ONLINE SINGLE-CHANNEL SEIZURE PREDICTION, BASED ON SEIZURE GENESIS MODEL OF DEPTH-EEG SIGNALS USING EXTENDED KALMAN FILTER

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

SHAYEGH FARZANEH; GHASEMI FAHIMEH; AMIRFATAHI RASOUL; Sadri Saeed; ANSARIFARD KARIM

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: SIGNAL AND DATA PROCESSING Year:2018 | Volume:15 | Issue:1 (SERIAL 35) Page(s): 3-27

Download Full-Text

Persian Verion

View:

535

Download:

Cites:

Information Journal Paper

Title

ONLINE SINGLE-CHANNEL SEIZURE PREDICTION, BASED ON SEIZURE GENESIS MODEL OF DEPTH-EEG SIGNALS USING EXTENDED KALMAN FILTER

Author(s)

Keywords

PHYSIOLOGICAL MODEL OF EPILEPTIC SEIZURESQ1

ONLINE SINGLE-CHANNEL SEIZURE PREDICTIONQ1

KALMAN FILTERQ2

STATE SPACE MODEL (SSM)Q1

EPILEPTICQ2

HIDDEN MARKOV MODEL (HMM)Q1

Abstract

Many efforts have been done to predict EPILEPTIC seizures so far. It seems that some kind of abnormal synchronization among brain areas is responsible for the seizure generation. This is because the synchronization-based algorithms have been the most important methods so far. However, the huge number of EEG channels, which is the main requirement of these methods, make them very difficult to use in practice. In this paper, in order to improve the prediction algorithm, the factor underlying the abnormal brain synchronization, i. e., the imbalance of excitation/inhibition neuronal activity, is taken into account. Accordingly, to extract these hidden excitatory/inhibitory parameters from depth-EEG signals, a realistic physiological model is used. The Output of this model (as a function of model parameters) imitate the depth-EEG signals. On the other hand, based on this model, one can estimate the model parameters behind every real depth-EEG signal, using an identification process. In order to be able to track the temporal variation of the parameter sequences, the model parameters, themselvese, are supposed to behave as a stochastic process. This stochastic process, described by a Hidden Markov Model formerly (HMM) and worked by the current researchists, is now modified to a State Space Model (SSM). The advantage of SSM is that it can be described by some differential equations. By adding these SSM equations to the differential equations producing depth-EEG signals, KALMAN FILTER can be used to identify the parameter sequences underlying signals. Then, these extracted inhibition/excitation sequences can be applied in order to predict seizures. By using the four model parametetrs relevant to excitation/inhibition neuronal activity, extracted from just one channel of depth-EEG signals, the proposed method reached the 100% sensitivity, and 0. 2 FP/h, which is very similar to the multi-channel algorithms. The algorithm can be done in an online manner.

Cites

No record.

References

No record.

Cite

APA: Copy

SHAYEGH, FARZANEH, GHASEMI, FAHIMEH, AMIRFATAHI, RASOUL, Sadri, Saeed, & ANSARIFARD, KARIM. (2018). ONLINE SINGLE-CHANNEL SEIZURE PREDICTION, BASED ON SEIZURE GENESIS MODEL OF DEPTH-EEG SIGNALS USING EXTENDED KALMAN FILTER. SIGNAL AND DATA PROCESSING, 15(1 (SERIAL 35) ), 3-27. SID. https://sid.ir/paper/160911/en

Vancouver: Copy

SHAYEGH FARZANEH, GHASEMI FAHIMEH, AMIRFATAHI RASOUL, Sadri Saeed, ANSARIFARD KARIM. ONLINE SINGLE-CHANNEL SEIZURE PREDICTION, BASED ON SEIZURE GENESIS MODEL OF DEPTH-EEG SIGNALS USING EXTENDED KALMAN FILTER. SIGNAL AND DATA PROCESSING[Internet]. 2018;15(1 (SERIAL 35) ):3-27. Available from: https://sid.ir/paper/160911/en

IEEE: Copy

FARZANEH SHAYEGH, FAHIMEH GHASEMI, RASOUL AMIRFATAHI, Saeed Sadri, and KARIM ANSARIFARD, “ONLINE SINGLE-CHANNEL SEIZURE PREDICTION, BASED ON SEIZURE GENESIS MODEL OF DEPTH-EEG SIGNALS USING EXTENDED KALMAN FILTER,” SIGNAL AND DATA PROCESSING, vol. 15, no. 1 (SERIAL 35) , pp. 3–27, 2018, [Online]. Available: https://sid.ir/paper/160911/en

Related Journal Papers