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Development of lower limb motion detection based on LPMS

机译:基于LPMS的下肢运动检测的开发

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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:到目前为止,随着年长人口的增加,越来越多的患者患有偏瘫。它导致对偏瘫康复的巨大需求。在传统的康复中,每个患者必须由治疗师治疗一个接一个。然而,由于治疗师的个体差异,没有保证康复的有效性。患者的康复状态仍然被治疗师诊断出他们的主观经验。这将导致对康复评估的不均匀性,有时对康复效应产生负面影响。为解决这些问题,许多研究组提出了康复评估系统,以定量评估偏瘫患者的状态。康复运动检测是评估系统的基础,它需要治疗师的参与。然而,许多运动检测方法不符合检测要求,例如机械跟踪和光学传感器等。在本文中,我们介绍了一种基于惯性传感器技术检测偏瘫患者的下肢运动的方法。 LPMS,高性能,易穿戴,便携式和大的测量范围传感器被选为运动传感器。我们通过LPM获取下肢的手势四元数,然后使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接头的旋转角度。最后,建立了膝关节旋转角度的曲线。检测下肢运动的方法可以集成到康复机器人控制系统中,实现智能检测和评估。因此,可以预期康复机器人可以自动地根据患者状态调整培训参数,预计在医疗康复机器人场中会产生重大影响。

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