关键词: 活动识别, 加速度, 陀螺仪, 统计学习模型

Abstract: Activity recognition is a fundamental and challenging topic in context-aware applications. However, the current research on activity recognition cannot obtain satisfactory results by considering the complexity and diversity of human activity. To solve this problem, a novel method for activity recognition is proposed. The method extracts feature vector from three-dimensional acceleration sensor and gyro sensor of smart-phone, then construct recognition models based on four typical statistical methods（namely, K-nearest neighbor algorithm, support vector machines, naive bayes networks and AdaBoost） respectively, and finally select the optimal recognition model according to model evaluation and comparison. Experimental results show that the proposed method achieved good performance and the accuracy rate of activity recognition is 92%.

Key words: activity recognition, acceleration, gyroscope, statistical learning model