Using Constrained Square-Root Cubature Kalman Filter for Quantifying the Severity of Epileptic Activities in Mice
(1) Background: Quantification of severity of epileptic activities, especially during electrical stimulation, is an unmet need for seizure control and evaluation of therapeutic efficacy. In this study, a parameter ratio derived from constrained square-root cubature Kalman filter (CSCKF) was formulat...
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MDPI AG
2022-07-01
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| Series: | Biomedicines |
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| Online Access: | https://www.mdpi.com/2227-9059/10/7/1588 |
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| author | Chih-Hsu Huang Peng-Hsiang Wang Ming-Shaung Ju Chou-Ching K. Lin |
| author_facet | Chih-Hsu Huang Peng-Hsiang Wang Ming-Shaung Ju Chou-Ching K. Lin |
| author_sort | Chih-Hsu Huang |
| collection | DOAJ |
| description | (1) Background: Quantification of severity of epileptic activities, especially during electrical stimulation, is an unmet need for seizure control and evaluation of therapeutic efficacy. In this study, a parameter ratio derived from constrained square-root cubature Kalman filter (CSCKF) was formulated to quantify the excitability of local neural network and compared with three commonly used indicators, namely, band power, Teager energy operator, and sample entropy, to objectively determine their effectiveness in quantifying the severity of epileptiform discharges in mice. (2) Methods: A set of one normal and four types of epileptic EEGs was generated by a mathematical model. EEG data of epileptiform discharges during two types of electrical stimulation were recorded in 20 mice. Then, EEG segments of 5 s in length before, during and after the real and sham stimulation were collected. Both simulated and experimental data were used to compare the consistency and differences among the performance indicators. (3) Results: For the experimental data, the results of the four indicators were inconsistent during both types of electrical stimulation, although there was a trend that seizure severity changed with the indicators. For the simulated data, when the simulated EEG segments were used, the results of all four indicators were similar; however, this trend did not match the trend of excitability of the model network. In the model output which retained the DC component, except for the CSCKF parameter ratio, the results of the other three indicators were almost identical to those using the simulated EEG. For CSCKF, the parameter ratio faithfully reflected the excitability of the neural network. (4) Conclusion: For common EEG, CSCKF did not outperform other commonly used performance indicators. However, for EEG with a preserved DC component, CSCKF had the potential to quantify the excitability of the neural network and the associated severity of epileptiform discharges. |
| first_indexed | 2024-03-09T12:12:53Z |
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| language | English |
| last_indexed | 2024-03-09T12:12:53Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomedicines |
| spelling | doaj.art-75bfde4494514a4e951291ce40283f8f2023-11-30T22:50:32ZengMDPI AGBiomedicines2227-90592022-07-01107158810.3390/biomedicines10071588Using Constrained Square-Root Cubature Kalman Filter for Quantifying the Severity of Epileptic Activities in MiceChih-Hsu Huang0Peng-Hsiang Wang1Ming-Shaung Ju2Chou-Ching K. Lin3Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 70101, TaiwanDepartment of Mechanical Engineering, National Cheng Kung University, Tainan 70101, TaiwanDepartment of Mechanical Engineering, National Cheng Kung University, Tainan 70101, TaiwanDepartment of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan(1) Background: Quantification of severity of epileptic activities, especially during electrical stimulation, is an unmet need for seizure control and evaluation of therapeutic efficacy. In this study, a parameter ratio derived from constrained square-root cubature Kalman filter (CSCKF) was formulated to quantify the excitability of local neural network and compared with three commonly used indicators, namely, band power, Teager energy operator, and sample entropy, to objectively determine their effectiveness in quantifying the severity of epileptiform discharges in mice. (2) Methods: A set of one normal and four types of epileptic EEGs was generated by a mathematical model. EEG data of epileptiform discharges during two types of electrical stimulation were recorded in 20 mice. Then, EEG segments of 5 s in length before, during and after the real and sham stimulation were collected. Both simulated and experimental data were used to compare the consistency and differences among the performance indicators. (3) Results: For the experimental data, the results of the four indicators were inconsistent during both types of electrical stimulation, although there was a trend that seizure severity changed with the indicators. For the simulated data, when the simulated EEG segments were used, the results of all four indicators were similar; however, this trend did not match the trend of excitability of the model network. In the model output which retained the DC component, except for the CSCKF parameter ratio, the results of the other three indicators were almost identical to those using the simulated EEG. For CSCKF, the parameter ratio faithfully reflected the excitability of the neural network. (4) Conclusion: For common EEG, CSCKF did not outperform other commonly used performance indicators. However, for EEG with a preserved DC component, CSCKF had the potential to quantify the excitability of the neural network and the associated severity of epileptiform discharges.https://www.mdpi.com/2227-9059/10/7/1588constrained square-root cubature Kalman filtertemporal lobe epilepsyseverity of epileptiform discharge |
| spellingShingle | Chih-Hsu Huang Peng-Hsiang Wang Ming-Shaung Ju Chou-Ching K. Lin Using Constrained Square-Root Cubature Kalman Filter for Quantifying the Severity of Epileptic Activities in Mice Biomedicines constrained square-root cubature Kalman filter temporal lobe epilepsy severity of epileptiform discharge |
| title | Using Constrained Square-Root Cubature Kalman Filter for Quantifying the Severity of Epileptic Activities in Mice |
| title_full | Using Constrained Square-Root Cubature Kalman Filter for Quantifying the Severity of Epileptic Activities in Mice |
| title_fullStr | Using Constrained Square-Root Cubature Kalman Filter for Quantifying the Severity of Epileptic Activities in Mice |
| title_full_unstemmed | Using Constrained Square-Root Cubature Kalman Filter for Quantifying the Severity of Epileptic Activities in Mice |
| title_short | Using Constrained Square-Root Cubature Kalman Filter for Quantifying the Severity of Epileptic Activities in Mice |
| title_sort | using constrained square root cubature kalman filter for quantifying the severity of epileptic activities in mice |
| topic | constrained square-root cubature Kalman filter temporal lobe epilepsy severity of epileptiform discharge |
| url | https://www.mdpi.com/2227-9059/10/7/1588 |
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