James C Borders, Jessica E Huber, Michelle S Troche
{"title":"估计咳嗽时肺容量:呼吸校准任务和方法的比较。","authors":"James C Borders, Jessica E Huber, Michelle S Troche","doi":"10.1044/2025_JSLHR-25-00237","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Effective cough function requires sufficient respiratory support. To estimate lung volume, respiratory inductance plethysmography measures circumferential changes of the rib cage (RC) and abdomen (AB) during various behaviors, such as coughing. During speech breathing, the accuracy of these estimates is influenced by calibration tasks and analysis methods. Measurement error can introduce bias and confound results, yet the optimal approach for assessing lung volume during cough remains unclear.</p><p><strong>Method: </strong>Twenty participants with Parkinson's disease (<i>M</i><sub>age</sub> = 69 years; <i>M</i> disease duration = 11.39 years) completed three respiratory calibration tasks: (a) rest breathing, (b) cough-like breathing (\"breathe in like you're going to cough, then breathe out forcefully without coughing\"), and (c) single voluntary coughs (\"cough hard one time\"). Lung volume estimation error was calculated by comparing the estimated lung volume signal to the spirometry signal across tasks and task combinations. Error was also assessed across three analysis methods: the Banzett method (2:1 weighting for RC and AB) and two least squares methods-one correcting for both the RC and AB signals (LsqRC/AB) and another holding the AB constant (LsqRC).</p><p><strong>Results: </strong>Mean lung volume estimation error was 4.68% for LsqRC/AB, 9.88% for LsqRC, and 14.24% for the Banzett method. LsqRC/AB yielded significantly lower estimation error than both the LsqRC (<i>p</i> < .001, <i>d</i> = -1.14) and Banzett methods (<i>p</i> < .001, <i>d</i> = 1.69). Calibration task had no significant effect on estimation error (<i>p</i> = .889).</p><p><strong>Conclusions: </strong>The least squares method correcting for both the RC and AB (LsqRC/AB) provides the most precise lung volume estimates during cough. Error associated with the Banzett method exceeded previously reported values for speech breathing by more than 50%. Additional calibration tasks beyond rest breathing may not be necessary to meaningfully reduce lung volume error for cough measurement.</p><p><strong>Open science form: </strong>https://doi.org/10.23641/asha.29657360.</p>","PeriodicalId":520690,"journal":{"name":"Journal of speech, language, and hearing research : JSLHR","volume":" ","pages":"4290-4296"},"PeriodicalIF":2.2000,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimating Lung Volume During Cough: A Comparison of Respiratory Calibration Tasks and Methodologies.\",\"authors\":\"James C Borders, Jessica E Huber, Michelle S Troche\",\"doi\":\"10.1044/2025_JSLHR-25-00237\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>Effective cough function requires sufficient respiratory support. To estimate lung volume, respiratory inductance plethysmography measures circumferential changes of the rib cage (RC) and abdomen (AB) during various behaviors, such as coughing. During speech breathing, the accuracy of these estimates is influenced by calibration tasks and analysis methods. Measurement error can introduce bias and confound results, yet the optimal approach for assessing lung volume during cough remains unclear.</p><p><strong>Method: </strong>Twenty participants with Parkinson's disease (<i>M</i><sub>age</sub> = 69 years; <i>M</i> disease duration = 11.39 years) completed three respiratory calibration tasks: (a) rest breathing, (b) cough-like breathing (\\\"breathe in like you're going to cough, then breathe out forcefully without coughing\\\"), and (c) single voluntary coughs (\\\"cough hard one time\\\"). Lung volume estimation error was calculated by comparing the estimated lung volume signal to the spirometry signal across tasks and task combinations. Error was also assessed across three analysis methods: the Banzett method (2:1 weighting for RC and AB) and two least squares methods-one correcting for both the RC and AB signals (LsqRC/AB) and another holding the AB constant (LsqRC).