A Novel Adaptive Recursive Least Squares Filter to Remove the Motion Artifact in Seismocardiography
Abstract
:1. Introduction
2. Theory of Adaptive Recursive Least Squares Filter (ARLSF)
2.1. The Principle of Adaptive Recursive Least Squares Filter
2.2. Discussion of the Desired Signal
2.3. Discussion of the Forgetting Factor
3. Measurement Technique
3.1. Hardware System
3.2. Experiment Setup
3.3. Software System
3.3.1. Signal Preprocessing
3.3.2. ARLSF
3.3.3. Feature Extraction
4. Results
4.1. Heartbeat Detection Accuracy
4.2. Heart Rate Estimations
4.3. Bland–Altman Analyzation
5. Discussion and Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Subject No. | ECG Peaks Detected | SCG Peaks Detected | SCG Peaks Missing | Accuracy |
---|---|---|---|---|
1 | 483 | 478 | 5(2) | 98.9% |
2 | 475 | 468 | 7(4) | 98.5% |
3 | 472 | 468 | 4(3) | 99.1% |
4 | 480 | 475 | 5(3) | 98.9% |
5 | 488 | 483 | 5(3) | 98.9% |
6 | 478 | 473 | 5(2) | 98.9% |
7 | 492 | 483 | 9(6) | 98.1% |
8 | 501 | 496 | 5(2) | 99.0% |
9 | 495 | 490 | 5(2) | 98.9% |
10 | 490 | 486 | 4(1) | 99.1% |
11 | 477 | 471 | 6(5) | 98.7% |
12 | 486 | 483 | 3(2) | 99.3% |
13 | 496 | 491 | 5(3) | 98.9% |
14 | 491 | 489 | 2(2) | 99.5% |
15 | 485 | 477 | 8(4) | 98.3% |
16 | 482 | 474 | 8(6) | 98.3% |
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Yu, S.; Liu, S. A Novel Adaptive Recursive Least Squares Filter to Remove the Motion Artifact in Seismocardiography. Sensors 2020, 20, 1596. https://doi.org/10.3390/s20061596
Yu S, Liu S. A Novel Adaptive Recursive Least Squares Filter to Remove the Motion Artifact in Seismocardiography. Sensors. 2020; 20(6):1596. https://doi.org/10.3390/s20061596
Chicago/Turabian StyleYu, Shuai, and Sheng Liu. 2020. "A Novel Adaptive Recursive Least Squares Filter to Remove the Motion Artifact in Seismocardiography" Sensors 20, no. 6: 1596. https://doi.org/10.3390/s20061596
APA StyleYu, S., & Liu, S. (2020). A Novel Adaptive Recursive Least Squares Filter to Remove the Motion Artifact in Seismocardiography. Sensors, 20(6), 1596. https://doi.org/10.3390/s20061596