Annals of biomedical engineering
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Motion and noise artifacts (MNA) are a serious obstacle in utilizing photoplethysmogram (PPG) signals for real-time monitoring of vital signs. We present a MNA detection method which can provide a clean vs. corrupted decision on each successive PPG segment. For motion artifact detection, we compute four time-domain parameters: (1) standard deviation of peak-to-peak intervals (2) standard deviation of peak-to-peak amplitudes (3) standard deviation of systolic and diastolic interval ratios, and (4) mean standard deviation of pulse shape. ⋯ Another advantage of our method is its ability to provide highly accurate onset and offset detection times of MNAs. This capability is important for an automated approach to signal reconstruction of only those data points that need to be reconstructed, which is the subject of the companion paper to this article. Finally, our MNA detection algorithm is real-time realizable as the computational speed on the 7-s PPG data segment was found to be only 7 ms with a Matlab code.
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We introduce a new method to reconstruct motion and noise artifact (MNA) contaminated photoplethysmogram (PPG) data. A method to detect MNA corrupted data is provided in a companion paper. Our reconstruction algorithm is based on an iterative motion artifact removal (IMAR) approach, which utilizes the singular spectral analysis algorithm to remove MNA artifacts so that the most accurate estimates of uncorrupted heart rates (HRs) and arterial oxygen saturation (SpO2) values recorded by a pulse oximeter can be derived. ⋯ Two experimental PPG data sets were created with contrived MNA by having subjects perform random forehead and rapid side-to-side finger movements show that; the performance of the IMAR approach on these data sets was quite accurate as non-significant differences in the reconstructed HR and SpO2 were found compared to non-contaminated reference values, in most subjects. In comparison, the accuracy of the TD-ICA was poor as there were significant differences in reconstructed HR and SpO2 values in most subjects. For non-contrived MNA corrupted PPG data, which were collected with subjects performing walking and stair climbing tasks, the IMAR significantly outperformed TD-ICA as the former method provided HR and SpO2 values that were non-significantly different than MNA free reference values.
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The advantage of measuring differential pressure using fluid-filled catheters is that the system is relatively inexpensive, but the readings are not accurate and affected by the common mode pressure (CMP) distortion. High accuracy differential pressure measurements are required in various biomedical applications, such as in fluid-dynamic test rigs, or in the cath-lab, from cardiac valves efficacy to functional assessment of arterial stenoses. We have designed and built a unique system in which the pressure difference was measured along the fluid flow inside a rigid circular tube using a fluid-filled double-lumen catheter. ⋯ A restoration formula was developed based on simultaneous gauge pressure measurements, and was tested in several different cases. Several representative cases are presented and show that the common mode artifact was reduced by factors of 12-27. The restored pressure gradient signal was validated using direct pressure drop measurements, and showed very good agreement.
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The WRAIR projectile concussive impact (PCI) model was developed for preclinical study of concussion. It represents a truly non-invasive closed-head injury caused by a blunt impact. The original design, however, has several drawbacks that limit the manipulation of injury parameters. ⋯ Additional tests confirmed the steel sphere produced linear and rotational motions on the rat's head while remaining within a range that meets the criteria for mTBI. Finally, impact location testing results showed that PCI targeted at the temporoparietal surface of the rat head produced the most prominent gait abnormalities. Using the parameters defined above, pilot studies were conducted to provide initial validation of the PCI model demonstrating quantifiable and significant increases in righting reflex recovery time, axonal damage and astrocyte activation following single and multiple concussions.