Limits...
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

The largest interval (LI), the largest zero-crossing interval in intrinsic mode function (IMF), can catch the local oscillatory component whose frequency is lowest in each IMF (indicated by arrow B in IMF5). Since this local component is distinct compared to the rest of the components, IMF5 also has a high kurtosis (c). The IMFs with LI > 1 s (f) and a residual signal can be used to reconstruct a respiration signal (b).
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4541883&req=5

sensors-15-16372-f007: The largest interval (LI), the largest zero-crossing interval in intrinsic mode function (IMF), can catch the local oscillatory component whose frequency is lowest in each IMF (indicated by arrow B in IMF5). Since this local component is distinct compared to the rest of the components, IMF5 also has a high kurtosis (c). The IMFs with LI > 1 s (f) and a residual signal can be used to reconstruct a respiration signal (b).

Mentions: The second index is the largest interval index (LII):(7)LII=min{j/LIj>1 s}where LIj is the largest zero-crossing interval in IMFj. The largest interval reflects a kind of local property. As shown in Figure 7c, there is a short respiratory component (indicated by arrow B) in IMF5, and this short oscillatory property can be captured by LI. LII is the index that all LIs after this index (j ≥ LII) are greater than 1 s (equivalent frequencies less than 0.5 Hz) (Figure 7f). If the short component is distinct from the rest of the components in the IMF h(t), this IMF has a high kurtosis:(8)kurt{h(t)}=E{(h(t)−μ)4}σ4where μ is the mean of h(t), σ is the standard deviation of h(t), and E is the expected value operation.


Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition.

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

The largest interval (LI), the largest zero-crossing interval in intrinsic mode function (IMF), can catch the local oscillatory component whose frequency is lowest in each IMF (indicated by arrow B in IMF5). Since this local component is distinct compared to the rest of the components, IMF5 also has a high kurtosis (c). The IMFs with LI > 1 s (f) and a residual signal can be used to reconstruct a respiration signal (b).
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-16372-f007: The largest interval (LI), the largest zero-crossing interval in intrinsic mode function (IMF), can catch the local oscillatory component whose frequency is lowest in each IMF (indicated by arrow B in IMF5). Since this local component is distinct compared to the rest of the components, IMF5 also has a high kurtosis (c). The IMFs with LI > 1 s (f) and a residual signal can be used to reconstruct a respiration signal (b).
Mentions: The second index is the largest interval index (LII):(7)LII=min{j/LIj>1 s}where LIj is the largest zero-crossing interval in IMFj. The largest interval reflects a kind of local property. As shown in Figure 7c, there is a short respiratory component (indicated by arrow B) in IMF5, and this short oscillatory property can be captured by LI. LII is the index that all LIs after this index (j ≥ LII) are greater than 1 s (equivalent frequencies less than 0.5 Hz) (Figure 7f). If the short component is distinct from the rest of the components in the IMF h(t), this IMF has a high kurtosis:(8)kurt{h(t)}=E{(h(t)−μ)4}σ4where μ is the mean of h(t), σ is the standard deviation of h(t), and E is the expected value operation.

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