[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-detail-290402-en":59,"doc-seo-290402-105":81},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":5,"data":60},{"doc_id":61,"user_id":62,"nickname":63,"user_avatar":64,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":66,"doc_content":67,"file_id":68,"file_url":69,"file_type":70,"file_size":71,"view_count":29,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":72,"language":73,"language_code":74,"site_id":75,"html_lang":74,"table_of_contents":76,"faqs":77,"seo_title":78,"seo_description":66,"update_tm":79,"read_time":80,"preview_page_count":4},290402,4398048949847,"Eliana","https://ap-avatar.wpscdn.com/avatar/400002536579ef2da7f?_k=1778318612642679267","Real-time classification of EEG signals using Machine Learning deployment - Abstract","The paper proposes a real-time, machine-learning framework to assess student attentiveness and comprehension during lectures. Traditional classroom and online methods often make it difficult for educators to engage every student simultaneously. By monitoring electroencephalography (EEG) signals and using ML algorithms, the study predicts concentration and engagement levels from measurable parameters. A browser interface visualizes parameter values for selected topics, while deployment considerations include real-time performance, system cost, and trust in efficacy. The work outlines design choices and directions for future research.","Real-time classification ofEEG signals using Machine  \nLearning deployment  \nSwati CHOWDHURI1*, Satadip SAHA1, Samadrita KARMAKAR1, Ankur CHANDA2  \n1* Department of Electrical and Electronics Engineering, Institute of Engineering & Management, University  \nof Engineering & Management (UEM), Kolkata, India  \n2 Department of Computer Science and Engineering (Artificial Intelligence and Machine Learning), Institute of Engineering & Management, University of Engineering & Management (UEM), Kolkata, India  \n[swati.chowdhuri@iemcal.com](swati.chowdhuri@iemcal.com)*, [satadipsaha3@gmail.com](satadipsaha3@gmail.com), [bonnythemaa@gmail.com](bonnythemaa@gmail.com),  \n[ankurchanda198@gmail.com](ankurchanda198@gmail.com)  \n*Corresponding Author: Swati CHOWDHURI  \n[swati.chowdhuri@iemcal.com](swati.chowdhuri@iemcal.com)*  \nAbstract: The prevailing educational methods predominantly rely on traditional classroom instruction or online delivery, often limiting the teachers’ ability to engage effectively with all the students simultaneously. A more intrinsic method of evaluating student attentiveness during lectures can enable the educators to tailor the course materials and their teaching styles in order to better meet the students' needs. The aim of this paper is to enhance teaching quality in real time, thereby fostering a higher student engagement in the classroom activities. By monitoring the students' electroencephalography (EEG) signals and employing machine learning algorithms, this study proposes a comprehensive solution for addressing this challenge. Machine learning has emerged as a powerful tool for simplifying the analysis of complex variables, enabling the effective assessment of the students' concentration levels based on specific parameters. However, the realtime impact of machine learning models necessitates a careful consideration as their deployment is concerned. This study proposes a machine learning-based approach for predicting the level of students' comprehension with regard to a certain topic. A browser interface was introduced that accesses the values of the system's parameters to determine a student's level of concentration on a chosen topic. The deployment of the proposed system made it necessary to address the real-time challenges faced by the students, consider the system's cost, and establish trust in its efficacy. This paper presents the efforts made for approaching this pertinent issue through the implementation of innovative technologies and provides a framework for addressing key considerations for future research directions.  \nKeywords: Electroencephalogram, Machine Learning, Real-Time Impact, Brain-Computer Interface (BCI), Signal Classification.  \n1. Introduction  \nThe electroencephalogram (EEG) is a recording of the brain's electrical activity, captured through electrodes placed on the scalp. These electrodes detect and measure neural impulses between synapses as neurons communicate. EEG signals offer valuable insights into brain function, used in neuroscience, medicine and research for diagnosing and monitoring conditions like epilepsy, sleep disorders and brain injuries. Signal patterns and frequencies indicate brain activity states such as wakefulness, sleep stages, seizures, cognitive processes and abnormalities.  \nMachine learning can accurately measure EEG parameters like alpha, beta, theta and gamma waves values. Penolazzi et al. found that delta signals increase during linguistic acquisition, while high theta values indicate active concentration. Maximum alpha values suggest a state of rest or relaxation. These signals are computationally obtained using suitable algorithms, including machine learning models trained to recognize patterns and make predictions from given data.  \nTraining a machine learning model involves dataset collection, handling missing values, scaling features, and dividing data into training and testing sets. An appropriate model is selected based on the problem type, and featur","cbCaiulv3KgQ2mdd","https://ap.wps.com/l/cbCaiulv3KgQ2mdd","pdf",628264,13,"English","en",105,"# Introduction\n# Literature review","[{\"question\":\"How does the study evaluate student attentiveness during class?\",\"answer\":\"It records EEG signals while students watch educational videos and uses machine-learning models to estimate concentration and comprehension levels from signal parameters.\"},{\"question\":\"What role does the browser interface play in the proposed system?\",\"answer\":\"The interface accesses the system parameters to determine a student’s level of concentration for a chosen topic, supporting real-time monitoring.\"},{\"question\":\"Why is real-time deployment emphasized in the paper?\",\"answer\":\"Because machine-learning models must operate effectively in real time, the study addresses performance challenges, considers system cost, and aims to establish trust in the approach.\"}]","Real-time classification of EEG signals using Machine Learning deployment - Abstract | PDF",1789641617,33,{"code":4,"msg":82,"data":83},"ok",{"site_id":75,"language":74,"slug":84,"title":65,"keywords":85,"description":66,"schema_data":86,"social_meta":140,"head_meta":142,"extra_data":144,"updated_unix":145},"real-time-classification-of-eeg-signals-using-machine-learning-deployment-abstract","",{"@graph":87,"@context":139},[88,102,122],{"@type":89,"itemListElement":90},"BreadcrumbList",[91,95,97,100],{"item":92,"name":93,"@type":94,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":96,"name":9,"@type":94,"position":14},"https://docshare.wps.com/document/",{"item":98,"name":40,"@type":94,"position":99},"https://docshare.wps.com/document/research-report/",3,{"item":101,"name":65,"@type":94,"position":19},"https://docshare.wps.com/document/real-time-classification-of-eeg-signals-using-machine-learning-deployment-abstract/290402/",{"url":101,"name":65,"@type":103,"image":104,"author":109,"headline":65,"publisher":111,"fileFormat":114,"inLanguage":74,"description":66,"dateModified":115,"datePublished":116,"encodingFormat":114,"isAccessibleForFree":117,"interactionStatistic":118},"DigitalDocument",{"url":105,"@type":106,"width":107,"height":108},"https://docshare.wps.com/thumbnails/real-time-classification-of-eeg-signals-using-machine-learning-deployment-abstract/290402.png","ImageObject",300,407,{"name":63,"@type":110},"Person",{"url":92,"name":112,"@type":113},"DocShare","Organization","application/pdf","2026-10-30","2026-09-17",true,{"@type":119,"interactionType":120,"userInteractionCount":29},"InteractionCounter",{"@type":121},"ViewAction",{"@type":123,"mainEntity":124},"FAQPage",[125,131,135],{"name":126,"@type":127,"acceptedAnswer":128},"How does the study evaluate student attentiveness during class?","Question",{"text":129,"@type":130},"It records EEG signals while students watch educational videos and uses machine-learning models to estimate concentration and comprehension levels from signal parameters.","Answer",{"name":132,"@type":127,"acceptedAnswer":133},"What role does the browser interface play in the proposed system?",{"text":134,"@type":130},"The interface accesses the system parameters to determine a student’s level of concentration for a chosen topic, supporting real-time monitoring.",{"name":136,"@type":127,"acceptedAnswer":137},"Why is real-time deployment emphasized in the paper?",{"text":138,"@type":130},"Because machine-learning models must operate effectively in real time, the study addresses performance challenges, considers system cost, and aims to establish trust in the approach.","https://schema.org",{"og:url":101,"og:type":141,"og:title":65,"og:site_name":112,"og:description":66},"article",{"robots":143,"canonical":101},"index,follow",{"doc_id":61,"site_id":75},1790052662]