Browsing by Author "Ramesh, A."

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Automatic seizure detection by modified line length and Mahalanobis distance function
(2018) Pathak, A.; Ramesh, A.; Mitra, A.; Majumdar, K.
Automatic seizure detection with high accuracy and in linear time has profound implications on therapeutic intervention mechanisms. In this work taking into account 12 popular seizure detection algorithms we have shown that line length is one feature that is extractable in linear time from EEG signals and capable of automatic seizure onset detection with highest accuracy among linear time extractable features. Also line length is less prone to give false positives. The detection accuracy has been ascertained by ROC curve analysis on Freiburg Seizure Prediction Project data containing intracranial EEG recordings of 87 seizures from 21 patients with sufficient interictal signals. Next, we have modified the classical line length feature extraction algorithm to improve its accuracy without any additional computational burden. Finally, we have applied both classical line length (LL) and modified line length (MLL) on all focal channels and detected seizures on multidimensional focal channel signals by Mahalanobis distance function (MDF). Both detected 73 out of 87 seizures. Area under the ROC curve (AUC), detection delay and false positive for LL and MLL are 0.951, 11.903 s, 0.201/h and 0.954, 11.698 s, 0.198/h respectively. Since LL has already been incorporated into an FDA approved commercially available closed loop intervention system, even this minute improvement may have significant healthcare implications. 2018 Elsevier Ltd
Automatic seizure detection by modified line length and Mahalanobis distance function
(Elsevier Ltd, 2018) Pathak, A.; Ramesh, A.; Mitra, A.; Majumdar, K.
Automatic seizure detection with high accuracy and in linear time has profound implications on therapeutic intervention mechanisms. In this work taking into account 12 popular seizure detection algorithms we have shown that line length is one feature that is extractable in linear time from EEG signals and capable of automatic seizure onset detection with highest accuracy among linear time extractable features. Also line length is less prone to give false positives. The detection accuracy has been ascertained by ROC curve analysis on Freiburg Seizure Prediction Project data containing intracranial EEG recordings of 87 seizures from 21 patients with sufficient interictal signals. Next, we have modified the classical line length feature extraction algorithm to improve its accuracy without any additional computational burden. Finally, we have applied both classical line length (LL) and modified line length (MLL) on all focal channels and detected seizures on multidimensional focal channel signals by Mahalanobis distance function (MDF). Both detected 73 out of 87 seizures. Area under the ROC curve (AUC), detection delay and false positive for LL and MLL are 0.951, 11.903 s, 0.201/h and 0.954, 11.698 s, 0.198/h respectively. Since LL has already been incorporated into an FDA approved commercially available closed loop intervention system, even this minute improvement may have significant healthcare implications. © 2018 Elsevier Ltd
Exploring Plant-Derived Bioactive Compounds in Olea Europaea L. Leaves as Potent Inhibitors of PTP-1B Using an In silico Approach
(World Scientific, 2024) Deshpande, N.S.; Wagh, S.; Sharma, A.P.; Ramesh, A.; Mahindra; Lavanya; Moksha, B.S.; Divyashree; Disha; Dixit, S.R.; Singh, D.; Bidye, D.P.; Revanasiddappa, B.C.
In this study, we focus on exploring the medicinal potential of Olea Europaea L., a commonly used plant with diverse indigenous medicinal applications. The main aim is to identify promising phytoconstituents from Olea Europaea L. leaves that can act as inhibitors for the PTP-1B target, utilizing an in silico approach. The phytoconstituents were sourced from the IMMPAT database, and molecular docking was employed to assess their binding affinities. The docking results revealed that rutin (-10.05 kcal/mol) and quercetin (-8.28 kcal/mol) displayed the highest binding scores against PTP-1B, outperforming reference compounds. Furthermore, MM-GBSA calculations indicated favorable free binding energy. To ensure stability, 200 ns Molecular Dynamics simulations were conducted on the 2QBS-Rutin complex. The results revealed that the 2QBS-Rutin complex showed stable conformation throughout the simulation, maintaining consistency with RMSD values below 1 Å. This study highlights rutin and quercetin as promising phytoconstituents from Olea Europaea L. leaves, demonstrating potent-binding affinities against PTP-1B inhibitors. © 2024 World Scientific Publishing Company.