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.