发帖
雷达卡
摘要翻译：
一项全面的调查显示，许多急性心肌梗死患者很晚才到达医院进行有效的治疗。这导致治疗效果不佳，增加了死亡率。农村卫生保健中心缺乏诊断设施，急诊室缺乏心脏病专家等多重原因阻碍了及时治疗。本研究旨在建立一套有效的急性心肌梗塞院前管理系统。早期溶栓治疗心肌梗塞的有效性已得到充分证实，尤其是在降低死亡率方面的积极作用。我们提出的系统利用远程心电图技术，使心脏病专家能够在远离医疗中心的地方分析病人的信号。该系统利用internet网络将采集到的心电信号和一些生命体征传输到医疗中心。为了对记录的数据进行复查和分析，本系统增加了心电查看器软件。自动测量算法和一些附加工具嵌入到心电检测仪中，为医学中心心内科医生分析心电信号提供了一个方便的平台。所设计的系统已在德黑兰应急服务中心进行了原型测试。该系统在记录、传输和准确分析心电信号以早期诊断急性心肌梗死方面取得了良好的效果。
---
英文标题：
《Pre-Hospital Management of Acute Myocardial Infarction Using
Tele-Electrocardiography System》
---
作者：
Masoud Elhami Asl, Masoomeh Rahimpour, Mahmoud Reza Merati, Amir
Hossein Panahi, Kamran Gholami
---
最新提交年份：
2018
---
分类信息：
一级分类：Electrical Engineering and Systems Science 电气工程与系统科学
二级分类：Signal Processing 信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
--
---
英文摘要：
A comprehensive survey revealed that many patients of Acute Myocardial Infarction reach to the hospital so late to deliver an effective treatment. This leads to poor treatment outcome which increases the mortality rates. Multiple reasons such as lack of diagnostic facilities in the rural health care centers and absence of cardiologists in Emergency Rooms inhibit the timely treatment. In this study, we aimed to develop an effective system to pre-hospital management of Acute Myocardial Infarction. The effectiveness of early thrombolysis in Myocardial Infarction is well established, particularly with regard to its positive effect on reducing the mortality rates. Our proposed system by using tele-electrocardiography technology enables cardiologist to analyze the patient's signal far away from a medical center. This system transmits the collected ECG signal as well some vital signs to the medical center by using internet network. In order to review and analyze the recorded data, an ECG Viewer software is added to this system. The automatic measurement algorithm and some additional tools embedded in the ECG Viewer provide a convenient platform for ECG signal analysis by the cardiologist in the medical center. The designed system has been tested as a prototype in Tehran Emergency Service Center. The evaluation of the proposed system shows acceptable results in recording, transmission, and accurate analysis of ECG signals to early diagnosis of Acute Myocardial Infarction.
---
PDF链接：
https://arxiv.org/pdf/1805.05913
京公网安备 11010802022788号
