Fast neural network processing for detecting breathing sound recorded by microphone

DOI

Bibliographic Information

Other Title
  • マイクロフォンにより録音された呼吸音のニューラルネットワークに基づく高速検出法

Abstract

Measurements of breathing have been used as one of the tools used in the diagnosis of sleep apnea. Respiratory inductance plethysmography, temperature sensor and thoracic impedance cardiography have mainly been used for measuring breathing information. However these methods require the sensors attached on the body of the subjects. Under a quiet environment, the breathing information can be recorded by using non-contact microphone. The sound recordings include not only breathing but also other sound. In addition, breathing sound should be recorded under low signal-to-noise ratio (SNR). Our group has developed neural network (NN) based method to detect breathing sound in the sound recordings. This method can detect low SNR breathing sound with high accuracy. However, the method needs to use multi neural networks. For this reason, we make effective use of testing process and propose new NN-based method to detect breathing sounds with higher speed. We show that the proposed method can accurately detect low SNR breathing sound with higher speed.

Journal

Details 詳細情報について

  • CRID
    1390282680244908032
  • NII Article ID
    130005163935
  • DOI
    10.11239/jsmbe.53.s239_01
  • ISSN
    18814379
    1347443X
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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