Jagos Harald, Pils Katharina, Haller Michael, Wassermann Claudia, Chhatwal Christa, Rafolt Dietmar, Rattay Frank
a Institute for Analysis and Scientific Computing , Vienna University of Technology , Vienna , Austria.
b Institut für Physikalische Medizin und Rehabilitation , Sophienspital , Wien , Austria.
J Med Eng Technol. 2017 Jul;41(5):375-386. doi: 10.1080/03091902.2017.1320434. Epub 2017 Jun 2.
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.
临床步态分析对康复支持和住院护理的改善有巨大贡献。eSHOE研究项目希望成为丰富多样的步态分析系统的有益补充。它旨在填补价格合理、精度尚可且高度便携的测量设备的空白。其总体目标是为患有影响运动系统的慢性病的患者提供个性化的居家监测和训练。运动和压力传感器直接在（用户的）脚上收集运动数据，在本地存储这些数据和/或将其无线传输到电脑。模式识别和特征提取算法相结合，将运动数据转化为标准步态参数。在一项临床试点研究中，对照参考系统GAITRite评估了eSHOE的准确性。这些试验纳入了11名髋部骨折患者（78.4±7.7岁）和12名健康受试者（40.8±9.1岁）。所有受试者以舒适的步行速度在8米的距离内进行三次测量，其中包括6米长的GAITRite垫子。从总共347个步态周期中提取了六个标准步态参数。通过散点图、直方图和布兰德-奥特曼图分析一致性。在患者组中，eSHOE和GAITRite之间的平均差异在-0.046至0.045秒之间，在健康组中在-0.029至0.029秒之间。因此，可以得出结论，eSHOE能提供足够准确的结果。特别是作为临床步态分析的居家补充或后续手段，并且与其他先进的可穿戴运动分析系统相比。
