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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Senkamalavalli, Rajagopalan
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Computer Science & IT Electrical & Electronics Engineering

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Journal : International Journal of Electrical and Computer Engineering

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Cloud based prediction of epileptic seizures using real-time electroencephalograms analysis Thahniyath, Gousia; Yadav, Chelluboina Subbarayudu Gangaiah; Senkamalavalli, Rajagopalan; Priya, Shanmugam Sathiya; Aghalya, Stalin; Reddy, Kuppireddy Narsimha; Murugan, Subbiah
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp6047-6056

Abstract

This study aims to improve the accuracy of epileptic seizure prediction using cloud-based, real-time electroencephalogram analysis. The goal is to build a strong framework that can quickly process electroencephalogram (EEG) data, extract relevant features, and use advanced machine learning algorithms to predict seizures with high accuracy and low latency by taking advantage of cloud platforms' computing power and scalability. The main objective is to provide patients and their caregivers with timely notifications so that they may control epilepsy episodes proactively. The goal of this project is to improve the lives of people with epilepsy by reducing the impact of seizures and improving treatment results via real-time analysis of EEG data. Cloud computing also allows the suggested seizure prediction system to be more accessible and scalable, meaning more people worldwide could benefit from it. This section discusses the results from five separate datasets of patients with epileptic seizures who underwent EEG analysis with the following details as frontopolar (FP1, FP2), frontal (F3, F4), frontotemporal (F7, F8), central (C3, C4), temporal (T3, T4), parieto-temporal (T5, T6), parietal (P3, P4), occipital (O1, O2), time (HH:MM:SS).
Video conferencing algorithms for enhanced access to mental healthcare services in cloud-powered telepsychiatry Senkamalavalli, Rajagopalan; Prasad, Subramaniyan Nesamony Sheela Evangelin; Shobana, Mahalingam; Sri, Chellaiyan Bharathi; Sandiri, Rajendar; Karthik, Jayavarapu; Murugan, Subbiah
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp1142-1151

Abstract

Exploring the video conferencing algorithms for cloud-powered telepsychiatry to improve mental healthcare access. The goal is to evaluate and optimise these algorithms' latency, bandwidth utilisation, packet loss, and jitter across worldwide locations. To provide a smooth and high-quality virtual consultation between patients and mental health providers. Using performance data to identify areas for development, the effort aims to lower technological hurdles and increase telepsychiatry session dependability. Findings will help create strong, efficient algorithms that can handle different network situations, increasing patient outcomes and extending mental healthcare services. In the 1st instance latent analysis in a sample of 5 cities, the average latency (ms) is 45, the peak latency is 120, the off-peak latency is 30, and the packet loss is 0.5. In another instance, bandwidth utilisation in a sample of 5 sessions ranged from 30 to 120 minutes, with data supplied in MB - 150-600 and received in MB - 160-620, with average bandwidth (Mbps) - 5-15 and maximum bandwidth: 10-20.
Co-Authors Aghalya, Stalin Karthik, Jayavarapu Murugan, Subbiah Parivazhagan, Alaguchamy Prasad, Subramaniyan Nesamony Sheela Evangelin Priya, Shanmugam Sathiya Raja, Raju Reddy, Kuppireddy Narsimha Sandiri, Rajendar Sankar, Singaravel Selvaraj, Yoganand Shobana, Mahalingam Sri, Chellaiyan Bharathi Srinivas, Porandla Thahniyath, Gousia Varadarajan, Mageshkumar Naarayanasamy Yadav, Chelluboina Subbarayudu Gangaiah