Multistage Adaptive Noise Cancellation Scheme for Heart Rate Estimation From PPG Signal Utilizing Mode Based Decomposition of Acceleration Data
Photoplethysmography (PPG) has recently become a popular method for heart rate estimation due to its simple acquisition technique. However, the main challenge in determining the heart rate from the PPG signals is its high vulnerability to motion artifacts (MA). In this paper, a new scheme is propose...
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9759386/ |
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| author | Md. Toky Foysal Talukdar Naqib Sad Pathan Shaikh Anowarul Fattah Muhammad Quamruzzaman Mohammad Saquib |
| author_facet | Md. Toky Foysal Talukdar Naqib Sad Pathan Shaikh Anowarul Fattah Muhammad Quamruzzaman Mohammad Saquib |
| author_sort | Md. Toky Foysal Talukdar |
| collection | DOAJ |
| description | Photoplethysmography (PPG) has recently become a popular method for heart rate estimation due to its simple acquisition technique. However, the main challenge in determining the heart rate from the PPG signals is its high vulnerability to motion artifacts (MA). In this paper, a new scheme is proposed for heart rate estimation through frame selective multistage adaptive noise cancellation (MANC). The frame selective approach determines the specific frames of PPG signal which are significantly interfered with MA, and the MA removal operation is only employed over those specific frames. The MANC scheme is implemented through the Least Mean Square (LMS) algorithm in which instead of the conventional approach of using accelerometer data directly, we propose to utilize mode-based decomposed 3-channel accelerometer data as reference signals independently in a sequential manner. The use of decomposed modes offers high degrees of controllability in the ANC scheme depending on the overlap between the spectra corresponding to MA and heart rate, thereby offers effective denoising. A peak searching algorithm is employed to estimate heart rate-related peaks from the resulting noise-reduced PPG signal. The novelty of the proposed scheme lies in the use of decomposed reference inputs to the MANC algorithm (named as DERMANC scheme) which is accomplished through both empirical mode decomposition (EMD) and variational mode decomposition (VMD). Performance of the proposed EMD and VMD based schemes (E-DERMANC and V-DERMANC) has been tested on a publicly available dataset and very satisfactory results are obtained in terms of estimation accuracy and computational time (0.95 and 1.10 BPM, respectively on 12 recordings) that makes the schemes worthy to be implemented in wearable devices. |
| first_indexed | 2024-04-13T18:56:39Z |
| format | Article |
| id | doaj.art-b68ebb0bb86c41b0a994df6f4896bc22 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-13T18:56:39Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-b68ebb0bb86c41b0a994df6f4896bc222022-12-22T02:34:13ZengIEEEIEEE Access2169-35362022-01-0110597595977110.1109/ACCESS.2022.31687429759386Multistage Adaptive Noise Cancellation Scheme for Heart Rate Estimation From PPG Signal Utilizing Mode Based Decomposition of Acceleration DataMd. Toky Foysal Talukdar0Naqib Sad Pathan1https://orcid.org/0000-0002-1571-8221Shaikh Anowarul Fattah2https://orcid.org/0000-0001-8090-2327Muhammad Quamruzzaman3Mohammad Saquib4https://orcid.org/0000-0002-9641-2397Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, BangladeshDepartment of Electrical and Electronic Engineering, Chittagong University of Engineering and Technology, Chattogram, BangladeshDepartment of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, BangladeshDepartment of Electrical and Electronic Engineering, Chittagong University of Engineering and Technology, Chattogram, BangladeshDepartment of Electrical Engineering, The University of Texas at Dallas, Richardson, TX, USAPhotoplethysmography (PPG) has recently become a popular method for heart rate estimation due to its simple acquisition technique. However, the main challenge in determining the heart rate from the PPG signals is its high vulnerability to motion artifacts (MA). In this paper, a new scheme is proposed for heart rate estimation through frame selective multistage adaptive noise cancellation (MANC). The frame selective approach determines the specific frames of PPG signal which are significantly interfered with MA, and the MA removal operation is only employed over those specific frames. The MANC scheme is implemented through the Least Mean Square (LMS) algorithm in which instead of the conventional approach of using accelerometer data directly, we propose to utilize mode-based decomposed 3-channel accelerometer data as reference signals independently in a sequential manner. The use of decomposed modes offers high degrees of controllability in the ANC scheme depending on the overlap between the spectra corresponding to MA and heart rate, thereby offers effective denoising. A peak searching algorithm is employed to estimate heart rate-related peaks from the resulting noise-reduced PPG signal. The novelty of the proposed scheme lies in the use of decomposed reference inputs to the MANC algorithm (named as DERMANC scheme) which is accomplished through both empirical mode decomposition (EMD) and variational mode decomposition (VMD). Performance of the proposed EMD and VMD based schemes (E-DERMANC and V-DERMANC) has been tested on a publicly available dataset and very satisfactory results are obtained in terms of estimation accuracy and computational time (0.95 and 1.10 BPM, respectively on 12 recordings) that makes the schemes worthy to be implemented in wearable devices.https://ieeexplore.ieee.org/document/9759386/Acceleration dataadaptive noise cancellation (ANC)empirical mode decomposition (EMD)heart ratemotion artifactsphotoplethysmography (PPG) |
| spellingShingle | Md. Toky Foysal Talukdar Naqib Sad Pathan Shaikh Anowarul Fattah Muhammad Quamruzzaman Mohammad Saquib Multistage Adaptive Noise Cancellation Scheme for Heart Rate Estimation From PPG Signal Utilizing Mode Based Decomposition of Acceleration Data IEEE Access Acceleration data adaptive noise cancellation (ANC) empirical mode decomposition (EMD) heart rate motion artifacts photoplethysmography (PPG) |
| title | Multistage Adaptive Noise Cancellation Scheme for Heart Rate Estimation From PPG Signal Utilizing Mode Based Decomposition of Acceleration Data |
| title_full | Multistage Adaptive Noise Cancellation Scheme for Heart Rate Estimation From PPG Signal Utilizing Mode Based Decomposition of Acceleration Data |
| title_fullStr | Multistage Adaptive Noise Cancellation Scheme for Heart Rate Estimation From PPG Signal Utilizing Mode Based Decomposition of Acceleration Data |
| title_full_unstemmed | Multistage Adaptive Noise Cancellation Scheme for Heart Rate Estimation From PPG Signal Utilizing Mode Based Decomposition of Acceleration Data |
| title_short | Multistage Adaptive Noise Cancellation Scheme for Heart Rate Estimation From PPG Signal Utilizing Mode Based Decomposition of Acceleration Data |
| title_sort | multistage adaptive noise cancellation scheme for heart rate estimation from ppg signal utilizing mode based decomposition of acceleration data |
| topic | Acceleration data adaptive noise cancellation (ANC) empirical mode decomposition (EMD) heart rate motion artifacts photoplethysmography (PPG) |
| url | https://ieeexplore.ieee.org/document/9759386/ |
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