如何发现 COVID-19 患者:用于 SARS-COV-2 冠状病毒患者初步诊断的语音和声音音频分析。

How to spot COVID-19 patients: Speech & sound audio analysis for preliminary diagnosis of SARS-COV-2 corona patients.

机构信息

Department of Pharmacy Practice, ISF College of Pharmacy, Moga, Punjab, India.

Uttarakhand Technical University, Dehradun, Uttarakhand, India.

出版信息

Int J Clin Pract. 2021 Jun;75(6):e14134. doi: 10.1111/ijcp.14134. Epub 2021 Mar 21.

Abstract

BACKGROUND

The global cases of COVID-19 increasing day by day. On 25 November 2020, a total of 59 850 910 cases reported globally with a 1 411 216 global death. In India, total cases in the country now stand at 91 77 841 including 86 04 955 recoveries and 4 38 667 active cases as on 24 November 2020, as per the data issued by ICMR. A new generation of voice/audio analysis application can tell whether the person is suffering from COVID-19 or not.

AIMS

To describe how to established a new generation of voice/audio analysis application to identify the suspected COVID-19 hidden cases in hotspot areas with the help of an audio sample of the general public.

MATERIALS & METHODS: The different patents and data available as literature on the internet are evaluated to make a new generation of voice/audio analysis application with the help of an audio sample of the general public.

RESULTS

The collection of the audio sample will be done from the already suffered COVID-19 patients in (.Wave files) personally or through phone calls. The audio samples such as the sound of the cough, the pattern of breathing, respiration rate and way of speech will be recorded. The parameters will be evaluated for loudness, articulation, tempo, rhythm, melody and timbre. The analysis and interpretation of the parameters can be made through machine learning and artificial intelligence to detect corona cases with an audio sample.

DISCUSSION

The voice/audio application current project can be merged with a mobile App called 'AarogyaSetu' by the Government of India. The project can be implemented in the high-risk area of COVID-19 in the country.

CONCLUSION

This new method of detecting cases will decrease the workload in the COVID-19 laboratory.

摘要

背景

全球 COVID-19 病例日益增加。截至 2020 年 11 月 25 日,全球报告的病例总数为 5985.091 万,全球死亡人数为 141.1216 万。根据 ICMR 发布的数据,截至 2020 年 11 月 24 日,印度全国病例总数为 917.7841 万,其中 860.4955 万人康复,43.8667 万人为活跃病例。新一代的语音/音频分析应用程序可以判断一个人是否患有 COVID-19。

目的

描述如何建立一个新的语音/音频分析应用程序,通过公众的音频样本识别热点地区疑似 COVID-19 的隐匿病例。

材料和方法

评估互联网上的不同专利和可用数据,以帮助公众获取音频样本,开发新一代的语音/音频分析应用程序。

结果

将从已经感染 COVID-19 的患者个人或通过电话中收集音频样本。将记录咳嗽声、呼吸模式、呼吸频率和说话方式等音频样本。将评估参数的响度、清晰度、节奏、韵律、旋律和音色。通过机器学习和人工智能分析和解释参数,以利用音频样本检测冠状病毒病例。

讨论

目前的语音/音频应用项目可以与印度政府的“AarogyaSetu”移动应用程序合并。该项目可以在该国 COVID-19 高风险地区实施。

结论

这种新的病例检测方法将减少 COVID-19 实验室的工作量。

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