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Assessment of Fall Characteristics from Depth Sensor Videos

机译:从深度传感器视频评估跌落特征

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摘要

Falls are a major source of death and disability in older adults; little data, however, are available about the etiology of falls in community-dwelling elders. Sensor systems installed in independent and assisted living residences of 105 older adults participating in an ongoing technology study were programmed to record live videos of probable fall events. Sixty-four fall video segments from 19 individuals were viewed and rated using the Falls Video Assessment Questionnaire. Raters identified that 56% (n=36) of falls were due to an incorrect shift of body weight and 27% (n=17) from losing support of an external object, such as an unlocked wheelchair or rolling walker. In 60% of falls, mobility aids were present in the room or in use at the time of the fall. Use of environmentally-embedded sensors provides a mechanism for real-time fall detection and, ultimately, may supply information to clinicians for fall prevention interventions.
机译:跌倒是老年人死亡和残疾的主要来源;但是,关于社区居民中老年人跌倒的病因的数据很少。对安装在参与正在进行的技术研究的105名老年人的独立和辅助居住区中的传感器系统进行了编程,以记录可能坠落事件的实时视频。使用“瀑布视频评估问卷”对来自19个人的64个秋天视频片段进行了查看和评分。评估者指出,有56%(n = 36)的跌倒是由于体重的不正确移动造成的,而27%(n = 17)的跌落是由于失去对外部物体的支撑,例如未锁定的轮椅或助步车。在60%的跌倒中,跌倒时房间内或使用中有助行器。使用嵌入环境的传感器提供了一种实时跌倒检测机制,最终可以为临床医生提供预防跌倒干预的信息。

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