用于即时医疗系统中以患者为中心的决策的无线生物信号采集设备的自动化集成。
Automated integration of wireless biosignal collection devices for patient-centred decision-making in point-of-care systems.
作者信息
Menychtas Andreas, Tsanakas Panayiotis, Maglogiannis Ilias
机构信息
R&D Dept., BioAssist S.A., Athens 11524, Greece; Dept of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece.
Dept of Electrical and Computer Engineering , National Technical University of Athens , Athens , Greece.
出版信息
Healthc Technol Lett. 2016 Mar 23;3(1):34-40. doi: 10.1049/htl.2015.0054. eCollection 2016 Mar.
The proper acquisition of biosignals data from various biosensor devices and their remote accessibility are still issues that prevent the wide adoption of point-of-care systems in the routine of monitoring chronic patients. This Letter presents an advanced framework for enabling patient monitoring that utilises a cloud computing infrastructure for data management and analysis. The framework introduces also a local mechanism for uniform biosignals collection from wearables and biosignal sensors, and decision support modules, in order to enable prompt and essential decisions. A prototype smartphone application and the related cloud modules have been implemented for demonstrating the value of the proposed framework. Initial results regarding the performance of the system and the effectiveness in data management and decision-making have been quite encouraging.
从各种生物传感器设备正确采集生物信号数据及其远程可访问性，仍然是阻碍即时护理系统在慢性病患者日常监测中广泛应用的问题。本文提出了一个先进的框架，用于实现患者监测，该框架利用云计算基础设施进行数据管理和分析。该框架还引入了一种本地机制，用于从可穿戴设备和生物信号传感器统一采集生物信号，以及决策支持模块，以便能够做出及时且重要的决策。已经实现了一个原型智能手机应用程序和相关的云模块，以展示所提出框架的价值。关于系统性能以及数据管理和决策有效性的初步结果相当令人鼓舞。
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