Title | ||
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Dynamic Estimation Of Cerebral Blood Flow Using Photoplethysmography Signal During Simulated Apnea |
Abstract | ||
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monitoring apnea-induced cerebral blood flow oscillations is of importance for assessing apnea patient brain health. Using an autoregressive moving average model, peak and trough values of cerebral blood flow were estimated from a concurrently recorded forehead photoplethysmography signal. Preliminary testing of the method in 7 subjects (4 F, 32 +/- 4yrs., BMI 24.57 +/- 3.87 kg/m(2)) using a breath hold paradigm for simulating apnea shows that maximum mean and standard deviation of the prediction error is -1.10 +/- 8.49 cm/s and the maximum root mean squared of the error is 8.92 cm/s |
Year | DOI | Venue |
---|---|---|
2019 | 10.1109/EMBC.2019.8856611 | 2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) |
Field | DocType | Volume |
Biomedical engineering,Forehead,Autoregressive–moving-average model,Computer vision,Mean squared prediction error,Computer science,Photoplethysmogram,Apnea,Artificial intelligence,Root mean square,Cerebral blood flow,Standard deviation | Conference | 2019 |
ISSN | Citations | PageRank |
1557-170X | 0 | 0.34 |
References | Authors | |
0 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Armin Soltan Zadi | 1 | 3 | 1.79 |
Raichel M. Alex | 2 | 0 | 0.68 |
R. Zhang | 3 | 16 | 6.20 |
Donald E Watenpaugh | 4 | 3 | 3.15 |
Khosrow Behbehani | 5 | 16 | 4.71 |