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Time Delay Estimation between Two Photoplethysmography Signals under Noisy Conditions

Teymoori, Parisa | 2015

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 46959 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Zahedi, Edmond; Shamsollahi, Mohammad Bagher
  7. Abstract:
  8. In this project, a processing algorithm is approached which is resistant against environmental and motion noises to find the pulse transmission time using two photoplethysmography signals. For this purpose, a new processing framework is checked and generalized for photoplethysmography signals. Already, this processing framework had impressive results. The considered processing method is obtained by offering a dynamic model for the signal and using it in a Kalman filter structure. For the photoplethysmography signals, with modeling every beat of signal to a Gaussian three or four sum form and with adding self-returned equations for model parameters, a nonlinear signal model is obtained. Then, this nonlinear model is used in a generalized Kalman filter structure and with considering the signal as the filter input, the processing ideas on the model output, including signal and its parameters, are implemented. The considering ideas are based on the suggested method and in fact they are for finding the pulse transmission time with removing noise from these signals in noise condition and then finding signal model parameters and expressing the pulse transmission time with these parameters. In noise removing method, the suggested filter is modulated with the frequency domain filters to estimate some filter parameters which that causes improved results. Finally, by implementing the suggested methods on the photoplethysmography signals gotten from healthy people, results for removing noise and calculating the pulse transmission time are quantitatively and qualitatively evaluated and compared with current and valid methods. In the removing noise field, the proposed method based on modulating the frequency domain filters and the suggested framework, has a great performance comparing with the other methods in a wide SNR value domain of input. Also qualitative evaluations show that the suggested method has better results rather than old methods in removing motion artifacts. The quantitative evaluations in calculating the pulse transmission time using the suggested method (which uses the estimated parameters by the kalman filter for calculating the pulse transmission time), show that has greater results rather than the old methods. Even the suggested method results comparing with the results due applying old methods on the removed noise signals using the suggested method show better performance. So, the provided structure in this project can be counted as a new developed effective step in processing photoplethysmography signals
  9. Keywords:
  10. Pulse Transit Time (PTT) ; Dynamics Models ; Kalman Filters ; Photoplethysmography ; Motion Artifacts

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