Title
Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition
Abstract
Impedance plethysmography provides a way to measure respiratory activity by sensing the change of thoracic impedance caused by inspiration and expiration. This measurement imposes little pressure on the body and uses the human body as the sensor, thereby reducing the need for adjustments as body position changes and making it suitable for long-term or ambulatory monitoring. The empirical mode decomposition (EMD) can decompose a signal into several intrinsic mode functions (IMFs) that disclose nonstationary components as well as stationary components and, similarly, capture respiratory episodes from thoracic impedance. However, upper-body movements usually produce motion artifacts that are not easily removed by digital filtering. Moreover, large motion artifacts disable the EMD to decompose respiratory components. In this paper, motion artifacts are detected and replaced by the data mirrored from the prior and the posterior before EMD processing. A novel intrinsic respiratory reconstruction index that considers both global and local properties of IMFs is proposed to define respiration-related IMFs for respiration reconstruction and instantaneous respiratory estimation. Based on the experiments performing a series of static and dynamic physical activates, our results showed the proposed method had higher cross correlations between respiratory frequencies estimated from thoracic impedance and those from oronasal airflow based on small window size compared to the Fourier transform-based method.
Year
DOI
Venue
2015
10.3390/s150716372
SENSORS
Keywords
Field
DocType
impedance plethysmography,respiratory disorder,empirical mode decomposition,intrinsic mode function
Thoracic impedance,Digital filter,Fourier transform,Electrical impedance,Electronic engineering,Airflow,Respiratory system,Engineering,Hilbert–Huang transform
Journal
Volume
Issue
ISSN
15
7.0
1424-8220
Citations 
PageRank 
References 
3
0.42
5
Authors
5
Name
Order
Citations
PageRank
Fu-Tai Wang171.59
Hsiao-Lung Chan217619.98
Chun-Li Wang3111.65
hungming jian430.42
Shen-Hsiung Lin561.56