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Development of lower limb motion detection based on LPMS

机译:基于LPMS的下肢运动检测开发

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Up to now, with the increasing of the elderly population, more and more patients are suffering from hemiplegia. It leads to a great need for hemiplegic rehabilitation. In traditional rehabilitation, each patient must be treated by therapist, one by one. However, since the individual differences of therapists, no effectiveness rehabilitation is guaranteed. And the rehabilitation status of patient is still diagnosed by therapists with their subjective experience. This would cause the inhomogeneity on rehabilitation evaluation and sometimes negative influence on the rehabilitation effect. To solve these problems, many research groups proposed rehabilitation evaluation systems to assess the status of the hemiplegic patients quantitatively. Rehabilitation motion detection is the basis of the evaluation system, and it requires the participation of therapist. However, many motion detection methods do not meet the detection requirements, such as mechanical tracking and optical sensor, etc. In this article we present a method to detect lower limb motion of hemiplegic patients based on inertial sensor technology. LPMS, a high performance, easy wearable, portable and large measurement range sensor, is selected as the motion sensor. We obtain the gesture quaternion of lower limb through LPMS, and then use the algorithm to convert quaternion to matrix and Euler angle. Combining with the simplified lower limb motion model, we compute the rotation angle of joint by processing the rotation quaternion in Matlab. Finally, the curve of rotation angle of knee is established. The method detecting the motion of lower limb can be integrated into the rehabilitation robot control system, realizing intelligent detection and evaluation. Thus, the rehabilitation robots could be expected adjusting training parameters based on patient status automatically, expected to have significant impacts in medical rehabilitation robot field.
机译:迄今为止,随着老年人口的增加,越来越多的患者出现偏瘫。这导致偏瘫康复的巨大需求。在传统的康复治疗中,每个患者都必须由治疗师一个接一个地治疗。但是,由于治疗师的个体差异,不能保证有效性的康复。并且,治疗师仍可以凭其主观经验来诊断患者的康复状态。这将导致康复评估的不均一性,有时甚至对康复效果产生负面影响。为了解决这些问题,许多研究小组提出了康复评估系统,以定量评估偏瘫患者的状况。康复运动检测是评估系统的基础,需要治疗师的参与。但是,许多运动检测方法不能满足检测要求,例如机械跟踪和光学传感器等。在本文中,我们提出了一种基于惯性传感器技术的偏瘫患者下肢运动检测方法。 LPMS是一种高性能,易磨损,便携式且测量范围大的传感器,被选为运动传感器。通过LPMS获得下肢的手势四元数,然后利用该算法将四元数转换为矩阵和欧拉角。结合简化的下肢运动模型,我们通过在Matlab中处理旋转四元数来计算关节的旋转角度。最后,建立了膝盖的旋转角度曲线。下肢运动检测方法可以集成到康复机器人控制系统中,实现智能检测与评估。因此,可以期望康复机器人根据患者状态自动调整训练参数,从而有望对医学康复机器人领域产生重大影响。

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