Feng Mengling, Zhang Zhuo, Zhang Feng, Ge Yu, Loy Liang Yu, Vellaisamy Kuralmani, Guo Wenyuan, Chin Pei Loon, King Nicolas Kon Kam, Ang Beng Ti, Guan Cuntai
Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:6426-9. doi: 10.1109/IEMBS.2011.6091586.
Close monitoring and timely treatment are extremely crucial in Neuro Intensive/Critical Care Units (NICUs) to prevent patients from secondary brain damages. However, the current clinical practice is labor-intensive, prone to human errors and ineffective. To address this, we developed an integrated and intelligent system, namely iSyNCC, to enhance the effectiveness of patient monitoring and clinical decision makings in NICUs. The requirements of the system were investigated through interviews and discussions with neurosurgeons, neuroclinicians and nurses. Based on the summarized requirements, a modular 2-tier system is developed. iSyNCC integrates and stores crucial patient information ranging from demographic details, clinical & treatment records to continuous physiological monitoring data. iSyNCC enables remote and centralized patient monitoring and provides computational intelligence to facilitate clinical decision makings.
在神经重症监护病房(NICUs)中,密切监测和及时治疗对于防止患者发生继发性脑损伤极为关键。然而,当前的临床实践劳动强度大,容易出现人为错误且效率低下。为了解决这一问题,我们开发了一个集成智能系统,即iSyNCC,以提高NICUs中患者监测和临床决策的有效性。通过与神经外科医生、神经临床医生和护士进行访谈和讨论,对该系统的需求进行了调查。基于总结出的需求,开发了一个模块化的两层系统。iSyNCC整合并存储从人口统计学细节、临床和治疗记录到连续生理监测数据等关键患者信息。iSyNCC支持远程和集中式患者监测,并提供计算智能以促进临床决策。