Sleep snoring sound classification detecting method and system based on depth learning
A deep learning and classification detection technology, applied in the field of disease detection, can solve problems such as affecting the normal sleep state of patients, inconvenience, high price, etc., and achieve the effect of accurately evaluating whether or not and the degree of disease.
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[0056] Such as figure 1 Shown, a kind of sleep snoring classification detection method based on deep learning, comprises the following steps:
[0057] S1. Collect the patient's sleep sound signal throughout the night, and detect the sound segment in the sleep sound signal, and obtain the sound segment map in the sleep sound signal, and the sound segment is a snoring sound or breathing sound or other noise;
[0058] S11. Detect the sound segment in the sleep sound signal: perform pre-emphasis and frame-division preprocessing on the sleep sound signal, and perform noise reduction processing on the pre-processed sleep sound signal, and then calculate the noise reduction The effective value of the voiced segment and the residual noise segment in the processed sleep sound signal is determined according to the effective value profile of the sleep sound signal to determine the final effective value signal;
[0059] S111. Perform pre-emphasis and frame-dividing preprocessing on the s...
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