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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.


The global upper interval (GI), the mean of the 25% largest zero-crossing intervals, is computed for each intrinsic mode function (IMF). IMF5 has a smaller GI because its major content is noise (c). IMF6 and IMF7 contain a respiratory component, yielding a higher GI (d,e). Only considering upper intervals for computing GI is meant to avoid the effect of shorter zero-crossing intervals that are mainly attributed to noise (indicated by arrow A in IMF6). The IMFs with GI > 0.67 s (f) and a residual signal can be used to reconstruct a respiration signal (b).
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sensors-15-16372-f006: The global upper interval (GI), the mean of the 25% largest zero-crossing intervals, is computed for each intrinsic mode function (IMF). IMF5 has a smaller GI because its major content is noise (c). IMF6 and IMF7 contain a respiratory component, yielding a higher GI (d,e). Only considering upper intervals for computing GI is meant to avoid the effect of shorter zero-crossing intervals that are mainly attributed to noise (indicated by arrow A in IMF6). The IMFs with GI > 0.67 s (f) and a residual signal can be used to reconstruct a respiration signal (b).

Mentions: In order to determine IRRI, two indexes are derived from each IMF. The first one is the global upper interval index (GII):(6)GII=min{j/GIj>0.67 s}where GIj is the mean of the 25% largest zero-crossing intervals in IMFj. As shown in Figure 6, IMF5 has a smaller GI because its major content is noise. IMF6 and IMF7 have a higher GI for containing respiratory components. Only including upper intervals for computing GI is meant to avoid the effect of shorter zero-crossing intervals that are attributed to noises (indicated by arrow A in Figure 6d). GII is the index that all GIs after this index (j ≥ GII) are greater than 0.67 s (Figure 6f). Selecting IMFs with GI > 0.67 s corresponds to considering oscillatory components with frequencies below 0.75 Hz (<45 breaths/min equivalently) that cover the normal respiratory rate and most of the abnormal respiratory rate [17,18].


Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition.

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

The global upper interval (GI), the mean of the 25% largest zero-crossing intervals, is computed for each intrinsic mode function (IMF). IMF5 has a smaller GI because its major content is noise (c). IMF6 and IMF7 contain a respiratory component, yielding a higher GI (d,e). Only considering upper intervals for computing GI is meant to avoid the effect of shorter zero-crossing intervals that are mainly attributed to noise (indicated by arrow A in IMF6). The IMFs with GI > 0.67 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-f006: The global upper interval (GI), the mean of the 25% largest zero-crossing intervals, is computed for each intrinsic mode function (IMF). IMF5 has a smaller GI because its major content is noise (c). IMF6 and IMF7 contain a respiratory component, yielding a higher GI (d,e). Only considering upper intervals for computing GI is meant to avoid the effect of shorter zero-crossing intervals that are mainly attributed to noise (indicated by arrow A in IMF6). The IMFs with GI > 0.67 s (f) and a residual signal can be used to reconstruct a respiration signal (b).
Mentions: In order to determine IRRI, two indexes are derived from each IMF. The first one is the global upper interval index (GII):(6)GII=min{j/GIj>0.67 s}where GIj is the mean of the 25% largest zero-crossing intervals in IMFj. As shown in Figure 6, IMF5 has a smaller GI because its major content is noise. IMF6 and IMF7 have a higher GI for containing respiratory components. Only including upper intervals for computing GI is meant to avoid the effect of shorter zero-crossing intervals that are attributed to noises (indicated by arrow A in Figure 6d). GII is the index that all GIs after this index (j ≥ GII) are greater than 0.67 s (Figure 6f). Selecting IMFs with GI > 0.67 s corresponds to considering oscillatory components with frequencies below 0.75 Hz (<45 breaths/min equivalently) that cover the normal respiratory rate and most of the abnormal respiratory rate [17,18].

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.