reason to cause accidental death of aged adults. Static balance training is an effective method to increase the balancing capacity of elderly and reduce their fall risks. This paper proposes combined virtual reality (VR) with motion capture system (MoCap) to practice balance training. Our method lets the subjects wear motion capture devices to interactively manipulate a digital human model (DHM) in a virtual environment to follow a 3D posture model (PM). A usability evaluation experiment is conducted and the results show that the parameters of PM design will affect the subjects posture control performance. Our approach is superior to existed methods in several aspects. First, the training process could be customized by modifying the parameters of the PM. Secondly, the training process is accurate because the trainee has to follow the PM. Thirdly, the training process could be quantitatively evaluated by detecting and analyzing the collision information between the DHM and PM. The results show that the visual stimulations created by different PM designs could affect the trainee’s posture control ability and quality.