A Comparative Study to Extract the Diaphragmatic Electromyogram Signal

Lu, Yue; Xian, Ying; Chen, Jiongfeng; Zheng, Zhong

doi:10.1109/bmei.2008.77

Cited by 4 publications

(4 citation statements)

References 10 publications

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“…Morphological tracing is developed based on rigorous mathematical topology. The mathematical morphological method has two fundamental operations (expansion and corrosion) and two basic operations (open and closed operations) [ 15 , 24 ]. Morphological tracing is to traverse the signal using shift and extreme value by using the template function.…”

Section: Methodsmentioning

confidence: 99%

“…EMGdi has spectral aliasing with ECG [ 10 ] (the main frequency band of ECG signal is 20–100 Hz, in which P wave and T wave are below 20 hz, while the main frequency band of diaphragm EMG is 30–400 Hz), which makes it challenging to extract the EMGdi signal without ECG. To remove ECG interference from EMGdi signals, re-searchers have proposed many solutions, including using gating [ 6 ], template reduction [ 11 , 11 , 12 , 13 , 14 ], mathematical morphology [ 15 ], wavelet filter [ 5 , 16 , 17 ] and independent variable analysis [ 17 ]. However, these methods either cannot remove ECG interference while retaining most EMGdi information or are limited in clinical application due to computational complexity and the need to add extra channels.…”

Section: Introductionmentioning

confidence: 99%

“…ICA and wavelet transform methods achieve better performance by increasing the complexity. Lu [ 15 ] and others have proposed a mathematical morphology method to remove ECG interference from EMGdi. This method is simple and easy to implement, but they process all segments of EMGdi and eventually cause EMGdi to decay.…”

Section: Introductionmentioning

confidence: 99%

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Morphological ECG subtraction method for removing ECG artifacts from diaphragm EMG

Guo

Zhang

et al. 2023

THC

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BACKGROUND: Diaphragmatic electromyographic (EMGdi) is a helpful method to reflect the respiratory center’s activity visually. However, the electrocardiogram (ECG) severely affected its weakness, limiting its use. OBJECTIVE: To remove the ECG artifact from the EMGdi, we designed a Morphological ECG subtraction method (MES) based on three steps: 1) ECG localization, 2) morphological tracking, and 3) ECG subtractor. METHODS: We evaluated the MES method against the wavelet-based dual-threshold and stationary wavelet filters using visual and frequency-domain characteristics (median frequency and power ratio). RESULTS: The results show that the MES method can preserve the features of the original diaphragm signal for both surface diaphragm signal (SEMGdi) and clinical collection of diaphragm signal (EMGdi_clinic), and it is more effective than the wavelet-based dual-threshold and stationary wavelet filtering methods. CONCLUSION: The MES method is more effective than other methods. This technique may improve respiratory monitoring and assisted ventilation in patients with respiratory diseases.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Morphological ECG subtraction method for removing ECG artifacts from diaphragm EMG

Guo

Zhang

et al. 2023

THC

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show abstract

“…One is to increase the collection of the ECG signal and use it as a reference input to filter out the interference of the ECG signal by using shear substitution [13], adaptive noise cancellation (ANC) [14] and event synchronization cancellation (ESC) [15]. The other is to directly filter the ECG signal through stationary wavelet transform [11], mathematical morphology [16], and non-linearly scaled wavelets [17] on the EMGdi without ECG acquisition. Nevertheless, these studies focused on the filtering effect of the ECG in EMGdi, and did not perform further feature extraction and analysis on it.…”

Section: Evaluation Of Correlation Between Surface Diaphragm Electromyography and Airflow Using Fixed Sample Entropy In Healthy Subjectsmentioning

confidence: 99%

Evaluation of Correlation Between Surface Diaphragm Electromyography and Airflow Using Fixed Sample Entropy in Healthy Subjects

Ren

Shi

et al. 2022

IEEE Trans. Neural Syst. Rehabil. Eng.

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EMGdi was used as characteristic parameter to build a quantitative relationship with the airflow by polynomial regression analysis. Mean coefficient of determination of all subjects in any breathing state is greater than 0.88. Finally, nonlinear programming method was used to solve a universal fitting coefficient between fSampEn of EMGdi and airflow for each subject to further evaluate the possibility of using surface EMGdi to monitor and control respiratory activity.

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Development of robust, fast and efficient QRS complex detector: a methodological review

Raj

Ray

Shankar

2018

Australas Phys Eng Sci Med

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The basis and reliability for timely diagnosis of cardiovascular diseases depend on the robust and accurate detection of QRS complexes along with the fiducial points in the electrocardiogram (ECG) signal. Despite, the several QRS detection algorithms reported in the literature, the development of an efficient QRS detector remains a challenge in the clinical environment. Therefore, this article summarizes the performance analysis of various QRS detection techniques depending upon three assessment factors which include robustness to noise, computational load, and sensitivity validated on the benchmark MIT-BIH arrhythmia database. Moreover, the limitations of these algorithms are discussed and compared with the standard signal processing algorithms, followed by the future suggestions to develop a reliable and efficient QRS methodology. Further, the suggested method can be implemented on suitable hardware platforms to develop smart health monitoring systems for continuous and long-term ECG assessment for real-time applications.

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A Comparative Study to Extract the Diaphragmatic Electromyogram Signal

Cited by 4 publications

References 10 publications

Morphological ECG subtraction method for removing ECG artifacts from diaphragm EMG

Morphological ECG subtraction method for removing ECG artifacts from diaphragm EMG

Evaluation of Correlation Between Surface Diaphragm Electromyography and Airflow Using Fixed Sample Entropy in Healthy Subjects

Development of robust, fast and efficient QRS complex detector: a methodological review

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