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Tonometric arterial pulse sensor with noise cancellation.
Edward J Ciaccio1, Gary M Drzewiecki
1Department of Pharmacology, Columbia University, New York, NY 10032, USA. ciaccio@columbia.edu
IEEE Transactions on Bio-Medical Engineering
|October 8, 2008
Summary
Noise cancellation techniques significantly improve arterial tonometry by removing motion artifacts. Adaptive algorithms like LMS and DSD offer superior noise reduction compared to fixed weighting for accurate arterial pressure waveform recording.
Area of Science:
- Biomedical Engineering
- Signal Processing
Background:
- Arterial tonometry noninvasively records arterial pressure waveforms.
- Motion artifacts degrade the quality of tonometer signals.
Purpose of the Study:
- To develop and compare noise cancellation methods for arterial tonometry.
- To reduce motion artifact and noise in arterial pulse signals.
Main Methods:
- Constructed an arterial tonometer with two piezoelectric transducers.
- Applied noise cancellation using fixed weighting, Least Mean Squares (LMS), and Differential Steepest Descent (DSD) algorithms.
- Used a common-mode reference input for noise cancellation.
Main Results:
- Adaptive algorithms (LMS, DSD) showed lower mean peak-to-peak and point-to-point errors than fixed weighting.
- DSD algorithm yielded the lowest mean errors.
- Noise cancellation substantially reduced motion artifact and noise.
Conclusions:
- Adaptive weighting provides superior noise cancellation in arterial tonometry compared to fixed weighting.
- Common-mode reference input effectively reduces artifacts in tonometric signals.
- This technique enhances the accuracy of noninvasive arterial pressure waveform recording.
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