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Sensors:新型模型可根据咳嗽声估计咳嗽峰值流量

2018-07-28 MedSci MedSci原创

咳嗽峰值流量(CPF)是用于评估咳嗽功能障碍风险的测量值,并且可以使用各种装置(例如肺活量计)来测量。然而,复杂的装置设置和需要牢固地附着在嘴上的面罩会给患者及其护理人员带来了不便。因此,本研究开发了一种使用咳嗽声的新型咳嗽强度评估方法。 研究人员提出了一个指数模型用于估计咳嗽峰值声压级(CPSL)的CPF。研究了咳嗽声和咳嗽流之间的关系以及咳嗽声,麦克风类型和参与者身高和性别的测量条件对C

咳嗽峰值流量(CPF)是用于评估咳嗽功能障碍风险的测量值,并且可以使用各种装置(例如肺活量计)来测量。然而,复杂的装置设置和需要牢固地附着在嘴上的面罩会给患者及其护理人员带来了不便。因此,本研究开发了一种使用咳嗽声的新型咳嗽强度评估方法。

研究人员提出了一个指数模型用于估计咳嗽峰值声压级(CPSL)的CPF。研究了咳嗽声和咳嗽流之间的关系以及咳嗽声,麦克风类型和参与者身高和性别的测量条件对CPF估计准确性的影响。

结果证实,该模型评估CPF的精度较高。与麦克风距离患者口腔30厘米以上相比,距离30厘米以内时,CPF与估计CPF之间的绝对误差显著降低。对模型参数的分析表明,估计准确性不受参与者身高或性别的影响。

综上所述,这些结果表明,本研究所提出的模型有可能或可提高CPF的测量和评估。

原始出处:

Umayahara Y, Soh Z, et al., Estimation of Cough Peak Flow Using Cough Sounds. Sensors (Basel). 2018 Jul 22;18(7). pii: E2381. doi: 10.3390/s18072381.

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  1. [GetPortalCommentsPageByObjectIdResponse(id=1793732, encodeId=64391e937324e, content=<a href='/topic/show?id=55ab1613566' target=_blank style='color:#2F92EE;'>#sensor#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=79, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=16135, encryptionId=55ab1613566, topicName=sensor)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=ac59108, createdName=hxj0117, createdTime=Mon May 20 09:29:00 CST 2019, time=2019-05-20, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=336333, encodeId=4bc63363332d, content=新模型,学习了。, beContent=null, objectType=article, channel=null, level=null, likeNumber=93, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://cdnapi.center.medsci.cn/medsci/head/2018/07/16/3b24606172648eea459125cb74754afe.jpg, createdBy=6c022216608, createdName=liumin1987, createdTime=Sat Aug 04 11:03:59 CST 2018, time=2018-08-04, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1047594, encodeId=b8b5104e5949b, content=梅斯里提供了很多疾病的模型计算公式,赞一个!, beContent=null, objectType=article, channel=null, level=null, likeNumber=80, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=f0620, createdName=CHANGE, createdTime=Sat Jul 28 21:29:00 CST 2018, time=2018-07-28, status=1, ipAttribution=)]
    2019-05-20 hxj0117
  2. [GetPortalCommentsPageByObjectIdResponse(id=1793732, encodeId=64391e937324e, content=<a href='/topic/show?id=55ab1613566' target=_blank style='color:#2F92EE;'>#sensor#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=79, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=16135, encryptionId=55ab1613566, topicName=sensor)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=ac59108, createdName=hxj0117, createdTime=Mon May 20 09:29:00 CST 2019, time=2019-05-20, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=336333, encodeId=4bc63363332d, content=新模型,学习了。, beContent=null, objectType=article, channel=null, level=null, likeNumber=93, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://cdnapi.center.medsci.cn/medsci/head/2018/07/16/3b24606172648eea459125cb74754afe.jpg, createdBy=6c022216608, createdName=liumin1987, createdTime=Sat Aug 04 11:03:59 CST 2018, time=2018-08-04, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1047594, encodeId=b8b5104e5949b, content=梅斯里提供了很多疾病的模型计算公式,赞一个!, beContent=null, objectType=article, channel=null, level=null, likeNumber=80, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=f0620, createdName=CHANGE, createdTime=Sat Jul 28 21:29:00 CST 2018, time=2018-07-28, status=1, ipAttribution=)]
    2018-08-04 liumin1987

    新模型,学习了。

    0

  3. [GetPortalCommentsPageByObjectIdResponse(id=1793732, encodeId=64391e937324e, content=<a href='/topic/show?id=55ab1613566' target=_blank style='color:#2F92EE;'>#sensor#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=79, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=16135, encryptionId=55ab1613566, topicName=sensor)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=ac59108, createdName=hxj0117, createdTime=Mon May 20 09:29:00 CST 2019, time=2019-05-20, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=336333, encodeId=4bc63363332d, content=新模型,学习了。, beContent=null, objectType=article, channel=null, level=null, likeNumber=93, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://cdnapi.center.medsci.cn/medsci/head/2018/07/16/3b24606172648eea459125cb74754afe.jpg, createdBy=6c022216608, createdName=liumin1987, createdTime=Sat Aug 04 11:03:59 CST 2018, time=2018-08-04, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1047594, encodeId=b8b5104e5949b, content=梅斯里提供了很多疾病的模型计算公式,赞一个!, beContent=null, objectType=article, channel=null, level=null, likeNumber=80, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=f0620, createdName=CHANGE, createdTime=Sat Jul 28 21:29:00 CST 2018, time=2018-07-28, status=1, ipAttribution=)]
    2018-07-28 CHANGE

    梅斯里提供了很多疾病的模型计算公式,赞一个!

    0

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