基于软件定义智能的睡眠动作识别

Sleep Action Recognition Based on Software-Defined Intelligence

基于软件定义智能层次化模型设计了一种睡眠动作识别系统,该系统可通过规则推理来应对智能环境中的各种变化因素.设计了一种时间队列实时提取动作特征来训练模型,提出了一种规则提取算法从该模型中提取系统所需规则.该系统基于这些规则可识别9种睡眠动作,每种动作的识别精确率均可达到96%以上,总识别准确率达到98.9%,且比其它系统适应性更强.实验结果表明,该系统通过更新规则可快速应对节点位置、节点数量和用户需求的变化.

Based on the hierarchical model of SDI(Software-Defined Intelligence),a system for action recognition during sleep is designed to deal with various changing factors in smart environment through rule-based reasoning.A time queue is designed to extract the characteristics of actions in real-time to train the model,and a rule extraction algorithm is proposed to extract the rules required by the system from the model.Depending on these rules,the proposed system can recognize nine types of sleep actions:the recognition precision of each type can exceed 96%;the total recognition accuracy can reach 98.9%.Importantly,it has more robust adaptability than other systems.Experimental results show that the system can update rules for quickly adapting to changes in node position,the number of nodes,and user requirements.