Park Sunwoo, Ryu Kihong, Kim Jungyoon, Son Jongsang, Kim Youngho
Department of Biomedical Engineering , Institute of Medical Engineering, Yonsei University, Wonju, Gangwon, South Korea.
Comput Methods Biomech Biomed Engin. 2012;15(11):1129-35. doi: 10.1080/10255842.2011.575376. Epub 2011 May 23.
In this study, we have analysed heel strike (HS) and toe off (TO) of normal individuals and hemiplegic patients, taking advantage of output curves acquired from various sensors, and verified the validity of sensor detection methods and their effectiveness when they were used for hemiplegic gaits. Gait phase detections using three different motion sensors were valid, since they all had reliabilities more than 95%, when compared with foot velocity algorithm. Results showed that the tilt sensor and the gyrosensor could detect gait phase more accurately in normal individuals. Vertical acceleration could detect HS most accurately in hemiplegic patient group A. The gyrosensor could detect HS and TO most accurately in hemiplegic patient groups A and B. The detection of TO from all sensor signals was valid in both the patient groups A and B. However, the vertical acceleration detected HS validly in patient group A and the gyrosensor detected HS validly in patient group B.
在本研究中，我们利用从各种传感器获取的输出曲线，分析了正常个体和偏瘫患者的足跟触地（HS）和足趾离地（TO）情况，并验证了传感器检测方法的有效性及其用于偏瘫步态时的效果。与足部速度算法相比，使用三种不同运动传感器进行的步态阶段检测是有效的，因为它们的可靠性均超过95%。结果表明，倾斜传感器和陀螺仪传感器在正常个体中能更准确地检测步态阶段。垂直加速度在偏瘫患者A组中检测足跟触地最为准确。陀螺仪传感器在偏瘫患者A组和B组中检测足跟触地和足趾离地最为准确。在患者A组和B组中，从所有传感器信号检测足趾离地都是有效的。然而，垂直加速度在患者A组中有效检测到足跟触地，而陀螺仪传感器在患者B组中有效检测到足跟触地。
