基于超宽带和惯性传感融合的运动捕捉技术研究及康复应用

可穿戴式惯性人体运动捕捉设备在运动健康和康复医疗领域具有广泛应用前景，因为其可以在各种环境中监测用户的活动，不受光学遮挡影响。然而，现有技术在无线信号复杂的环境中容易出现丢包现象、以及长时间使用会导致定位漂移等问题，从而影响运动捕捉系统的稳定性和精度。本研究旨在引入超宽带通讯技术（UWB），实现强抗干扰能力和高精度的运动捕捉。重点研究如何构建具有强抗干扰能力的无线体传感器网络系统，以及如何在复杂干扰场景下实现高精度姿态测量和位置测量。为此，本研究开发了一套基于UWB技术和MEMS惯性传感器（IMU）的运动捕捉系统——iCapturer。通过应用UWB-IMU多传感器融合的姿态追踪、定位算法以及人体姿态解算算法，实现了对人体动作的稳定捕捉。本研究还将iCapturer系统应用于康复领域，并通过人体试验对其效果进行验证。本课题的主要贡献包括设计了一套UWB-IMU融合的体传感器网络系统，提出了适用于该系统的姿态解算算法、UWB-IMU定位融合算法，并通过仿真实验进行验证。此外，通过人体试验，验证了所提出系统的运动捕捉精度，并进行了初步的康复相关应用测试，证实了其在临床应用中的可行性。基于UWB-IMU融合的iCapturer系统具备实际场景应用潜力，为康复医疗领域提供了一种创新的运动捕捉和评估工具，有望为患者和专业人员带来更多便利。

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