An improved Kalman filter in Photoplethysmography DC component denoising for cardiorespiratory analysis
Objective: To design an improved accuracy filter for photoplethysmography Direct Current (DC) component denoising and clinically applicable measurement design. Methodology: The data source for this study was obtained from Physionet. The obtained PPG signal was mixed with seven different types of noi...
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Pakistan Medical Association
2022
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| author | Muhammad Kashif, Muhammad Kashif Muhammad Fahmi, Muhammad Fahmi Dita Aprilia Hariyani, Dita Aprilia Hariyani Akif Rahmatilah, Akif Rahmatilah Khusnul Ain, Khusnul Ain Yunus Susilo, Yunus Susilo Syahrom, Ardiyansyah Suryani Dyah Astuti, Suryani Dyah Astuti |
| author_facet | Muhammad Kashif, Muhammad Kashif Muhammad Fahmi, Muhammad Fahmi Dita Aprilia Hariyani, Dita Aprilia Hariyani Akif Rahmatilah, Akif Rahmatilah Khusnul Ain, Khusnul Ain Yunus Susilo, Yunus Susilo Syahrom, Ardiyansyah Suryani Dyah Astuti, Suryani Dyah Astuti |
| author_sort | Muhammad Kashif, Muhammad Kashif |
| collection | ePrints |
| description | Objective: To design an improved accuracy filter for photoplethysmography Direct Current (DC) component denoising and clinically applicable measurement design. Methodology: The data source for this study was obtained from Physionet. The obtained PPG signal was mixed with seven different types of noises. The seven different derivates of PPG signals were denoised using 4 types of denoisers that were designed using Infinite impulse response (IIR), finite impulse response (FIR), Kalman, and improved Kalman filters. The difference can be measured by the SNR value, the lower signal to noise ratio (SNR) value shows higher noise in the signal. Results: SNR value achieved on FIR filter was 7.54dB, IIR 9.08dB, Kalman 18.96dB and the maximum SNR achieved on the improved Kalman filter which is 24.76 dB. Conclusion: It can be said that the Improved Kalman Filter is more appropriate for DC signal denoising in PPG signals rather than the FIR filter, IIR filter, and Kalman filter. |
| first_indexed | 2024-03-05T21:28:59Z |
| format | Article |
| id | utm.eprints-103908 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T21:28:59Z |
| publishDate | 2022 |
| publisher | Pakistan Medical Association |
| record_format | dspace |
| spelling | utm.eprints-1039082023-12-06T04:38:55Z http://eprints.utm.my/103908/ An improved Kalman filter in Photoplethysmography DC component denoising for cardiorespiratory analysis Muhammad Kashif, Muhammad Kashif Muhammad Fahmi, Muhammad Fahmi Dita Aprilia Hariyani, Dita Aprilia Hariyani Akif Rahmatilah, Akif Rahmatilah Khusnul Ain, Khusnul Ain Yunus Susilo, Yunus Susilo Syahrom, Ardiyansyah Suryani Dyah Astuti, Suryani Dyah Astuti QC Physics TJ Mechanical engineering and machinery Objective: To design an improved accuracy filter for photoplethysmography Direct Current (DC) component denoising and clinically applicable measurement design. Methodology: The data source for this study was obtained from Physionet. The obtained PPG signal was mixed with seven different types of noises. The seven different derivates of PPG signals were denoised using 4 types of denoisers that were designed using Infinite impulse response (IIR), finite impulse response (FIR), Kalman, and improved Kalman filters. The difference can be measured by the SNR value, the lower signal to noise ratio (SNR) value shows higher noise in the signal. Results: SNR value achieved on FIR filter was 7.54dB, IIR 9.08dB, Kalman 18.96dB and the maximum SNR achieved on the improved Kalman filter which is 24.76 dB. Conclusion: It can be said that the Improved Kalman Filter is more appropriate for DC signal denoising in PPG signals rather than the FIR filter, IIR filter, and Kalman filter. Pakistan Medical Association 2022 Article PeerReviewed Muhammad Kashif, Muhammad Kashif and Muhammad Fahmi, Muhammad Fahmi and Dita Aprilia Hariyani, Dita Aprilia Hariyani and Akif Rahmatilah, Akif Rahmatilah and Khusnul Ain, Khusnul Ain and Yunus Susilo, Yunus Susilo and Syahrom, Ardiyansyah and Suryani Dyah Astuti, Suryani Dyah Astuti (2022) An improved Kalman filter in Photoplethysmography DC component denoising for cardiorespiratory analysis. Rawal Medical Journal, 47 (3). pp. 743-747. ISSN 0303-5212 https://www.rmj.org.pk/?mno=48464 NA |
| spellingShingle | QC Physics TJ Mechanical engineering and machinery Muhammad Kashif, Muhammad Kashif Muhammad Fahmi, Muhammad Fahmi Dita Aprilia Hariyani, Dita Aprilia Hariyani Akif Rahmatilah, Akif Rahmatilah Khusnul Ain, Khusnul Ain Yunus Susilo, Yunus Susilo Syahrom, Ardiyansyah Suryani Dyah Astuti, Suryani Dyah Astuti An improved Kalman filter in Photoplethysmography DC component denoising for cardiorespiratory analysis |
| title | An improved Kalman filter in Photoplethysmography DC component denoising for cardiorespiratory analysis |
| title_full | An improved Kalman filter in Photoplethysmography DC component denoising for cardiorespiratory analysis |
| title_fullStr | An improved Kalman filter in Photoplethysmography DC component denoising for cardiorespiratory analysis |
| title_full_unstemmed | An improved Kalman filter in Photoplethysmography DC component denoising for cardiorespiratory analysis |
| title_short | An improved Kalman filter in Photoplethysmography DC component denoising for cardiorespiratory analysis |
| title_sort | improved kalman filter in photoplethysmography dc component denoising for cardiorespiratory analysis |
| topic | QC Physics TJ Mechanical engineering and machinery |
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