| Title |
Time-varying signal analysis to detect high-altitude periodic breathing in climbers ascending to extreme altitude
|
|---|---|
| Published in |
Medical & Biological Engineering & Computing, March 2015
|
| DOI | 10.1007/s11517-015-1275-x |
| Pubmed ID | |
| Authors |
A. Garde, B. F. Giraldo, R. Jané, T. D. Latshang, A. J. Turk, T. Hess, M. M. Bosch, D. Barthelmes, T. M. Merz, J. Pichler Hefti, O. D. Schoch, K. E. Bloch |
| Abstract |
This work investigates the performance of cardiorespiratory analysis detecting periodic breathing (PB) in chest wall recordings in mountaineers climbing to extreme altitude. The breathing patterns of 34 mountaineers were monitored unobtrusively by inductance plethysmography, ECG and pulse oximetry using a portable recorder during climbs at altitudes between 4497 and 7546 m on Mt. Muztagh Ata. The minute ventilation (VE) and heart rate (HR) signals were studied, to identify visually scored PB, applying time-varying spectral, coherence and entropy analysis. In 411 climbing periods, 30-120 min in duration, high values of mean power (MP(VE)) and slope (MSlope(VE)) of the modulation frequency band of VE, accurately identified PB, with an area under the ROC curve of 88 and 89 %, respectively. Prolonged stay at altitude was associated with an increase in PB. During PB episodes, higher peak power of ventilatory (MP(VE)) and cardiac (MP LF (HR) ) oscillations and cardiorespiratory coherence (MP LF (Coher) ), but reduced ventilation entropy (SampEn(VE)), was observed. Therefore, the characterization of cardiorespiratory dynamics by the analysis of VE and HR signals accurately identifies PB and effects of altitude acclimatization, providing promising tools for investigating physiologic effects of environmental exposures and diseases. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 3 | 11% |
| Unknown | 25 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 18% |
| Student > Bachelor | 4 | 14% |
| Librarian | 4 | 14% |
| Researcher | 3 | 11% |
| Student > Ph. D. Student | 3 | 11% |
| Other | 4 | 14% |
| Unknown | 5 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 25% |
| Engineering | 5 | 18% |
| Sports and Recreations | 5 | 18% |
| Nursing and Health Professions | 2 | 7% |
| Computer Science | 2 | 7% |
| Other | 2 | 7% |
| Unknown | 5 | 18% |
Attention Score in Context
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#20,655,488
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Outputs from Medical & Biological Engineering & Computing
#1,812
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Outputs of similar age from Medical & Biological Engineering & Computing
#11
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