Recognizing Thoracic Breathing by Ensemble Empirical Mode Decomposition

被引：0
|
作者：
Chen, Jin-Long [1 ]
Chen, Ya-Chen [2 ]
Hsiao, Tzu-Chien [3 ]
机构：
[1] Tzu Chi Univ, Dept Med Informat, Hualien, Taiwan
[2] Natl Chiao Tung Univ, Inst Comp Sci & Engn, Hsinchu, Taiwan
[3] Natl Chiao Tung Univ, Dept Comp Sci, Inst Biomed Engn, Hsinchu, Taiwan
来源：
2013 9TH INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATIONS AND SIGNAL PROCESSING (ICICS) | 2013年
关键词：
thoracic breathing; abdominal breathing; ensemble empirical mode decomposition; THORACOABDOMINAL MOVEMENT;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Recognizing breathing pattern is important in many fields of medicine. Ensemble empirical mode decomposition (an adaptive algorithm) was used to investigate breathing pattern, including thoracic breathing (TB) and abdominal breathing (AB). This study recognizes TB and AB by correlation coefficient and power proportion. Results indicate that the recognition accuracy of TB by correlation coefficient and power proportion are 85.2% and 93.3% respectively, and that of AB by correlation coefficient and power proportion are 54.3% and 56.2% respectively. The TB can be well defined and recognized in complex time variation. These results can be used as references to develop the real time breathing evaluation system in the future.
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页数：5
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