Fall Risk Assessment for the Elderly Based on Weak Foot Features of Wearable Plantar Pressure
Fall Risk Assessment for the Elderly Based on Weak Foot Features of Wearable Plantar Pressure
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DOI：
10.1109/tnsre.2022.3167473
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发表时间：
2022-01-01
影响因子：
4.9
通讯作者：
Chen, Zhuoming
中科院分区：
文献类型：
--
作者：
Song, Zhen;Ou, Jianlin;Chen, Zhuoming
老年人的高跌倒率给家庭和医疗系统带来了巨大的挑战，因此，早期风险评估和干预非常必要。与其他基于传感器的技术相比，鞋内足底压力传感器由于其便携性，有效性和低突兀性被广泛用于长期跌倒风险评估。虽然频繁使用的双足压力中心（COP）特征是从压力感测平台导出的，但是由于缺乏相对位置信息，它们不适合于鞋系统或压力鞋垫。因此，本研究提出“弱脚”的定义，以解决单一脚特徴的敏感性问题，并促进时间一致性相关特徴的抽取。基于单足COP提取了44个多维弱足特征，探讨了弱足跌倒风险与时间不一致性之间的关系，并采用概率分布方法分析了步态线的对称性和时间一致性。通过实验，收集了48名受试者的足底压力数据，其中24名高风险（HR）和24名低风险（LR）的智能鞋系统获得。最终模型的准确度为87.5%，对测试数据的灵敏度为100%，优于使用双足COP的基线模型。研究结果和特征空间表明，可穿戴足底压力的新特征可以综合评价HR组和LR组之间的差异。基于这些特征的跌倒风险评估模型具有良好的泛化性能，并在实际监测情况下表现出实用性和可靠性。
The high fall rate of the elderly brings enormous challenges to families and the medical system; therefore, early risk assessment and intervention are quite necessary. Compared to other sensor-based technologies, in-shoe plantar pressure sensors, effectiveness and low obtrusiveness are widely used for long-term fall risk assessments because of their portability. While frequently-used bipedal center-of-pressure (COP) features are derived from a pressure sensing platform, they are not suitable for the shoe system or pressure insole owing to the lack of relative position information. Therefore, in this study, a definition of "weak foot" was proposed to solve the sensitivity problem of single foot features and facilitate the extraction of temporal consistency related features. Forty-four multi-dimensional weak foot features based on single foot COP were correspondingly extracted; notably, the relationship between the fall risk and temporal inconsistency in the weak foot were discussed in this study, and probability distribution method was used to analyze the symmetry and temporal consistency of gait lines. Though experiments, foot pressure data were collected from 48 subjects with 24 high risk (HR) and 24 low risk (LR) ones obtained by the smart footwear system. The final models with 87.5% accuracy and 100% sensitivity on test data outperformed the base line models using bipedal COP. The results and feature space shown the novel features of wearable plantar pressure could comprehensively evaluate the difference between HR and LR groups. Our fall risk assessment models based on these features had good generalization performance, and showed practicability and reliability in real-life monitoring situations.