New tracheal sound feature for apnoea analysis.

Sleep apnoea syndrome is common in the general population and is currently underdiagnosed. The aim of the present work was to develop a new tracheal sound feature for separation of apnoea events from non-apnoea time. Ten overnight recordings from apnoea patients containing 1,107 visually scored apno...

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Publicado en:Medical & Biological Engineering & Computing Vol. 47; no. 4; pp. 405 - 413
Autores principales: Kulkas A, Huupponen E, Virkkala J, Tenhunen M, Saastamoinen A, Rauhala E, Himanen SL, Kulkas, A, Huupponen, E, Virkkala, J, Tenhunen, M, Saastamoinen, A, Rauhala, E, Himanen, S-L
Formato: research Journal Article
Publicado: Springer Nature Apr2009
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2009
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      pub: Springer Nature
      place: New York, New York
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        atl: New tracheal sound feature for apnoea analysis.
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          Kulkas A
          Huupponen E
          Virkkala J
          Tenhunen M
          Saastamoinen A
          Rauhala E
          Himanen SL
          Kulkas, A
          Huupponen, E
          Virkkala, J
          Tenhunen, M
          Saastamoinen, A
          Rauhala, E
          Himanen, S-L
        affil: Department of Clinical Neurophysiology, Medical Imaging Center, Pirkanmaa Hospital District, Tampere, Finland
      sug:
        subj:
          Auscultation Methods
          Sleep Apnea Syndromes Diagnosis
          Trachea Physiopathology
          Adult
          Male
          Middle Age
          Signal Processing, Computer Assisted
          Sound Spectrography Methods
          Vibration
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Male
      ab: Sleep apnoea syndrome is common in the general population and is currently underdiagnosed. The aim of the present work was to develop a new tracheal sound feature for separation of apnoea events from non-apnoea time. Ten overnight recordings from apnoea patients containing 1,107 visually scored apnoea events totalling 7 h in duration and 72 h of non-apnoea time were included in the study. The feature was designed to describe the local spectral content of the sound signal. The median, maximum and mean smoothing of different time scales were compared in the feature extraction. The feature was designed to range from 0 to 1 irrespective of tracheal sound amplitudes. This constant range could offer application of the feature without patient-specific adjustments. The overall separation of feature values during apnoea events from non-apnoea time across all patients was good, reaching 80.8%. Due to the individual differences in tracheal sound signal amplitudes, developing amplitude-independent means for screening apnoea events is beneficial.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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