融合语音和脑电的智慧病房控制系统
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广东省重点研发计划(2018B030339001); 广州市科技计划重点领域研发计划(202007030005); 国家自然科学基金(61876067); 广东省自然科学基金(2019A1515011375)


Smart Ward Control System Integrating Speech and EEG
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    摘要:

    在智能化技术革新各个传统行业的过程中, 对于传统病房护理人们提出了更高水平的服务诉求. 在传统病房实地调研的基础上, 为了提高患者日常病房生活中的自理能力, 加强医护和家属对病人生活状况的实时监控, 结合现有物联网智能控制技术, 本文提出一种融合语音和脑电的智慧病房控制系统, 实现了病房电器等基础设施的控制和云端病房实时监测. 此外, 基于眨眼动作的ElectroEncephaloGraphy (EEG)控制方法在一定程度上解决了对患者身体状况的更高要求的问题. 根据涉及10名受试者的两个实验, 语音识别的准确度达到98%, 对健康人和患者基于脑电的眨眼识别的准确率分别为94.3%和82.9%. 结果表明, 该系统能够在病房这类复杂环境下稳定运行, 为患者提供更加智能舒适的疗养环境.

    Abstract:

    People put forward a higher service demand for traditional ward care in the process of intelligent technology reforming various traditional industries. According to the field investigation of traditional wards, the self-care ability of patients should be improved in daily ward life and the real-time monitoring of their living conditions by medical staff as well as families is waiting to be strengthened. To this end, this study proposes a smart ward control system integrating speech and ElectroEncephaloGraphy (EEG) and combined with the Internet of Things (IoT), thereby realizing the control of infrastructures such as ward appliances and real-time monitoring of cloud wards. Furthermore, the EEG-based control method based on eye blinks can meet the higher requirement for a patient’s physical conditions. According to the two experiments involving 10 subjects, speech recognition achieved an accuracy of 98%, and the accuracy of EEG-based blink recognition for healthy people and patients is 94.3% and 82.9%. The results show that the system can operate stably in complex environments such as wards, providing patients with a more intelligent and comfortable convalescent environment.

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蔡旭刚,王磊,王帆,李俊廷,潘家辉.融合语音和脑电的智慧病房控制系统.计算机系统应用,2021,30(11):71-81

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  • 收稿日期:2021-01-12
  • 最后修改日期:2021-02-07
  • 在线发布日期: 2021-10-22
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