Objective: This paper proposes a wearable human motion tracking device using micro flow sensor incorporating a micro accelerometer, which allows detecting postures of human limbs in dynamic motions. Methods: A micro flow sensor is used to detect motion velocity, from which, motion acceleration can be estimated. Thereby, the limb postures are figured out by using the components of the gravity acceleration that are determined by subtracting the motion accelerations from the accelerometer outputs. The motion tracking device is packaged in a watch-type case, which allows it to be wearable. A Kalman filter is employed to implement sensor data fusion. Results: The motion velocity, motion acceleration, and postures of human limbs can be effectively detected by the proposed motion tracking device and methodology. Experiments including human limb tracking are conducted to validate the effectiveness of the proposed device and methodology. Conclusion: The experimental results show that the measurements of human limb motion and posture are feasible and free of accumulative errors. Significance: The flow-aid motion tracking device is wearable, environmental-restriction free, and practicable for long-term monitoring, and provides a promising approach for physical rehabilitation, intelligent prosthesis, personal athletic training, etc.

中文翻译：

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一种使用微流量传感器结合微加速度计的可穿戴人体运动跟踪装置

目的：本文提出了一种可穿戴式人体运动跟踪设备，该设备使用结合了微加速度计的微流量传感器，可以检测动态运动中人体四肢的姿势。方法：使用微流量传感器检测运动速度，由此可以估计运动加速度。因此，通过使用从加速度计输出中减去运动加速度而确定的重力加速度分量来计算肢体姿势。运动跟踪设备封装在手表式外壳中，因此可以佩戴。采用卡尔曼滤波器来实现传感器数据融合。结果：所提出的运动跟踪装置和方法可以有效地检测人体四肢的运动速度、运动加速度和姿势。进行包括人体肢体跟踪在内的实验以验证所提出的设备和方法的有效性。结论：实验结果表明，人体肢体运动和姿势的测量是可行的，没有累积误差。意义：助流运动追踪装置可穿戴、不受环境限制、可长期监测，为身体康复、智能假肢、个人运动训练等提供了一种有前景的方法。