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首页> 外文会议>IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics >Development of an abnormal gait analysis system in gait exercise assist robot “Welwalk” for hemiplegic stroke patients
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Development of an abnormal gait analysis system in gait exercise assist robot “Welwalk” for hemiplegic stroke patients

机译：偏瘫中风患者步态辅助机器人“ Welwalk”中异常步态分析系统的开发

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Welwalk WW-1000 is a gait exercise robotic assist system that allows subjects to walk on treadmill by attaching a knee-ankle-foot robot to a paralyzed limb. Abnormal gait patterns during exercise using Welwalk WW-1000 are evaluated by gait observation or marker-based motion analysis systems. However, gait observation is a subjective and ordinal measure, and marker-based motion analysis systems are challenging to implement due to the complexity of preparing equipment and attaching markers to subjects. In this study, we propose the Welwalk WW-2000 system, which incorporated a marker-less motion analysis system that detects abnormal gait patterns during exercise using the robotic system. Using this system, it is expected that a gait exercise program can be planned from easily obtainable, objective information. This system detects the features of abnormal gait patterns using the body position coordinates of the subject obtained from three-dimensional, inertial, knee angle, and load sensors. The purpose of this study was to validate the marker-less motion analysis system against marker-based motion analysis systems. One healthy male simulated the seven abnormal gait patterns which occur frequently in stroke patients, with four grades of severity. Spearman"s rank correlation coefficients were calculated for the relationship between the abnormal gait pattern parameters calculated by each motion analysis system. The correlations between the two systems ranged from 0.81 to 0.95. Therefore, it was confirmed that the marker-less motion analysis system of the Welwalk WW-2000 was valid.
机译：Welwalk WW-1000是一种步态锻炼机器人辅助系统，通过将膝盖，脚踝，脚踝机器人附着到瘫痪的肢体上，受试者可以在跑步机上行走。使用步态观察或基于标记的运动分析系统评估使用Welwalk WW-1000进行运动时的异常步态模式。然而，步态观察是一种主观和有序的措施，基于标记的运动分析系统由于准备设备和将标记物附着到受试者的复杂性而难以实施。在这项研究中，我们提出了Welwalk WW-2000系统，该系统结合了无标记运动分析系统，该系统使用机器人系统检测运动过程中的异常步态模式。使用该系统，可以从容易获得的客观信息中计划步态锻炼程序。该系统使用从三维，惯性，膝盖角度和负荷传感器获得的对象的身体位置坐标来检测异常步态模式的特征。本研究的目的是针对基于标记的运动分析系统来验证无标记运动分析系统。一名健康的男性模拟了中风患者中频繁发生的七种异常步态模式，严重程度分为四个等级。对于每个运动分析系统计算出的异常步态模式参数之间的关系，计算了Spearman等级相关系数。两个系统之间的相关性介于0.81至0.95之间。 Welwalk WW-2000有效。

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