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To propose a transfer learning-based method for breath sound feature recognition and autonomous determination of sputum suction timing.
An electronic stethoscope was used to collect breath sounds from the main airways of clinically ventilated patients before and after sputum suction, with pre-suction breath sounds labeled as requiring suction. The collected data underwent high-pass filtering and wavelet soft-threshold denoising, followed by the extraction of log-Mel spectrograms. A VGGish model pretrained on the Audio Set dataset was then employed to extract feature vectors from these spectrograms, which were subsequently classified using a support vector machine to determine whether suction was required.
The precision, recall and F1 score for recognition of breath sounds requiring sputum suction were 86.73%, 93.06% and 89.78%, respectively.
The proposed breath sound recognition method based on transfer learning effectively determines the timing of sputum suction and shows a significant clinical potential.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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