Improved Detection of Lung Fluid With Standardized Acoustic Stimulation of the Chest

被引:5
作者
Rao, Adam [1 ]
Chu, Simon [2 ]
Batlivala, Neil
Zetumer, Samuel [2 ]
Roy, Shuvo [1 ]
机构
[1] Univ Calif San Francisco, Dept Bioengn & Therapeut Sci, San Francisco, CA 94158 USA
[2] Univ Calif San Francisco, Sch Med, San Francisco, CA 94143 USA
来源
IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE | 2018年 / 6卷
关键词
Acoustic sensors; actuators; biomedical acoustics; transfer function; classification algorithms; SOUND ANALYSIS; CLASSIFICATION; TRANSMISSION;
D O I
10.1109/JTEHM.2018.2863366
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Accumulation of excess air and water in the lungs leads to breakdown of respiratory function and is a common cause of patient hospitalization. Compact and non-invasive methods to detect the changes in lung fluid accumulation can allow physicians to assess patients' respiratory conditions. In this paper, an acoustic transducer and a digital stethoscope system are proposed as a targeted solution for this clinical need. Alterations in the structure of the lungs lead to measurable changes which can be used to assess lung pathology. We standardize this procedure by sending a controlled signal through the lungs of six healthy subjects and six patients with lung disease. We extract mel-frequency cepstral coefficients and spectroid audio features, commonly used in classification for music retrieval, to characterize subjects as healthy or diseased. Using the K-nearest neighbors algorithm, we demonstrate 91.7% accuracy in distinguishing between healthy subjects and patients with lung pathology.
引用
收藏
页数:7
相关论文
共 37 条
  • [1] Ahmed A., 2018, UPTODATE
  • [2] Alsmadi SS, 2002, P ANN INT IEEE EMBS, P1771, DOI 10.1109/IEMBS.2002.1106645
  • [3] Amatriain X, 2002, DAFX - DIGITAL AUDIO EFFECTS, P373
  • [4] Classification of lung sounds using convolutional neural networks
    Aykanat, Murat
    Kilic, Ozkan
    Kurt, Bahar
    Saryal, Sevgi
    [J]. EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING, 2017,
  • [5] Pattern recognition methods applied to respiratory sounds classification into normal and wheeze classes
    Bahoura, Mohammed
    [J]. COMPUTERS IN BIOLOGY AND MEDICINE, 2009, 39 (09) : 824 - 843
  • [6] On the use of phase and energy for musical onset detection in the complex domain
    Bello, JP
    Duxbury, C
    Davies, M
    Sandler, M
    [J]. IEEE SIGNAL PROCESSING LETTERS, 2004, 11 (06) : 553 - 556
  • [7] Bickley L. S., 2012, BATES GUIDE PHYS EXA
  • [8] Bogdanov D., 2013, P 21 ACM INT C MULT, P855, DOI [10.1145/2502081.2502229, DOI 10.1145/2502081]
  • [9] ACOUSTIC TRANSMISSION OF THE RESPIRATORY SYSTEM USING SPEECH STIMULATION
    COHEN, A
    BERSTEIN, AD
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 1991, 38 (02) : 126 - 132
  • [10] ANALYSIS AND AUTOMATIC CLASSIFICATION OF BREATH SOUNDS
    COHEN, A
    LANDSBERG, D
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 1984, 31 (09) : 585 - 590