基于步态检测算法的辅助行走系统设计

为了保证盲人和视障患者安全方便出行和减少误报警，设计一种基于步态检测算法的辅助行走系统。信号处理算法上利用小波包对信号进行降噪，提取三轴加速度的均值、标准差、方差与小波能量谱，并结合足底压力信息组成多维参数作为步态特征，选取基于遗传算法优化支持向量机进行步态识别。硬件部分主要包括三轴加速度信号和足底压力信号采集硬件设计。软件部分主要包括对足底压力信号和三轴加速度信号的采集和处理以及一款能够自动拨号安卓手机APP。实验结果表明，该系统基于多传感器融合的步态检测技术，步态检测识别率平均达90.48%。该系统便携性好、功耗低、测障效果好，在辅助行走领域具有一定的研究意义和实用价值。

Design of Walking Auxiliary System Based on Gait Detection Algorithm

To ensure the safety of blind and visually impaired patients and reduce false alarms in the process of obstacle avoidance, a walking auxiliary system based on gait detection algorithm is designed. In the signal processing algorithm, wavelet packet is used to reduce the noise of the signal, the mean value, standard deviation, variance and wavelet energy of the three-axis acceleration are extracted, and multi-dimensional parameters are constituted as the gait characteristics by combining the information of foot pressure. Then, the optimized multi-classification support vector machine algorithm based on genetic algorithm is selected to train and identify the gait. The hardware part mainly consists of three-axis acceleration signal and plantar pressure signal acquisition hardware design. The software part mainly includes the acquisition and processing of the plantar pressure signal and three-axis acceleration signals and an android phone APP which can dial automatically. Experimental results show that the proposed system is based on the gait detection technology of multi-sensor fusion, with an average gait recognition rate of 90.48%. The system has good portability, low power consumption, good obstacle detection effect, and has certain research significance and practical value in the field of auxiliary walking.