DocumentCode
1621357
Title
Identification of Vascular Dynamics and Estimation of the Cardiac Output Waveform from Wearable PPG Sensors
Author
McCombie, D. ; Asada, H. ; Reisner, A.
Author_Institution
Dept. of Mechanical Eng., MIT, Cambridge, MA
fYear
2006
Firstpage
3490
Lastpage
3493
Abstract
A method for estimating cardiovascular dynamics and cardiac output waveforms using signals derived from two PPG sensors is presented. The method employs a novel signal-processing algorithm known as Laguerre model blind system identification to identify the vascular dynamics associated with the measured PPG signals. A unique deconvolution method is then used with the identified Laguerre models to estimate the cardiac output waveform. Initial results implementing the method on data derived from a human subject is presented. Results show good agreement between the morphology of the estimated waveform and the typical morphology of the human cardiac output waveform
Keywords
cardiovascular system; deconvolution; medical signal processing; stochastic processes; wearable computers; Laguerre model blind system identification; cardiac output estimation; cardiovascular dynamics; deconvolution; wearable PPG sensors; Biological system modeling; Biosensors; Cardiovascular system; Deconvolution; Equations; Finite impulse response filter; Mechanical sensors; Sensor systems; USA Councils; Wearable sensors; biomedical signal processing; non-invasive cardiovascular monitoring; system identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location
Shanghai
Print_ISBN
0-7803-8741-4
Type
conf
DOI
10.1109/IEMBS.2005.1617231
Filename
1617231
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