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用于开发动态咳嗽监测设备的技术。

Technologies for developing ambulatory cough monitoring devices.

作者信息

Amoh Justice, Odame Kofi

机构信息

Analog Laboratory, Thayer School of Engineering, Dartmouth College, Hanover, NH.

出版信息

Crit Rev Biomed Eng. 2013;41(6):457-68.

Abstract

Cough is a prevailing symptom in most lung diseases. While cough sounds themselves can be very instrumental in the diagnosis of certain diseases, their intensity and frequency also infers the intensity of the particular illness. There is an imperative need for a robust system for identifying and analyzing cough sounds. In implementing such systems, researchers are confronted with technical challenges such as the choice of sensors and methods of signal acquisition, the real time analysis of the acquired signals, and the accurate identification of cough events, distinguishing them from similar sounds such as speech, laughing, throat clearing and sneezing. Previous approaches have employed external environmental sensing methods to achieve more accurate detections at the expense of mobility, scalability and real-time cough sensing. Alternative approaches have proposed wearable cough sensing methods, which, while mobile, can often face challenges in terms of robustness and obtrusiveness. In this paper, we explore the strengths and shortcomings of the various techniques that have been proposed for automatic detection and analysis of cough sounds. We also suggest the next steps in furthering the state of the art.

摘要

咳嗽是大多数肺部疾病的常见症状。虽然咳嗽声音本身对某些疾病的诊断非常有帮助,但其强度和频率也能推断出特定疾病的严重程度。迫切需要一个强大的系统来识别和分析咳嗽声音。在实施这样的系统时,研究人员面临着技术挑战,如传感器的选择和信号采集方法、对采集信号的实时分析,以及准确识别咳嗽事件,将其与语音、笑声、清嗓和打喷嚏等类似声音区分开来。以前的方法采用外部环境传感方法来实现更准确的检测,但牺牲了移动性、可扩展性和实时咳嗽传感。替代方法提出了可穿戴咳嗽传感方法,虽然具有移动性,但在鲁棒性和干扰性方面往往面临挑战。在本文中,我们探讨了已提出的用于自动检测和分析咳嗽声音的各种技术的优缺点。我们还提出了推动该领域技术发展的下一步措施。

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