DocumentCode :
2503642
Title :
Detection of Respiratory Rhythm from Photoplethysmography Signal Using Morphological Operators
Author :
Li Jin ; Jin, Li
Author_Institution :
Postdoctoral Mobile Station of Biomed. Eng., Xi´´an Jiaotong Univ., Xi´´an, China
fYear :
2009
fDate :
11-13 June 2009
Firstpage :
1
Lastpage :
4
Abstract :
A new approach using morphological operators was proposed to detect the respiratory rhythm from the photoplethysmography (PPG) signal. In the study, photoplethysmograms were obtained from 5 healthy adult volunteers when they respired 6, 10, 15 times per minute. The reference respiratory signal was obtained by transthoracic impedance method simultaneously. Each PPG signal was processed using morphological operators to reduce the low frequency baseline drift and extract the peak envelope of the corrected signal first. Then the algorithm detected trend change of the pre-processed signal and obtained the rhythm of respiration. The result with a false rate of 4.52% showed that our technique had a good performance on detection of respiratory rhythm from PPG signal. The low computational complexity of the algorithm may make it easy to be implemented on MCU for real-time processing. More experimental data is necessary to improve the reliability and robustness of the algorithm.
Keywords :
medical signal detection; optical information processing; optical signal detection; plethysmography; pneumodynamics; PPG signal processing; computational complexity; low-frequency baseline drift; morphological operators; photoplethysmography signal; real-time processing; respiratory rhythm detection; signal preprocessing; transthoracic impedance method; Biomedical engineering; Biomedical signal processing; Change detection algorithms; Computational complexity; Frequency; Medical signal detection; Monitoring; Rhythm; Signal processing; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2901-1
Electronic_ISBN :
978-1-4244-2902-8
Type :
conf
DOI :
10.1109/ICBBE.2009.5162610
Filename :
5162610
Link To Document :
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