Paul S. Addison;Andre Antunes;Dean Montgomery;Ulf R. Borg
{"title":"非接触式监测非通气受试者的吸气-呼气 (I:E) 比值","authors":"Paul S. Addison;Andre Antunes;Dean Montgomery;Ulf R. Borg","doi":"10.1109/JTEHM.2024.3496196","DOIUrl":null,"url":null,"abstract":"The inhalation-exhalation (I:E) ratio, known to be an indicator of respiratory disease, is the ratio between the inhalation phase and exhalation phase of each breath. Here, we report on results from a non-contact monitoring method for the determination of the I:E ratio. This employs a depth sensing camera system that requires no sensors to be physically attached to the patient. A range of I:E ratios from 0.3 to 1.0 over a range of respiratory rates from 4 to 40 breaths/min were generated by healthy volunteers, producing a total of 3,882 separate breaths for analysis. Depth information was acquired using an Intel D415 RealSense camera placed at 1.1 m from the subjects’ torso. This data was processed in real-time to extract depth changes within the subjects’ torso region corresponding to respiratory activity. This was further converted into a respiratory signal from which the I:E ratio was determined (I:E\n<inline-formula> <tex-math>$_{\\mathrm {depth}}$ </tex-math></inline-formula>\n). I:Edepth was compared to spirometer data (I:E\n<inline-formula> <tex-math>$_{\\mathrm {spiro}}$ </tex-math></inline-formula>\n). A Bland Altman analysis produced a mean bias of –0.004, with limits of agreement [–0.234, 0.227]. A linear regression analysis produced a line of best fit given by I:E\n<inline-formula> <tex-math>$_{\\mathrm {depth}} = 1.004\\times $ </tex-math></inline-formula>\n I:Espiro – 0.006, with 95% confidence intervals for the slope [0.988, 1.019] and intercept [–0.017, 0.004]. We have demonstrated the viability of a non-contact monitoring method for determining the I:E ratio on healthy subjects breathing without mechanical support. This measure may be useful in monitoring the deterioration in respiratory status and/or response to therapy within the patient population. Clinical and Translational Impact Statement - The I:E ratio is an indicator of disease severity in COPD and asthma. Non-contact continuous monitoring of I:E ratio will offer the clinician a powerful new tool for respiratory monitoring","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"12 ","pages":"721-726"},"PeriodicalIF":3.7000,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10750123","citationCount":"0","resultStr":"{\"title\":\"Non-Contact Monitoring of Inhalation-Exhalation (I:E) Ratio in Non-Ventilated Subjects\",\"authors\":\"Paul S. Addison;Andre Antunes;Dean Montgomery;Ulf R. Borg\",\"doi\":\"10.1109/JTEHM.2024.3496196\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The inhalation-exhalation (I:E) ratio, known to be an indicator of respiratory disease, is the ratio between the inhalation phase and exhalation phase of each breath. Here, we report on results from a non-contact monitoring method for the determination of the I:E ratio. This employs a depth sensing camera system that requires no sensors to be physically attached to the patient. A range of I:E ratios from 0.3 to 1.0 over a range of respiratory rates from 4 to 40 breaths/min were generated by healthy volunteers, producing a total of 3,882 separate breaths for analysis. Depth information was acquired using an Intel D415 RealSense camera placed at 1.1 m from the subjects’ torso. This data was processed in real-time to extract depth changes within the subjects’ torso region corresponding to respiratory activity. This was further converted into a respiratory signal from which the I:E ratio was determined (I:E\\n<inline-formula> <tex-math>$_{\\\\mathrm {depth}}$ </tex-math></inline-formula>\\n). I:Edepth was compared to spirometer data (I:E\\n<inline-formula> <tex-math>$_{\\\\mathrm {spiro}}$ </tex-math></inline-formula>\\n). A Bland Altman analysis produced a mean bias of –0.004, with limits of agreement [–0.234, 0.227]. A linear regression analysis produced a line of best fit given by I:E\\n<inline-formula> <tex-math>$_{\\\\mathrm {depth}} = 1.004\\\\times $ </tex-math></inline-formula>\\n I:Espiro – 0.006, with 95% confidence intervals for the slope [0.988, 1.019] and intercept [–0.017, 0.004]. We have demonstrated the viability of a non-contact monitoring method for determining the I:E ratio on healthy subjects breathing without mechanical support. This measure may be useful in monitoring the deterioration in respiratory status and/or response to therapy within the patient population. 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Non-Contact Monitoring of Inhalation-Exhalation (I:E) Ratio in Non-Ventilated Subjects
The inhalation-exhalation (I:E) ratio, known to be an indicator of respiratory disease, is the ratio between the inhalation phase and exhalation phase of each breath. Here, we report on results from a non-contact monitoring method for the determination of the I:E ratio. This employs a depth sensing camera system that requires no sensors to be physically attached to the patient. A range of I:E ratios from 0.3 to 1.0 over a range of respiratory rates from 4 to 40 breaths/min were generated by healthy volunteers, producing a total of 3,882 separate breaths for analysis. Depth information was acquired using an Intel D415 RealSense camera placed at 1.1 m from the subjects’ torso. This data was processed in real-time to extract depth changes within the subjects’ torso region corresponding to respiratory activity. This was further converted into a respiratory signal from which the I:E ratio was determined (I:E
$_{\mathrm {depth}}$
). I:Edepth was compared to spirometer data (I:E
$_{\mathrm {spiro}}$
). A Bland Altman analysis produced a mean bias of –0.004, with limits of agreement [–0.234, 0.227]. A linear regression analysis produced a line of best fit given by I:E
$_{\mathrm {depth}} = 1.004\times $
I:Espiro – 0.006, with 95% confidence intervals for the slope [0.988, 1.019] and intercept [–0.017, 0.004]. We have demonstrated the viability of a non-contact monitoring method for determining the I:E ratio on healthy subjects breathing without mechanical support. This measure may be useful in monitoring the deterioration in respiratory status and/or response to therapy within the patient population. Clinical and Translational Impact Statement - The I:E ratio is an indicator of disease severity in COPD and asthma. Non-contact continuous monitoring of I:E ratio will offer the clinician a powerful new tool for respiratory monitoring
期刊介绍:
The IEEE Journal of Translational Engineering in Health and Medicine is an open access product that bridges the engineering and clinical worlds, focusing on detailed descriptions of advanced technical solutions to a clinical need along with clinical results and healthcare relevance. The journal provides a platform for state-of-the-art technology directions in the interdisciplinary field of biomedical engineering, embracing engineering, life sciences and medicine. A unique aspect of the journal is its ability to foster a collaboration between physicians and engineers for presenting broad and compelling real world technological and engineering solutions that can be implemented in the interest of improving quality of patient care and treatment outcomes, thereby reducing costs and improving efficiency. The journal provides an active forum for clinical research and relevant state-of the-art technology for members of all the IEEE societies that have an interest in biomedical engineering as well as reaching out directly to physicians and the medical community through the American Medical Association (AMA) and other clinical societies. The scope of the journal includes, but is not limited, to topics on: Medical devices, healthcare delivery systems, global healthcare initiatives, and ICT based services; Technological relevance to healthcare cost reduction; Technology affecting healthcare management, decision-making, and policy; Advanced technical work that is applied to solving specific clinical needs.