</p><p><strong>Results: </strong>Mean lung volume estimation error was 4.68% for LsqRC/AB, 9.88% for LsqRC, and 14.24% for the Banzett method. LsqRC/AB yielded significantly lower estimation error than both the LsqRC (<i>p</i> < .001, <i>d</i> = -1.14) and Banzett methods (<i>p</i> < .001, <i>d</i> = 1.69). Calibration task had no significant effect on estimation error (<i>p</i> = .889).</p><p><strong>Conclusions: </strong>The least squares method correcting for both the RC and AB (LsqRC/AB) provides the most precise lung volume estimates during cough. Error associated with the Banzett method exceeded previously reported values for speech breathing by more than 50%. Additional calibration tasks beyond rest breathing may not be necessary to meaningfully reduce lung volume error for cough measurement.</p><p><strong>Open science form: </strong>https://doi.org/10.23641/asha.29657360.</p>\",\"PeriodicalId\":520690,\"journal\":{\"name\":\"Journal of speech, language, and hearing research : JSLHR\",\"volume\":\" \",\"pages\":\"4290-4296\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of speech, language, and hearing research : JSLHR\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1044/2025_JSLHR-25-00237\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/8/18 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of speech, language, and hearing research : JSLHR","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1044/2025_JSLHR-25-00237","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/18 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
目的:有效的止咳功能需要足够的呼吸支持。为了估计肺容量,呼吸感应容积描记术测量了各种行为(如咳嗽)时胸腔(RC)和腹部(AB)的周向变化。在语音呼吸过程中,这些估计的准确性受到校准任务和分析方法的影响。测量误差可能导致偏差和混淆结果,但评估咳嗽期间肺容量的最佳方法仍不清楚。方法:20例帕金森病患者(年龄69岁,病程M = 11.39年)完成3项呼吸校准任务:(a)休息呼吸,(b)咳嗽样呼吸(“像要咳嗽一样吸气,然后用力呼气,不咳嗽”),(c)单次自主咳嗽(“用力咳嗽一次”)。通过比较估计的肺容量信号与跨任务和任务组合的肺活量测量信号来计算肺容量估计误差。还评估了三种分析方法的误差:Banzett方法(2:1加权RC和AB)和两种最小二乘法-一种校正RC和AB信号(LsqRC/AB),另一种保持AB常数(LsqRC)。结果:LsqRC/AB法平均肺体积估计误差为4.68%,LsqRC法为9.88%,Banzett法为14.24%。LsqRC/AB方法的估计误差显著低于LsqRC方法(p < 0.001, d = -1.14)和Banzett方法(p < 0.001, d = 1.69)。校正任务对估计误差无显著影响(p = .889)。结论:对RC和AB进行校正的最小二乘法(LsqRC/AB)提供了咳嗽时最精确的肺体积估计。与Banzett方法相关的误差超过了先前报道的语音呼吸值的50%以上。除了休息呼吸之外,可能不需要额外的校准任务来有意义地减少咳嗽测量的肺容量误差。开放科学形式:https://doi.org/10.23641/asha.29657360。
Estimating Lung Volume During Cough: A Comparison of Respiratory Calibration Tasks and Methodologies.
Purpose: Effective cough function requires sufficient respiratory support. To estimate lung volume, respiratory inductance plethysmography measures circumferential changes of the rib cage (RC) and abdomen (AB) during various behaviors, such as coughing. During speech breathing, the accuracy of these estimates is influenced by calibration tasks and analysis methods. Measurement error can introduce bias and confound results, yet the optimal approach for assessing lung volume during cough remains unclear.
Method: Twenty participants with Parkinson's disease (Mage = 69 years; M disease duration = 11.39 years) completed three respiratory calibration tasks: (a) rest breathing, (b) cough-like breathing ("breathe in like you're going to cough, then breathe out forcefully without coughing"), and (c) single voluntary coughs ("cough hard one time"). Lung volume estimation error was calculated by comparing the estimated lung volume signal to the spirometry signal across tasks and task combinations. Error was also assessed across three analysis methods: the Banzett method (2:1 weighting for RC and AB) and two least squares methods-one correcting for both the RC and AB signals (LsqRC/AB) and another holding the AB constant (LsqRC).
Results: Mean lung volume estimation error was 4.68% for LsqRC/AB, 9.88% for LsqRC, and 14.24% for the Banzett method. LsqRC/AB yielded significantly lower estimation error than both the LsqRC (p < .001, d = -1.14) and Banzett methods (p < .001, d = 1.69). Calibration task had no significant effect on estimation error (p = .889).
Conclusions: The least squares method correcting for both the RC and AB (LsqRC/AB) provides the most precise lung volume estimates during cough. Error associated with the Banzett method exceeded previously reported values for speech breathing by more than 50%. Additional calibration tasks beyond rest breathing may not be necessary to meaningfully reduce lung volume error for cough measurement.
Open science form: https://doi.org/10.23641/asha.29657360.