Haescher Marian, Chodan Wencke, Höpfner Florian, Bieber Gerald, Aehnelt Mario, Srinivasan Karthik, Murphy Margit Alt
Fraunhofer Institute for Computer Graphics Research IGD, Competence Center Visual Assistance Technologies, Rostock, DE, Germany.
Institute for Visual and Analytic Computing, Department of Multimedia Communication, University of Rostock, DE, Germany.
J Rehabil Assist Technol Eng. 2020 Dec 4;7:2055668320946209. doi: 10.1177/2055668320946209. eCollection 2020 Jan-Dec.
Falls cause major expenses in the healthcare sector. We investigate the ability of supporting a fall risk assessment by introducing algorithms for automated assessments of standardized fall risk-related tests via wearable devices.
In a study, 13 participants conducted the standardized 6-Minutes Walk Test, the Timed-Up-and-Go Test, the 30-Second Sit-to-Stand Test, and the 4-Stage Balance Test repeatedly, producing 226 tests in total. Automatedalgorithms computed by wearable devices, as well as a visual analysis of the recorded data streams, were compared to the observational results conducted by physiotherapists.
There was a high congruence between automated assessments and the ground truth for all four test types (ranging from 78.15% to 96.55%), with deviations ranging all well within one standard deviation of the ground truth. Fall risk (assessed by questionnaire) correlated with the individual tests.
The automated fall risk assessment using wearable devices and algorithms matches the validity of the ground truth, thus providing a resourceful alternative to the effortful observational assessment, while minimizing the risk of human error. No single test can predict overall fall risk; instead, a much more complex model with additional input parameters (e.g., fall history, medication etc.) is needed.
跌倒在医疗保健领域造成了巨大的费用支出。我们通过引入算法来自动评估通过可穿戴设备进行的标准化跌倒风险相关测试，从而研究支持跌倒风险评估的能力。
在一项研究中，13名参与者反复进行了标准化的6分钟步行测试、定时起立行走测试、30秒坐立测试和四阶段平衡测试，总共进行了226次测试。将可穿戴设备计算出的自动算法以及对记录数据流的视觉分析与物理治疗师的观察结果进行比较。
对于所有四种测试类型，自动评估与实际情况之间具有高度一致性（范围从78.15%到96.55%），偏差均在实际情况的一个标准差范围内。跌倒风险（通过问卷评估）与各个测试相关。
使用可穿戴设备和算法进行的自动跌倒风险评估与实际情况的有效性相匹配，从而为费力的观察性评估提供了一种有用的替代方法，同时将人为错误的风险降至最低。没有单一的测试能够预测总体跌倒风险；相反，需要一个具有更多输入参数（例如跌倒史、药物治疗等）的更为复杂的模型。
