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通过声学分析进行家庭筛查的睡眠呼吸暂停自动识别。

Automatic identification of apnea through acoustic analysis for at-home screening.

机构信息

Department of Medical and Welfare Management, Koshien University, Takarazuka, Hyogo, Japan.

出版信息

Telemed J E Health. 2011 Jul-Aug;17(6):467-71. doi: 10.1089/tmj.2010.0207. Epub 2011 Jun 1.

Abstract

OBJECTIVE

Although many studies have analyzed breathing sounds in the diagnosis of obstructive sleep apnea syndrome, the recording of snoring sounds at home is hampered by the various background noises of daily life. Recordings also frequently include talking during sleep, which may infringe the privacy of patients.

MATERIALS AND METHODS

A recording system used a bone conduction microphone to record snoring sounds. This microphone reduced background noise. A simple system transmitted recorded breathing sound data for screening at a hospital as envelope data instead of complete sound recordings, thereby decreasing data volume and protecting privacy.

RESULTS

In periods in which blood oxygen levels (SpO₂) were drastically decreased, the probability of apnea as deduced from the envelope curve of breathing sounds was consistent with SpO₂ values.

CONCLUSIONS

This method provides a basis for telemonitoring of sleep apnea syndrome.

摘要

目的

尽管许多研究已经分析了呼吸音在阻塞性睡眠呼吸暂停综合征诊断中的应用,但由于日常生活中的各种背景噪音,在家中录制打鼾声受到了阻碍。此外,录制的声音还经常包含睡眠中的说话声,这可能侵犯了患者的隐私。

材料与方法

记录系统使用骨传导麦克风来记录打鼾声。该麦克风降低了背景噪音。一个简单的系统将记录的呼吸声数据作为包络数据传输到医院进行筛查,而不是完整的录音,从而减少了数据量并保护了隐私。

结果

在血氧水平(SpO₂)急剧下降的时期,从呼吸声的包络曲线推断出的呼吸暂停的概率与 SpO₂值一致。

结论

该方法为睡眠呼吸暂停综合征的远程监测提供了依据。

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