PDF(Pubmed)
Abstract：
UNASSIGNED: Novel technologies based on virtual reality (VR) are creating attractive virtual environments with high ecological value, used both in basic/clinical neuroscience and modern medical practice. The study aimed to evaluate the effects of VR-based training in an elderly population.
UNASSIGNED: The study included 36 women over the age of 60, who were randomly divided into two groups subjected to balance-strength and balance-cognitive training. The research applied both conventional clinical tests, such as (a) the Timed Up and Go test, (b) the five-times sit-to-stand test, and (c) the posturographic exam with the Romberg test with eyes open and closed. Training in both groups was conducted for 10 sessions and embraced exercises on a bicycle ergometer and exercises using non-immersive VR created by the ActivLife platform. Machine learning methods with a k-nearest neighbors classifier, which are very effective and popular, were proposed to statistically evaluate the differences in training effects in the two groups.
UNASSIGNED: The study showed that training using VR brought beneficial improvement in clinical tests and changes in the pattern of posturographic trajectories were observed. An important finding of the research was a statistically significant reduction in the risk of falls in the study population. The use of virtual environments in exercise/training has great potential in promoting healthy aging and preventing balance loss and falls among seniors.
UNASSIGNED: The study included 36 women over the age of 60, who were randomly divided into two groups subjected to balance-strength and balance-cognitive training. The research applied both conventional clinical tests, such as (a) the Timed Up and Go test, (b) the five-times sit-to-stand test, and (c) the posturographic exam with the Romberg test with eyes open and closed. Training in both groups was conducted for 10 sessions and embraced exercises on a bicycle ergometer and exercises using non-immersive VR created by the ActivLife platform. Machine learning methods with a k-nearest neighbors classifier, which are very effective and popular, were proposed to statistically evaluate the differences in training effects in the two groups.
UNASSIGNED: The study showed that training using VR brought beneficial improvement in clinical tests and changes in the pattern of posturographic trajectories were observed. An important finding of the research was a statistically significant reduction in the risk of falls in the study population. The use of virtual environments in exercise/training has great potential in promoting healthy aging and preventing balance loss and falls among seniors.
摘要：
■基于虚拟现实（VR）的新技术正在创造具有高生态价值的有吸引力的虚拟环境，用于基础/临床神经科学和现代医学实践。该研究旨在评估基于VR的培训对老年人群的影响。
■该研究包括36名60岁以上的女性，她们被随机分为两组，接受平衡力量和平衡认知训练。这项研究既应用了常规的临床试验，例如(A)定时上行和上行测试，(b)五次静坐试验。和(c)用睁眼和闭眼的Romberg测试进行泌尿外科检查。两组都进行了10次培训，并在自行车测力计上进行了练习，并使用ActivLife平台创建的非沉浸式VR进行了练习。具有k最近邻分类器的机器学习方法，非常有效和受欢迎，建议对两组的训练效果进行统计评估。
■研究表明，使用VR进行的训练在临床测试中带来了有益的改善，并且观察到了后尿路轨迹模式的变化。该研究的一个重要发现是研究人群中跌倒风险的统计学显着降低。在运动/训练中使用虚拟环境在促进健康衰老和防止老年人平衡丧失和跌倒方面具有巨大潜力。
■该研究包括36名60岁以上的女性，她们被随机分为两组，接受平衡力量和平衡认知训练。这项研究既应用了常规的临床试验，例如(A)定时上行和上行测试，(b)五次静坐试验。和(c)用睁眼和闭眼的Romberg测试进行泌尿外科检查。两组都进行了10次培训，并在自行车测力计上进行了练习，并使用ActivLife平台创建的非沉浸式VR进行了练习。具有k最近邻分类器的机器学习方法，非常有效和受欢迎，建议对两组的训练效果进行统计评估。
■研究表明，使用VR进行的训练在临床测试中带来了有益的改善，并且观察到了后尿路轨迹模式的变化。该研究的一个重要发现是研究人群中跌倒风险的统计学显着降低。在运动/训练中使用虚拟环境在促进健康衰老和防止老年人平衡丧失和跌倒方面具有巨大潜力。
