Title
Dynamic Estimation Of Cerebral Blood Flow Using Photoplethysmography Signal During Simulated Apnea
Abstract
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 Zadi131.79
Raichel M. Alex200.68
R. Zhang3166.20
Donald E Watenpaugh433.15
Khosrow Behbehani5164.71