Injury Prevention and Mobility Laboratory, Simon Fraser University, Burnaby, BC, Canada.
IEEE Trans Neural Syst Rehabil Eng. 2011 Dec;19(6):670-6. doi: 10.1109/TNSRE.2011.2162250. Epub 2011 Aug 22.
Falls are the number one cause of injury in older adults. Wearable sensors, typically consisting of accelerometers and/or gyroscopes, represent a promising technology for preventing and mitigating the effects of falls. At present, the goal of such "ambulatory fall monitors" is to detect the occurrence of a fall and alert care providers to this event. Future systems may also provide information on the causes and circumstances of falls, to aid clinical diagnosis and targeting of interventions. As a first step towards this goal, the objective of the current study was to develop and evaluate the accuracy of a wearable sensor system for determining the causes of falls. Sixteen young adults participated in experimental trials involving falls due to slips, trips, and "other" causes of imbalance. Three-dimensional acceleration data acquired during the falling trials were input to a linear discriminant analysis technique. This routine achieved 96% sensitivity and 98% specificity in distinguishing the causes of a falls using acceleration data from three markers (left ankle, right ankle, and sternum). In contrast, a single marker provided 54% sensitivity and two markers provided 89% sensitivity. These results indicate the utility of a three-node accelerometer array for distinguishing the cause of falls.
跌倒 是老年人受伤的首要原因。可穿戴传感器，通常由加速度计和/或陀螺仪组成，是预防和减轻跌倒影响的有前途的技术。目前，这种“可移动跌倒监测器”的目标是检测跌倒的发生，并向护理人员发出此事件的警报。未来的系统还可能提供有关跌倒原因和情况的信息，以帮助临床诊断和干预措施的定位。作为实现这一目标的第一步，本研究的目的是开发和评估一种可穿戴传感器系统，以确定跌倒的原因。16 名年轻人参加了涉及因滑倒、绊倒和“其他”失衡原因而跌倒的实验性试验。将跌倒试验过程中获得的三维加速度数据输入线性判别分析技术。该例程使用来自三个标记（左踝、右踝和胸骨）的加速度数据区分跌倒原因的灵敏度为 96%，特异性为 98%。相比之下，单个标记的灵敏度为 54%，两个标记的灵敏度为 89%。这些结果表明三节点加速度计阵列可用于区分跌倒的原因。
