Similä Heidi, Immonen Milla, Ermes Miikka
VTT Technical Research Centre of Finland Ltd, Kaitoväylä 1, P.O.Box 1100, FI-90571 Oulu, Finland.
VTT Technical Research Centre of Finland Ltd, Tekniikankatu 1, P.O.Box 1300, 33101 Tampere, Finland.
Comput Biol Med. 2017 Jun 1;85:25-32. doi: 10.1016/j.compbiomed.2017.04.009. Epub 2017 Apr 13.
Falls are the cause for more than half of the injury-related hospitalizations among older people. Accurate assessment of individuals' fall risk could enable targeted interventions to reduce the risk. This paper presents a novel method for using wearable accelerometers to detect early signs of deficits in balance from gait. Gait acceleration data were analyzed from 35 healthy female participants (73.86±5.40 years). The data were collected with waist-mounted accelerometer and the participants performed three supervised balance tests: Berg Balance Scale (BBS), Timed-Up-and-Go (TUG) and 4m walk. The follow-up tests with the same protocol were performed after one year. Altogether 43 features were extracted from the accelerometer signals. Sequential forward floating selection and ten-fold cross-validation were applied to determine models for 1) estimating the outcomes of BBS, TUG and 4m walk tests and 2) predicting decline in balance during one-year follow-up indicated as decline in BBS total score and one leg stance. Normalized root-mean-square errors (RMSE) of the assessment scale result estimates were 0.28 for BBS score, 0.18 for TUG time, and 0.22 for 4m walk test. Area under curve (AUC) was 0.78 for predicting decline in BBS total score and 0.82 for one leg stance, respectively. The results suggest that the gait features can be used to estimate the result of a clinical balance assessment scale and predict decline in balance. A simple walk test with wearable monitoring could be applicable as an initial screening tool to identify people with early signs of balance deficits.
跌倒是导致老年人因伤住院的半数以上原因。准确评估个体的跌倒风险有助于采取针对性干预措施以降低风险。本文提出了一种利用可穿戴加速度计检测步态中平衡缺陷早期迹象的新方法。对35名健康女性参与者（73.86±5.40岁）的步态加速度数据进行了分析。数据通过佩戴在腰部的加速度计收集，参与者进行了三项有监督的平衡测试：伯格平衡量表（BBS）、定时起立行走测试（TUG）和4米步行测试。一年后按照相同方案进行了后续测试。从加速度计信号中总共提取了43个特征。应用顺序向前浮动选择和十折交叉验证来确定模型，用于1）估计BBS、TUG和4米步行测试的结果，以及2）预测一年随访期间平衡能力下降情况，以BBS总分下降和单腿站立表示。评估量表结果估计的标准化均方根误差（RMSE）对于BBS评分是0.28，对于TUG时间是0.18，对于4米步行测试是0.22。预测BBS总分下降的曲线下面积（AUC）为0.78，预测单腿站立的AUC为0.82。结果表明，步态特征可用于估计临床平衡评估量表的结果并预测平衡能力下降。一项简单的可穿戴监测步行测试可作为一种初步筛查工具，用于识别有平衡缺陷早期迹象的人群。
