Artificial Intelligence Techniques Used for Wheeze Sounds Analysis: Review

被引:0
作者
Nabi, F. G. [1 ]
Sundaraj, K. [2 ]
Kiang, L. C. [1 ]
Palaniappan, R. [3 ]
Sundaraj, S. [4 ]
Ahamed, N. U. [5 ]
机构
[1] Univ Malaysia Perlis, Sch Mechatron Engn, Arau, Perlis, Malaysia
[2] Univ Tekn Malaysia Melaka UTeM, Fac Elect & Comp Engn, Durian Tunggal, Melaka, Malaysia
[3] VIT, Sch Elect Engn SENSE, Vellore, Tamil Nadu, India
[4] HTAR, Dept Anesthesiol, Klang, Selangor, Malaysia
[5] Univ Malaysia Pahang, Fac Mfg Engn, Pekan, Pahang, Malaysia
来源
3RD INTERNATIONAL CONFERENCE ON MOVEMENT, HEALTH AND EXERCISE: ENGINEERING OLYMPIC SUCCESS: FROM THEORY TO PRACTICE | 2017年 / 58卷
关键词
Wheeze; Wheeze Sounds; Respiratory Sounds; Airway Obstruction; Wheeze Analysis; INDEX;
D O I
10.1007/978-981-10-3737-5_8
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Wheezes are acoustic, adventitious, continues and high pitch pulmonary sounds produce due to airway obstruction, these sounds mostly exist in pneumonia and asthma patients. Artificial intelligence techniques have been extensively used for wheeze sound analysis to diagnose patient. The available literature has not yet been reviewed. In this article most recent and relevant 12 studies, from different databases related to artificial inelegance techniques for wheeze detection has been selected for detailed review. It has been noticed that now trend is going to increase in this area, for personal assistance and continues monitoring of patient health. The literature reveals that 1) wheezes signals have enough information for the classification of patients according to disease severity level and type of disease, 2) significant work is required for identification of severity level of airway obstruction and pathology differentiation.
引用
收藏
页码:37 / 40
页数:4
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