The automatic recognition and counting of cough.
The automatic recognition and counting of cough.
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DOI：
10.1186/1745-9974-2-8
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发表时间：
2006-09-28
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影响因子：
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通讯作者：
Walmsley, Anthony D
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文献类型：
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作者：
Barry, Samantha J;Dane, Adrie D;Morice, Alyn H;Walmsley, Anthony D
咳嗽记录已经进行了很多年，但咳嗽频率的分析和触发因素的时间关系已被证明是有问题的。因为咳嗽是间歇性的，所以需要数小时的数据收集，沿着同样耗时的实时听觉分析。本文提出了一种自动识别和计数录音中咳嗽声的方法。船体自动咳嗽计数器（HACC）是一种用于分析数字音频记录的程序。HACC使用数字信号处理（DSP）来计算声音事件的特征谱系数，然后通过使用概率神经网络（PNN）将声音事件分类为咳嗽和非咳嗽事件。可以根据音频处理的结果来计算作为时间的函数的诸如咳嗽的总数和咳嗽频率的参数。33名吸烟受试者（20名男性和13名女性），年龄在20岁至54岁之间，患有慢性咳嗽，在起床后一小时内使用录音进行了研究。使用图形用户界面（GUI），在一小时的记录中计算HACC识别的咳嗽次数，平均花费1分35秒，计数时间减少97.5%。HACC的敏感性为80%，特异性为96%。重复HACC分析的重现性为100%。已经开发了一种用于分析包含咳嗽和其他非咳嗽事件的声音文件的自动化系统，该系统对于音频记录中的实际咳嗽的数量具有高鲁棒性和良好的准确度。
Cough recordings have been undertaken for many years but the analysis of cough frequency and the temporal relation to trigger factors have proven problematic. Because cough is episodic, data collection over many hours is required, along with real-time aural analysis which is equally time-consuming. A method has been developed for the automatic recognition and counting of coughs in sound recordings. The Hull Automatic Cough Counter (HACC) is a program developed for the analysis of digital audio recordings. HACC uses digital signal processing (DSP) to calculate characteristic spectral coefficients of sound events, which are then classified into cough and non-cough events by the use of a probabilistic neural network (PNN). Parameters such as the total number of coughs and cough frequency as a function of time can be calculated from the results of the audio processing. Thirty three smoking subjects, 20 male and 13 female aged between 20 and 54 with a chronic troublesome cough were studied in the hour after rising using audio recordings. Using the graphical user interface (GUI), counting the number of coughs identified by HACC in an hour long recording, took an average of 1 minute 35 seconds, a 97.5% reduction in counting time. HACC achieved a sensitivity of 80% and a specificity of 96%. Reproducibility of repeated HACC analysis is 100%. An automated system for the analysis of sound files containing coughs and other non-cough events has been developed, with a high robustness and good degree of accuracy towards the number of actual coughs in the audio recording.