基于机器学习的在押人员生命体征监测系统设计

Design of Vital Signs Monitoring System for Detainees Based on Machine Learning

设计一种基于机器学习算法的在押人员生命体征监测系统。该系统包括智能手环、智能指环和智能胸带三部分组成,主要用来实现对心率、心电、血氧和血压等生命指标进行数据采集,并结合无线传感网技术实现可穿戴终端设备与后台应用服务的数据通信和交互。最后采用人工神经网络算法对生理数据进行训练并建立健康风险模型,以此实现对监所内高危人群的突发性疾病进行风险防控和实时预警。

Designs a detainee vital sign monitoring system based on machine learning algorithm.The system consists of a smart bracelet,a smart ring and a smart chest strap.Mainly used to collect data on life indicators such as heart rate,ECG,blood oxygen and blood pressure,Combined with wireless sensor network technology,data communication and interaction between wearable terminal devices and background application services are realized.Finally,the artificial neural network algorithm is used to train the physiological data and establish a health risk model,so as to realize the risk prevention and control and real-time warning for the sudden diseases of high-risk groups in the prison.