| Title |
A simple method to reconstruct the molar mass signal of respiratory gas to assess small airways with a double-tracer gas single-breath washout
|
|---|---|
| Published in |
Medical & Biological Engineering & Computing, March 2017
|
| DOI | 10.1007/s11517-017-1633-y |
| Pubmed ID | |
| Authors |
Johannes Port, Ziran Tao, Annika Junger, Christoph Joppek, Philipp Tempel, Kim Husemann, Florian Singer, Philipp Latzin, Sophie Yammine, Joachim H. Nagel, Martin Kohlhäufl |
| Abstract |
For the assessment of small airway diseases, a noninvasive double-tracer gas single-breath washout (DTG-SBW) with sulfur hexafluoride (SF6) and helium (He) as tracer components has been proposed. It is assumed that small airway diseases may produce typical ventilation inhomogeneities which can be detected within one single tidal breath, when using two tracer components. Characteristic parameters calculated from a relative molar mass (MM) signal of the airflow during the washout expiration phase are analyzed. The DTG-SBW signal is acquired by subtracting a reconstructed MM signal without tracer gas from the signal measured with an ultrasonic sensor during in- and exhalation of the double-tracer gas for one tidal breath. In this paper, a simple method to determine the reconstructed MM signal is presented. Measurements on subjects with and without obstructive lung diseases including the small airways have shown high reliability and reproducibility of this method. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 16 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 50% |
| Researcher | 3 | 19% |
| Other | 2 | 13% |
| Student > Doctoral Student | 1 | 6% |
| Unknown | 2 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 7 | 44% |
| Engineering | 2 | 13% |
| Medicine and Dentistry | 2 | 13% |
| Mathematics | 1 | 6% |
| Sports and Recreations | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 3 | 19% |
Attention Score in Context
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#22,764,772
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Outputs of similar age from Medical & Biological Engineering & Computing
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