A continuous monitoring of the physical strength and mobility of elderly people is important for maintaining their health and treating diseases at an early stage. However, frequent screenings by physicians are exceeding the logistic capacities. An alternate approach is the automatic and unobtrusive collection of functional measures by ambient sensors. In the current publication, we show the correlation among data of ambient motion sensors and the well-established mobility assessments Short-Physical-Performance-Battery, Tinetti and Timed Up & Go. We use the average number of motion sensor events as activity measure for correlation with the assessment scores. The evaluation on a real-world dataset shows a moderate to strong correlation with the scores of standardised geriatrics physical assessments.
翻译:对老年人的体力和流动性进行持续监测,对于在早期阶段保持他们的健康和治疗疾病十分重要,然而,医生经常进行的筛查超出了后勤能力,另一种办法是环境传感器自动和不受干扰地收集功能性措施,在目前出版物中,我们显示了环境运动传感器的数据与成熟的流动评估数据之间的关系,即短物理-性能-电池、Tinetti和定时上升-go。我们使用运动感应事件的平均数量作为活动衡量与评估分数的相关性。对真实世界数据集的评估显示,与标准化的老年病物理评估的分数有中度至强烈的关联。