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Mobile gait analysis via eSHOEs instrumented shoe insoles: a pilot study for validation against the gold standard GAITRite?

机译:通过eShoes仪表鞋鞋垫的移动步态分析:对黄金标准Gaitrite验证的试点研究?

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Clinical gait analysis contributes massively to rehabilitation support and improvement of in-patient care. The research project eSHOE aspires to be a useful addition to the rich variety of gait analysis systems. It was designed to fill the gap of affordable, reasonably accurate and highly mobile measurement devices. With the overall goal of enabling individual home-based monitoring and training for people suffering from chronic diseases, affecting the locomotor system. Motion and pressure sensors gather movement data directly on the (users) feet, store them locally and/or transmit them wirelessly to a PC. A combination of pattern recognition and feature extraction algorithms translates the motion data into standard gait parameters. Accuracy of eSHOE were evaluated against the reference system GAITRite in a clinical pilot study. Eleven hip fracture patients (78.4?±?7.7 years) and twelve healthy subjects (40.8?±?9.1 years) were included in these trials. All subjects performed three measurements at a comfortable walking speed over 8?m, including the 6-m long GAITRite mat. Six standard gait parameters were extracted from a total of 347 gait cycles. Agreement was analysed via scatterplots, histograms and Bland–Altman plots. In the patient group, the average differences between eSHOE and GAITRite range from ?0.046 to 0.045?s and in the healthy group from ?0.029 to 0.029?s. Therefore, it can be concluded that eSHOE delivers adequately accurate results. Especially with the prospect as an at home supplement or follow-up to clinical gait analysis and compared to other state of the art wearable motion analysis systems.
机译:临床步态分析促进康复支持和改善患者护理。研究项目eShoe渴望成为丰富各种步态分析系统的有用补充。它旨在填补经济实惠,合理准确和高度移动的测量装置的差距。凭借为患有慢性病患者的人们实现个人家庭监测和培训的总体目标,影响了运动系统。运动和压力传感器直接在(用户)脚上采集移动数据,在本地存储它们和/或将它们无线传输到PC。模式识别和特征提取算法的组合将运动数据转换为标准步态参数。在临床试验研究中针对参考系统Gaitrite评估eShoe的准确性。在这些试验中包括11名髋关节骨折患者(78.4?±7.7岁)和12个健康受试者(40.8?±9.1岁)。所有受试者均以超过8Ω米的舒适步行速度进行三次测量,包括6米长的延长垫。从总共347个步态周期提取六个标准步态参数。通过散点图,直方图和Bland-Altman图分析了协议。在患者组中,Oshoe和Gaitrite之间的平均差异来自Δ0.046至0.045?S和健康组的Δ0.029至0.029?s。因此,可以得出结论,eShoe提供了充分准确的结果。特别是与临床步态分析的展望作为临床步态分析,与其他艺术佩戴运动分析系统相比。

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