Deep learning-based method for examining mouth and nose breathing
A deep learning, mouth and nose technology, applied in the field of biomedicine, can solve problems that affect facial development, lack of inspection and classification of mouth, nose and breathing, and discomfort of the patient's head or face
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[0056] like figure 1 As shown, a method for examining mouth and nose breathing based on deep learning includes the following steps:
[0057] S1: Segment the respiratory signal to obtain an effective sound segment;
[0058] S2: Use the Mel frequency cepstral coefficient extraction method improved by the empirical mode decomposition method to extract the features of the effective sound segment and obtain the feature set;
[0059] S3: Use a recurrent convolutional neural network to divide the feature set into a training set and a test set, and obtain a high classification accuracy model through five-fold cross-validation to check the mouth and nose breathing.
[0060] In the above solution, the effective sound segment of the breathing signal can be segmented to extract the effective sound segment, so that the processing of the breathing sound is more targeted. Due to the non-stationary signal of the sound signal, the method of empirical mode decomposition suitable for non-stati...
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