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Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition.

Wang FT, Chan HL, Wang CL, Jian HM, Lin SH - Sensors (Basel) (2015)

Bottom Line: 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.Moreover, large motion artifacts disable the EMD to decompose respiratory components.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical Engineering, Hwa Hsia University of Technology, 111, Gongzhuan Rd., Zhonghe, New Taipei City 23568, Taiwan. wft.intuitive@seed.net.tw.

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.

No MeSH data available.


Related in: MedlinePlus

A thoracic impedance signal (a) is decomposed into numbers of intrinsic mode components (IMFs) by empirical mode decomposition (c–f) for respiration reconstruction (b). Major respiratory components are present at local points of IMF5 (d) and IMF6 (e).
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sensors-15-16372-f002: A thoracic impedance signal (a) is decomposed into numbers of intrinsic mode components (IMFs) by empirical mode decomposition (c–f) for respiration reconstruction (b). Major respiratory components are present at local points of IMF5 (d) and IMF6 (e).

Mentions: The decomposed IMFs have well-behaved Hilbert transforms so that instantaneous frequencies and amplitudes can be derived from the IMFs. The instantaneous estimation is beneficial for capturing respiratory episodes from normal respirations. However, only some of the IMFs are related to respiration, so identifying respiration-related IMFs is needed for estimating instantaneous properties. Liu et al. applied mutual information ratio and power of IMFs to select the best IMFs to reconstruct respiration signals [14]. However, even if respiratory components are similar, they may be decomposed at different local points in adjacent IMFs. As shown in Figure 2, a major respiratory component is present at both IMF5 and IMF6. Therefore, the local properties as well as global properties of IMFs should be considered for identifying respiration-related IMFs.


Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition.

Wang FT, Chan HL, Wang CL, Jian HM, Lin SH - Sensors (Basel) (2015)

A thoracic impedance signal (a) is decomposed into numbers of intrinsic mode components (IMFs) by empirical mode decomposition (c–f) for respiration reconstruction (b). Major respiratory components are present at local points of IMF5 (d) and IMF6 (e).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541883&req=5

sensors-15-16372-f002: A thoracic impedance signal (a) is decomposed into numbers of intrinsic mode components (IMFs) by empirical mode decomposition (c–f) for respiration reconstruction (b). Major respiratory components are present at local points of IMF5 (d) and IMF6 (e).
Mentions: The decomposed IMFs have well-behaved Hilbert transforms so that instantaneous frequencies and amplitudes can be derived from the IMFs. The instantaneous estimation is beneficial for capturing respiratory episodes from normal respirations. However, only some of the IMFs are related to respiration, so identifying respiration-related IMFs is needed for estimating instantaneous properties. Liu et al. applied mutual information ratio and power of IMFs to select the best IMFs to reconstruct respiration signals [14]. However, even if respiratory components are similar, they may be decomposed at different local points in adjacent IMFs. As shown in Figure 2, a major respiratory component is present at both IMF5 and IMF6. Therefore, the local properties as well as global properties of IMFs should be considered for identifying respiration-related IMFs.

Bottom Line: 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.Moreover, large motion artifacts disable the EMD to decompose respiratory components.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical Engineering, Hwa Hsia University of Technology, 111, Gongzhuan Rd., Zhonghe, New Taipei City 23568, Taiwan. wft.intuitive@seed.net.tw.

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.

No MeSH data available.


Related in: MedlinePlus