为实现住院患者连续生命体征监测，研制了随行生理参数监护系统 SensEcho。该系统由随行生理参数监测终端、无线组网和数据传输单元、中央监护系统三部分组成。其中随行生理参数监测终端为一件柔性背心，内嵌有呼吸感应体积描记传感器和织物心电电极，实现心电、呼吸、体位和体动等基本生理参数的穿戴式低负荷监测；无线生理信号传输单元为基于 WiFi 技术的组网系统，能够实现病区内多个患者的移动监护，并设计有多重数据续传和数据完整性保障机制；中央监护系统实现所有随行生理参数监测终端数据的显示和患者集中管理，设计有后台数据服务器和算法服务器，支持医疗大数据深度挖掘分析应用。为验证系统性能，我们开展了生理参数检测算法有效性和受试者可靠性测试，以及无线组网和数据传输可靠性测试。测试结果显示，系统无论在基本生理参数监测还是无线数据传输方面都能达到可靠性要求。该系统在医疗领域的应用有望开启个体化连续生命体征监护医疗新模式，为疾病诊断提供基于连续动态生理数据分析的精准信息。
To achieve continuously physiological monitoring on hospital inpatients, a ubiquitous and wearable physiological monitoring system SensEcho was developed. The whole system consists of three parts: a wearable physiological monitoring unit, a wireless network and communication unit and a central monitoring system. The wearable physiological monitoring unit is an elastic shirt with respiratory inductive plethysmography sensor and textile electrocardiogram (ECG) electrodes embedded in, to collect physiological signals of ECG, respiration and posture/activity continuously and ubiquitously. The wireless network and communication unit is based on WiFi networking technology to transmit data from each physiological monitoring unit to the central monitoring system. A protocol of multiple data re-transmission and data integrity verification was implemented to reduce packet dropouts during the wireless communication. The central monitoring system displays data collected by the wearable system from each inpatient and monitors the status of each patient. An architecture of data server and algorithm server was established, supporting further data mining and analysis for big medical data. The performance of the whole system was validated. Three kinds of tests were conducted: validation of physiological monitoring algorithms, reliability of the monitoring system on volunteers, and reliability of data transmission. The results show that the whole system can achieve good performance in both physiological monitoring and wireless data transmission. The application of this system in clinical settings has the potential to establish a new model for individualized hospital inpatients monitoring, and provide more precision medicine to the patients with information derived from the continuously collected physiological parameters.