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RISS 인기검색어
- 검색키워드
- 저자 : Gonuguntla, V. (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
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Event-Related Functional Network Identification: Application to EEG Classification
Gonuguntla, Venkateswarlu,Yubo Wang,Veluvolu, Kalyana C. IEEE 2016 IEEE journal of selected topics in signal processi Vol.10 No.7
<P>Recent works on brain functional analysis have accentuated the importance of distributed functional networks and synchronized activity between networks in mediating cognitive functions. The network perspective is important to relate mechanisms of brain functions and the basis for classifying brain states. In this work, the network patterns related to neural tasks based on synchronization measure phase-locking value (PLV) in an electroencephalogram (EEG) are analyzed. Based on network dissimilarities between the rest and motor imagery tasks, important nodes and channel pairs corresponding to motor tasks are identified. A framework is developed to identify these most reactive channel pairs that form the subject-specific functional network. The identified functional network corresponding to tasks demonstrate significant PLV variation in line with the experiment protocol. With the selection of subject-specific reactive band, these channel pairs provide even higher variation corresponding to tasks. To demonstrate the potential of the developed framework to brain-computer interface, identified network patterns are employed as features for classification of tasks. Analysis performed with the two classes (left-hand and right-hand motor imagery EEG data) showed that the proposed approach yielded better classification results compared to earlier band-power based approaches for single trial analysis.</P>
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Differential Evolution with Population and Strategy Parameter Adaptation
Gonuguntla, V.,Mallipeddi, R.,Veluvolu, Kalyana C. Hindawi Limited 2015 Mathematical problems in engineering Vol.2015 No.-
<P>Differential evolution (DE) is simple and effective in solving numerous real-world global optimization problems. However, its effectiveness critically depends on the appropriate setting of population size and strategy parameters. Therefore, to obtain optimal performance the time-consuming preliminary tuning of parameters is needed. Recently, different strategy parameter adaptation techniques, which can automatically update the parameters to appropriate values to suit the characteristics of optimization problems, have been proposed. However, most of the works do not control the adaptation of the population size. In addition, they try to adapt each strategy parameters individually but do not take into account the interaction between the parameters that are being adapted. In this paper, we introduce a DE algorithm where both strategy parameters are self-adapted taking into account the parameter dependencies by means of a multivariate probabilistic technique based on Gaussian Adaptation working on the parameter space. In addition, the proposed DE algorithm starts by sampling a huge number of sample solutions in the search space and in each generation a constant number of individuals from huge sample set are adaptively selected to form the population that evolves. The proposed algorithm is evaluated on 14 benchmark problems of CEC 2005 with different dimensionality.</P>
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Asymptomatic Giant Aneurysm of the Arteria Lusoria Treated by Debranching and Aneurysmal Resection
Aadithiyavikram Venkatesan,Akhilesh Gonuguntla,Anila Vasireddy,Guruprasad D Rai,Ganesh Sevagur Kamath,Arvind Kumar Bishnoi,Revanth Maramreddy 대한혈관외과학회 2022 Vascular Specialist International Vol.38 No.1
The aberrant right subclavian artery (ARSA, arteria lusoria) is the most common intrathoracic vascular anomaly, affecting up to 2% of the population. However, aneurysms of congenital anomalies are extremely unusual and often present with dysphagia, dysphonia, or dyspnea due to compression of the surrounding structures. We report a case of an asymptomatic 57-year-old male with chronic kidney disease who was incidentally found to have a large aneurysm of the ARSA on preoperative computed tomography for laparoscopic nephrectomy. Surgery is unequivocally warranted as these aneurysms are associated with a high risk of complications, including thrombosis, embolism, and rupture. We debranched the ARSA, followed by anastomosis to the right carotid artery through a right neck incision. Subsequently, aneurysmal resection was performed through left thoracotomy. The patient had an uneventful postoperative recovery and was asymptomatic during the follow-up.
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Harshith Thyagaturu,Nicholas Roma,Aakash Angirekula,Sittinun Thangjui,Alex Bolton,Karthik Gonuguntla,Yasar Sattar,Muchi Ditah Chobufo,Abhiram Challa,Neel Patel,Gayatri Bondi,Sameer Raina 대한심장학회 2023 Korean Circulation Journal Vol.53 No.12
Background and Objectives: There is limited data on the impact of type 2 myocardial infarction (T2MI) during the coronavirus disease 2019 (COVID-19) pandemic. Methods: The National Inpatient Sample (NIS) database from January 2019 to December 2020 was queried to identify T2MI hospitalizations based on the appropriate International Classification of Disease, Tenth Revision-Clinical Modification codes. Monthly trends of COVID-19 and T2MI hospitalizations were evaluated using Joinpoint regression analysis. In addition, the multivariate logistic and linear regression analysis was used to compare in-hospital mortality, coronary angiography use, and resource utilization between 2019 and 2020. Results: A total of 743,535 patients hospitalized with a diagnosis of T2MI were identified in the years 2019 (n=331,180) and 2020 (n=412,355). There was an increasing trend in T2MI hospitalizations throughout the study period corresponding to the increase in COVID-19 hospitalizations in 2020. The adjusted odds of in-hospital mortality associated with T2MI hospitalizations were significantly higher in 2020 compared with 2019 (11.1% vs. 8.1%: adjusted odds ratio, 1.19 [1.13–1.26]; p<0.01). In addition, T2MI hospitalizations were associated with lower odds of coronary angiography and higher total hospitalization charges, with no difference in the length of stay in 2020 compared with 2019. Conclusions: We found a significant increase in T2MI hospitalizations with higher in-hospital mortality, total hospitalization costs, and lower coronary angiography use during the early COVID-19 pandemic corresponding to the trends in the rise of COVID-19 hospitalizations. Further research into the factors associated with increased mortality can increase our preparedness for future pandemics.
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