关键词: 人体姿态识别, 传感网, 加速度传感器, 随机森林, 蜜蜂交配优化

Abstract: Adapting to the problem on the static property and easy convergence to local optima of traditional random forest algorithm, a honey-bee mating optimization random forest algorithm is proposed, and it is used to recognize the human motion patterns that is based on an acceleration sensor. A data collect system that is consist of a 3D acceleration sensor MMA7260 and wireless communication module CC2430 is designed, and is used to collect five daily activity and one abnormal behavior. Then, five features（Approximation Slope, Front and Rear Subtract, mean, RMS and SMA） are extracted from the acceleration signal. Finally, the improved random forest algorithm is adopted as a classifier. The experimental results have confirmed that the proposed algorithm is effective to recognize the six activity, meanwhile, the algorithm has achieved high classification prediction accuracy and recognition rate, and it has stronger stabile, robustness, ability of global optimal and anti-noise.

Key words: human posture pattern, sensor network, acceleration sensor, random forest, honey-bee mating optimization