Key result
The I2DTCWT technique outperformed other DTCWT processing methods in reducing motion artifacts and allowed for safe extraction of respiratory information with less computational cost than MASIMO SET.
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The proposed I2DTCWT technique effectively reduces motion artifacts in PPG signals, allowing for accurate SpO2 estimation and extraction of respiratory information with lower computational cost than existing methods.
In addition to estimation of arterial blood oxygen saturation (SpO2), pulse oximeter's photoplethysmographic (PPG) signals can be well utilized for extracting the vital respiratory information. The motion artifacts (MA) in PPGs not only make SpO2estimations unreliable and inaccurate but also make it difficult to extract respiratory information. Addressing this issue, for the first time, we propose a novel approach called “ICA-based improved dual-tree complex wavelet transform (I2DTCWT)” technique, for efficient reduction of MAs leaving the respiratory information undisturbed. The method makes use of source separation ability of independent component analysis (ICA) along with computationally efficient modified DTCWT processing. A prototype pulse oximeter was developed and performance analysis of DTCWT, modified DTCWT and I2DTCWT processing methods was carried out using PPG data recorded with intentionally created MAs (horizontal MA, vertical MA, and bending MA). Experimental results demonstrated the efficiency of DTCWT processing methods in restoring PPG morphology and proved that there is a significant improvement guaranteed in reducing MAs with the presented methods. Statistical performance is evaluated in terms of measures like signal-to-noise ratio, normalized root mean square error, and correlation analysis with correlation co-efficient measure. The I2DTCWT outperformed other DTCWT processing methods in respect of MA reduction and the computed spectra revealed that safe extraction of respiratory information is guaranteed from these MA reduced PPGs. The proposed method is also validated by comparing with the well established signal extraction technology of MASIMO pulse oximeters, for which the discrete saturation transform (DST) is the key element. The %SpO2estimations from processed PPGs by the proposed method closely followed the estimations based on DST and were very close to that of clean sections of PPG. In addition, the proposed method resulted in less computation cost compared to the MASIMO SET. Digital volume pulse waveform contour analysis is also performed on MA reduced PPGs to validate PPG morphology and the conventional parameters are calculated for assessing the arterial stiffness.
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Ram et al. (2013) studied Motion artifacts in photoplethysmographic (PPG) signals. ICA-based improved dual-tree complex wavelet transform (I2DTCWT) technique vs. DTCWT, modified DTCWT, and MASIMO SET was evaluated on Motion artifact reduction and SpO2 estimation accuracy. The I2DTCWT technique outperformed other DTCWT processing methods in reducing motion artifacts and allowed for safe extraction of respiratory information with less computational cost than MASIMO SET.
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