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A model based stroke rehabilitation monitoring system using inertial navigation systems

机译：使用惯性导航系统的基于模型的中风康复监测系统

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摘要

In this thesis, a low-cost rehabilitation monitoring system based on Inertial Navigation System (INS) techniques is developed. The purpose of this system is to provide practitioners with data sufficient-enough to characterise a post-stroke patient’s arm motion. We propose an inertial sensor-based system to characterize the motion trajectory. The system is composed of two main components: joint angle estimation and local positioning of points of interest. Joint angles are estimated using an Extended Kalman Filter by fusing data from different sensors. Local positioning is done using forward kinematic solutions: homogenous transformation, Denavit Hartenberg’s method and dual quaternions that approximating the arm as a serial robot. As a result, the relative joint angles and 3D positioning of points of interests on the human are calculated accurately. The data obtained prove useful for reconstructing the arm’s three-dimensional motion trajectories and provide feedback to stroke survivor patients or (remotely) the rehabilitation practitioner.
机译：本文开发了一种基于惯性导航系统（INS）技术的低成本康复监测系统。该系统的目的是为从业人员提供足够的数据，以表征中风后患者的手臂运动。我们提出了一种基于惯性传感器的系统来表征运动轨迹。该系统由两个主要部分组成：关节角度估计和关注点的局部定位。通过融合来自不同传感器的数据，使用扩展卡尔曼滤波器估计关节角度。本地定位是使用正向运动学解决方案完成的：同质变换，Denavit Hartenberg的方法和双四元数，这些四元数逼近了作为串行机器人的手臂。结果，准确地计算了人体上的兴趣点的相对关节角度和3D位置。所获得的数据证明对重建手臂的三维运动轨迹很有用，并且可以为中风幸存者患者或（远程）康复从业者提供反馈。

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