A Novel Personalized Motion and Noise Artifact (MNA) Detection Method for Smartphone Photoplethysmograph (PPG) Signals
Photoplethysmography (PPG) is a technique to detect blood volume changes in an optical way. Representative PPG applications are the measurements of oxygen saturation, heart rate, and respiratory rate. However, the PPG signals are sensitive to motion and noise artifacts (MNAs), especially when they a...
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8493515/ |
| _version_ | 1818913157930811392 |
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| author | Fatemehsadat Tabei Rajnish Kumar Tra Nguyen Phan David D. McManus Jo Woon Chong |
| author_facet | Fatemehsadat Tabei Rajnish Kumar Tra Nguyen Phan David D. McManus Jo Woon Chong |
| author_sort | Fatemehsadat Tabei |
| collection | DOAJ |
| description | Photoplethysmography (PPG) is a technique to detect blood volume changes in an optical way. Representative PPG applications are the measurements of oxygen saturation, heart rate, and respiratory rate. However, the PPG signals are sensitive to motion and noise artifacts (MNAs), especially when they are obtained from smartphone cameras. Moreover, the PPG signals are different among users and each individual's PPG signal has a unique characteristic. Hence, an effective MNA detection and reduction method for smartphone PPG signals, which adapts itself to each user in a personalized way, is highly demanded. In this paper, a concept of the probabilistic neural network is introduced to be used with the proposed extracted parameters. The signal amplitude, standard deviation of peak to peak time intervals and amplitudes, along with the mean of moving standard deviation, signal slope changes, and the optimal autoregressive model order are proposed for effective MNA detection. Accordingly, the performance of the proposed personalized algorithm is compared with conventional MNA detection algorithms. As for the performance metrics, we considered accuracy, sensitivity, and specificity. The results show that the overall performance of the personalized MNA detection is enhanced compared to the generalized algorithm. The average values of the accuracy, sensitivity, and specificity of the personalized one are 98.07%, 92.6%, and 99.78%, respectively, while these are 89.92%, 84.21%, and 93.63% for the general one. |
| first_indexed | 2024-12-19T23:26:02Z |
| format | Article |
| id | doaj.art-bf7abf1da2eb472e922a4781bd869a7d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T23:26:02Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-bf7abf1da2eb472e922a4781bd869a7d2022-12-21T20:01:52ZengIEEEIEEE Access2169-35362018-01-016604986051210.1109/ACCESS.2018.28758738493515A Novel Personalized Motion and Noise Artifact (MNA) Detection Method for Smartphone Photoplethysmograph (PPG) SignalsFatemehsadat Tabei0https://orcid.org/0000-0002-1639-1531Rajnish Kumar1Tra Nguyen Phan2David D. McManus3Jo Woon Chong4Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, USADepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, USADepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, USADepartment of Medicine, Division of Cardiovascular Medicine, University of Massachusetts Medical School, Worcester, MA, USADepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, USAPhotoplethysmography (PPG) is a technique to detect blood volume changes in an optical way. Representative PPG applications are the measurements of oxygen saturation, heart rate, and respiratory rate. However, the PPG signals are sensitive to motion and noise artifacts (MNAs), especially when they are obtained from smartphone cameras. Moreover, the PPG signals are different among users and each individual's PPG signal has a unique characteristic. Hence, an effective MNA detection and reduction method for smartphone PPG signals, which adapts itself to each user in a personalized way, is highly demanded. In this paper, a concept of the probabilistic neural network is introduced to be used with the proposed extracted parameters. The signal amplitude, standard deviation of peak to peak time intervals and amplitudes, along with the mean of moving standard deviation, signal slope changes, and the optimal autoregressive model order are proposed for effective MNA detection. Accordingly, the performance of the proposed personalized algorithm is compared with conventional MNA detection algorithms. As for the performance metrics, we considered accuracy, sensitivity, and specificity. The results show that the overall performance of the personalized MNA detection is enhanced compared to the generalized algorithm. The average values of the accuracy, sensitivity, and specificity of the personalized one are 98.07%, 92.6%, and 99.78%, respectively, while these are 89.92%, 84.21%, and 93.63% for the general one.https://ieeexplore.ieee.org/document/8493515/Personalizationphotoplethysmography (PPG)motion noise artifactssignal quality index |
| spellingShingle | Fatemehsadat Tabei Rajnish Kumar Tra Nguyen Phan David D. McManus Jo Woon Chong A Novel Personalized Motion and Noise Artifact (MNA) Detection Method for Smartphone Photoplethysmograph (PPG) Signals IEEE Access Personalization photoplethysmography (PPG) motion noise artifacts signal quality index |
| title | A Novel Personalized Motion and Noise Artifact (MNA) Detection Method for Smartphone Photoplethysmograph (PPG) Signals |
| title_full | A Novel Personalized Motion and Noise Artifact (MNA) Detection Method for Smartphone Photoplethysmograph (PPG) Signals |
| title_fullStr | A Novel Personalized Motion and Noise Artifact (MNA) Detection Method for Smartphone Photoplethysmograph (PPG) Signals |
| title_full_unstemmed | A Novel Personalized Motion and Noise Artifact (MNA) Detection Method for Smartphone Photoplethysmograph (PPG) Signals |
| title_short | A Novel Personalized Motion and Noise Artifact (MNA) Detection Method for Smartphone Photoplethysmograph (PPG) Signals |
| title_sort | novel personalized motion and noise artifact mna detection method for smartphone photoplethysmograph ppg signals |
| topic | Personalization photoplethysmography (PPG) motion noise artifacts signal quality index |
| url | https://ieeexplore.ieee.org/document/8493515/ |
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