Real-time obstructive sleep apnea detection based on ECG derived respiration signal

Teng Chieh Huang; Hsiao Yu Chen; Wai-Chi Fang

doi:10.1109/ISCAS.2012.6272031

Real-time obstructive sleep apnea detection based on ECG derived respiration signal

Teng Chieh Huang^*, Hsiao Yu Chen, Wai-Chi Fang

^*Corresponding author for this work

Research output: Contribution to conference › Paper › peer-review

6 Scopus citations

Abstract

It is known that ECG signal are strongly affected by the chest motion of respiration. We utilize this property and derive a respiration related signal with respect to the change of R wave area, and then match the derived signal to the time axis. We discovered that during the apnea section, a lower frequency component compared to the respiration frequency is observed. With the presence and absence of this lower frequency modulation on the ECG signal, we propose a real-time detection method to differentiate the apnea section and normal breathing section in the duration of sleep.

Original language	English
Pages	341-344
Number of pages	4
DOIs	https://doi.org/10.1109/ISCAS.2012.6272031
State	Published - 2012
Event	2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012 - Seoul, Korea, Republic of Duration: 20 May 2012 → 23 May 2012

Conference

Conference	2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012
Country/Territory	Korea, Republic of
City	Seoul
Period	20/05/12 → 23/05/12

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10.1109/ISCAS.2012.6272031

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abstract = "It is known that ECG signal are strongly affected by the chest motion of respiration. We utilize this property and derive a respiration related signal with respect to the change of R wave area, and then match the derived signal to the time axis. We discovered that during the apnea section, a lower frequency component compared to the respiration frequency is observed. With the presence and absence of this lower frequency modulation on the ECG signal, we propose a real-time detection method to differentiate the apnea section and normal breathing section in the duration of sleep.",

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AU - Chen, Hsiao Yu

AU - Fang, Wai-Chi

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N2 - It is known that ECG signal are strongly affected by the chest motion of respiration. We utilize this property and derive a respiration related signal with respect to the change of R wave area, and then match the derived signal to the time axis. We discovered that during the apnea section, a lower frequency component compared to the respiration frequency is observed. With the presence and absence of this lower frequency modulation on the ECG signal, we propose a real-time detection method to differentiate the apnea section and normal breathing section in the duration of sleep.

AB - It is known that ECG signal are strongly affected by the chest motion of respiration. We utilize this property and derive a respiration related signal with respect to the change of R wave area, and then match the derived signal to the time axis. We discovered that during the apnea section, a lower frequency component compared to the respiration frequency is observed. With the presence and absence of this lower frequency modulation on the ECG signal, we propose a real-time detection method to differentiate the apnea section and normal breathing section in the duration of sleep.

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U2 - 10.1109/ISCAS.2012.6272031

DO - 10.1109/ISCAS.2012.6272031

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T2 - 2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012

Y2 - 20 May 2012 through 23 May 2012

ER -

Real-time obstructive sleep apnea detection based on ECG derived respiration signal

Abstract

Conference

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