依赖人工监测睡姿的卧床护理效率低下。为了自动收集准确的睡姿信息，并注意改善用户体验和保护用户隐私，通过将理论分析和实验研究相结合，基于柔性压力传感阵列设计了简易、低成本、高精度、快速率的睡姿监测系统。理论上，根据触觉在识别机制上与视觉的相似性，揭示了压力图像分辨率对睡姿分类效果的影响规律；进一步利用公开数据集解析得到24×24的压力传感阵列规模阈值，从而大幅降低了系统的成本和复杂度。实验上，基于柔性压力传感阵列、信号扫描采集电路和睡姿识别算法框架3个模块设计了睡姿监测系统：(1) 以Velostat柔性压敏导电片为核心设计压阻式传感阵列；(2) 以零电势法阵列扫描理论为基础布局抗串扰信号采集电路；(3) 以改进的残差网络训练睡姿分类器。经实验测试，系统对8类睡姿的识别准确率为99.57%，监测速率可达150 ms/帧，有望用于实现商业化的可靠实时睡姿监测。
Bedside care that relies on manual monitoring of sleeping posture is inefficient. To automatically collect accurate sleeping posture information, improve user experience and protect user privacy, a simple, low-cost, high-precision and high-speed sleeping posture monitoring system based on flexible pressure sensing array is designed by combining theoretical analysis and experimental research. Theoretically, according to the similarity between tactile and visual recognition mechanism, the influence of pressure image resolution on the classification effect of sleeping posture is revealed. The 24×24 scale threshold of pressure sensing array is further obtained by analyzing a public dataset, which significantly reduces the cost and complexity of the system. Experimentally, the sleeping posture monitoring system is designed based on 3 modules: flexible pressure sensing array, signal scanning acquisition circuit and sleeping posture recognition algorithm. Firstly, the piezoresistive sensing array is designed based on flexible pressure-sensitive conductive sheet Velostat. Secondly, the anti-crosstalk signal acquisition circuit is arranged based on the zero-potential array scanning method. Thirdly, the sleeping posture classifier is trained with improved residual network. After experimental testing, the recognition accuracy for 8 types of sleeping posture is 99.57%, and the monitoring rate can reach 150 ms/frame. The system is expected to be commercially used for reliable real-time sleeping posture monitoring.