Dataset for Accuracy of an accelerometer-based smartphone application for balance assessment to predict falls in older adults

The purpose of this study was to examine the accuracy of an ACC-based smartphone application for predicting falls in community-dwelling older persons and to determine whether ACC-based smartphone balance assessment approach was more successful at predicting falls in older adults. At baseline, eighty older persons completed a balance evaluation using an accelerometer-based smartphone application that includes the Modified Clinical Test of Sensory Interaction in Balance (MCTSIB), a single-leg stance (SL) test, and a limit of stability (LOS) test. Additionally, the fall rate was documented throughout a six-month follow-up period. Accuracy was determined using the area under the receiver operating characteristic curve (AUC).

本研究旨在验证基于加速度计（ACC）的智能手机应用程序预测社区居住老年人跌倒风险的准确性，并探究该基于加速度计的智能手机平衡评估方法在预测老年人跌倒方面是否更具成效。基线阶段，80名老年人通过基于加速度计的智能手机应用程序完成平衡评估，该评估包含改良版临床平衡感觉交互测试（Modified Clinical Test of Sensory Interaction in Balance，简称MCTSIB）、单腿站立（SL）测试以及稳定性极限（LOS）测试。在为期6个月的随访期间，研究人员记录了受试者的跌倒发生率。最终采用受试者工作特征曲线下面积（AUC）评估该方法的预测准确性。