Detection of Atrial Fibrillation in Compressively Sensed Electrocardiogram for Remote Monitoring
The objective of this paper is to develop an optimized system to detect Atrial Fibrillation (AF) in compressively sensed electrocardiogram (ECG) for long-term remote patient monitoring. A three-stage system was developed to 1) reject ECG of poor signal quality, 2) detect AF in compressively sensed E...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-07-01
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| Series: | Frontiers in Electronics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/felec.2022.906689/full |
| _version_ | 1811318767019360256 |
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| author | Mohamed Abdelazez Sreeraman Rajan Adrian D. C. Chan |
| author_facet | Mohamed Abdelazez Sreeraman Rajan Adrian D. C. Chan |
| author_sort | Mohamed Abdelazez |
| collection | DOAJ |
| description | The objective of this paper is to develop an optimized system to detect Atrial Fibrillation (AF) in compressively sensed electrocardiogram (ECG) for long-term remote patient monitoring. A three-stage system was developed to 1) reject ECG of poor signal quality, 2) detect AF in compressively sensed ECG, and 3) detect AF in selectively reconstructed ECG. The Long-Term AF Database (LTAFDB), sampled at 128 Hz using a 12-bit ADC with a range of 20 mV, was used to validate the system. The LTAFDB had 83,315 normal and 82,435 AF rhythm 30 s ECG segments. Clean ECG from the LTAFDB was artificially contaminated with motion artifact to achieve −12 to 12 dB Signal-to-Noise Ratio (SNR) in steps of 3 dB. The contaminated ECG was compressively sensed at 50% and 75% compression ratio (CR). The system was evaluated using average precision (AP), the area under the curve (AUC) of the receiver operator characteristic curve, and the F1 score. The system was optimized to maximize the AP and minimize ECG rejection and reconstruction ratios. The optimized system for 50% CR had 0.72 AP, 0.63 AUC, and 0.58 F1 score, 0.38 rejection ratio, and 0.38 reconstruction ratio. The optimized system for 75% CR had 0.72 AP, 0.63 AUC, and 0.59 F1 score, 0.40 rejection ratio, and 0.35 reconstruction ratio. Challenges for long-term AF monitoring are the short battery life of monitors and the high false alarm rate due to artifacts. The proposed system improves the short battery life through compressive sensing while reducing false alarms (high AP) and ECG reconstruction (low reconstruction ratio). |
| first_indexed | 2024-04-13T12:31:13Z |
| format | Article |
| id | doaj.art-ea77a697228a4877bf3135496cb32a6f |
| institution | Directory Open Access Journal |
| issn | 2673-5857 |
| language | English |
| last_indexed | 2024-04-13T12:31:13Z |
| publishDate | 2022-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Electronics |
| spelling | doaj.art-ea77a697228a4877bf3135496cb32a6f2022-12-22T02:46:51ZengFrontiers Media S.A.Frontiers in Electronics2673-58572022-07-01310.3389/felec.2022.906689906689Detection of Atrial Fibrillation in Compressively Sensed Electrocardiogram for Remote MonitoringMohamed AbdelazezSreeraman RajanAdrian D. C. ChanThe objective of this paper is to develop an optimized system to detect Atrial Fibrillation (AF) in compressively sensed electrocardiogram (ECG) for long-term remote patient monitoring. A three-stage system was developed to 1) reject ECG of poor signal quality, 2) detect AF in compressively sensed ECG, and 3) detect AF in selectively reconstructed ECG. The Long-Term AF Database (LTAFDB), sampled at 128 Hz using a 12-bit ADC with a range of 20 mV, was used to validate the system. The LTAFDB had 83,315 normal and 82,435 AF rhythm 30 s ECG segments. Clean ECG from the LTAFDB was artificially contaminated with motion artifact to achieve −12 to 12 dB Signal-to-Noise Ratio (SNR) in steps of 3 dB. The contaminated ECG was compressively sensed at 50% and 75% compression ratio (CR). The system was evaluated using average precision (AP), the area under the curve (AUC) of the receiver operator characteristic curve, and the F1 score. The system was optimized to maximize the AP and minimize ECG rejection and reconstruction ratios. The optimized system for 50% CR had 0.72 AP, 0.63 AUC, and 0.58 F1 score, 0.38 rejection ratio, and 0.38 reconstruction ratio. The optimized system for 75% CR had 0.72 AP, 0.63 AUC, and 0.59 F1 score, 0.40 rejection ratio, and 0.35 reconstruction ratio. Challenges for long-term AF monitoring are the short battery life of monitors and the high false alarm rate due to artifacts. The proposed system improves the short battery life through compressive sensing while reducing false alarms (high AP) and ECG reconstruction (low reconstruction ratio).https://www.frontiersin.org/articles/10.3389/felec.2022.906689/fullsignal quality assessmentremote healthcarecompressive sensingelectrocardiogrammachine learningatrial fibrillation |
| spellingShingle | Mohamed Abdelazez Sreeraman Rajan Adrian D. C. Chan Detection of Atrial Fibrillation in Compressively Sensed Electrocardiogram for Remote Monitoring Frontiers in Electronics signal quality assessment remote healthcare compressive sensing electrocardiogram machine learning atrial fibrillation |
| title | Detection of Atrial Fibrillation in Compressively Sensed Electrocardiogram for Remote Monitoring |
| title_full | Detection of Atrial Fibrillation in Compressively Sensed Electrocardiogram for Remote Monitoring |
| title_fullStr | Detection of Atrial Fibrillation in Compressively Sensed Electrocardiogram for Remote Monitoring |
| title_full_unstemmed | Detection of Atrial Fibrillation in Compressively Sensed Electrocardiogram for Remote Monitoring |
| title_short | Detection of Atrial Fibrillation in Compressively Sensed Electrocardiogram for Remote Monitoring |
| title_sort | detection of atrial fibrillation in compressively sensed electrocardiogram for remote monitoring |
| topic | signal quality assessment remote healthcare compressive sensing electrocardiogram machine learning atrial fibrillation |
| url | https://www.frontiersin.org/articles/10.3389/felec.2022.906689/full |
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