高能效可重构移动健康多传感器接口集成电路研究

大数据智慧医疗的发展期待可穿戴移动健康(m-Health)多传感器系统在疾病监测和保健预防等方面带给人们更多更好的保护与体验。若采用临床上PCB板级合成的方案则难以满足其微型化、高可靠与低功耗等要求。本课题拟融合传感器、集成电路与生物医学知识，探索m-Health多传感器接口系统的单芯片集成理论与方法。首先从传感器敏感结构电学模型及非理想特性的电路补偿着手，探索超低频弱生理信号的获取、放大、去噪与转换方法，通过系统模型、架构、电路与版图实现多层次性能协同优化。第二，探索以可重构方法进行传感器控制、多通道的模块共享、性能参数调控以及依据各通道精度与速度等不同进行功率优化。第三，针对可穿戴环境能源的低能量密度、源内阻与输出电压的时变性与空变性，研究超低压启动、宽动态输入范围与双源同步追踪的高能效高稳定的在片电源管理。项目可为m-Health多传感器系统提供集成电路理论支撑、实现方法和芯片原型。

With the development of big data intelligent medical technology, people are looking forward to getting more，better, deeper protection and experience in disease monitoring and health care from wearable mobile health (m-Health) multi sensor system. It is difficult to meet the requirements of miniaturization, high reliability and low power consumption of m-Health system if one adopts PCB board level synthesis method like the clinic electronic equipment. In this project, we focus on the integration of sensors, integrated circuits and biomedical knowledge, and explore the single chip integration of m-Health multi-sensor interface system. Firstly, based on the electrical model of multi-sensor sensitive structure and the circuit compensation of non ideal characteristics, the acquisition, amplification, de-noising and conversion methods of ultra-low frequency weak physiological signals are studied. Multi-level performance collaborative optimization will be researched through system model, architecture, circuit and layout. Secondly, the reconfigurable method is used to sensors controlling, modules sharing among multi-channel, performance parameters regulating and power optimization according to the accuracy and speed of each sensor channel. Thirdly, in view of the low energy density, time-varying and spatial variability of source resistance and output voltage of environmental energy in wearable applications, high energy efficiency, high stability, ultra-low voltage start-up, wide dynamic input range and dual-source synchronous tracking technology in on-chip power management are studied. This project can provide integrated circuit theory, implementation method and chip prototype for m-health multi-sensor system.