Shanghai Jiao Tong University

Bei Pei

Ming Xia

Jie Wang

Hong Jiang

Ren Zhou

Shuang Cao

Chen Yu Jin

Tian Yi Xu

The present disclosure relates to a difficult airway evaluation method and device based on a machine learning voice technology. The method includes the following steps: acquiring voice data of a patient; carrying out feature extraction on the voice data, obtaining a pitch period of pronunciations, and acquiring a voiced sound feature and unvoiced sound features based on the pitch period of pronunciations; and constructing a difficult airway evaluation classifier based on the machine learning voice technology, analyzing the received voiced sound feature and unvoiced sound features by the trained difficult airway evaluation classifier, and carrying out scoring on the severity of a difficult airway to obtain an evaluation result of the difficult airway.

Difficult airway evaluation method and device based on machine learning voice technology

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Shanghai, China

Bei Pei