Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/471937
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dc.date.accessioned2023-03-23T12:20:32Z-
dc.date.available2023-03-23T12:20:32Z-
dc.identifier.urihttp://hdl.handle.net/10603/471937-
dc.description.abstractThe human mind involves many neurons, which accept a massive part in controlling the newlinebehavior of the human body concerning inside/outer engine/tactile boosts. Moreover, the human brain indicates different repeats in the mindfulness or resting period. By using these unique kinds of frequencies, mind waves can be perceived from each other. Besides, these electric signs can be assessed by an EEG (electroencephalograph) headset. The neuron goes about as information transporters between the human body and psyche. Understanding the scholarly lead of the psyche ought to be conceivable by taking apart signals or pictures from the brain. Human conduct can be imagined similar to the engine and tangible states, for instance, eye development, lip development, acknowledgment, thought, hand getting a handle on, etc. these states are associated with express sign repeat, which helps with understanding valuable lead of confusing brain structure. Electroencephalography (EEG) is a successful technique that helps with acquiring mind signals identified with various states newlinefrom the scalp surface district. These signs are arranged overall as delta, theta, alpha, beta, and gamma, which are reliant upon signal frequencies going from 0.1Hz to more than 100Hz. This paper focuses on EEG signs and their depiction concerning various human newlinebody states. It similarly oversees the introductory course of action used in EEG newlineexamination. Previously, the EEG headset was unassuming and just used in medicine. newlineNonetheless, over the last several years, various unassuming EEG contraptions have been newlineavailable watching out. Along these lines, the BCI (Brain-Computer Interface) investigation has been widened. Neurosky Mindwave compact II is a discreet and simple-to-utilize EEG device we use here for our assessment. This research uses Neurosky Mindwave convenient II to find our work and choose its comfort.
dc.format.extent
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleStress Ocare an Advance IOMT Based Physiological Data Analysis for Health Status Prediction Classification
dc.title.alternative
dc.creator.researcherRamani, Bhupendra
dc.subject.keywordAnxiety detection
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordElectroencephalogram
dc.subject.keywordEngineering and Technology
dc.subject.keywordHyperparameter tuning
dc.subject.keywordMachine learning
dc.subject.keywordRandom Forest
dc.description.note
dc.contributor.guideSolanki, Kamini and Patel, Warish
dc.publisher.placeVadodara
dc.publisher.universityParul University
dc.publisher.institutionDepartment of Computer Science Engineering (CSE)
dc.date.registered2018
dc.date.completed2023
dc.date.awarded2023
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science Engineering (CSE)

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01_title_page.pdfAttached File398.58 kBAdobe PDFView/Open
02_prelim_page.pdf4.79 MBAdobe PDFView/Open
03_contents.pdf573.5 kBAdobe PDFView/Open
04_abstract.pdf566.32 kBAdobe PDFView/Open
05_chapter_1.pdf1.42 MBAdobe PDFView/Open
06_chapter_2.pdf1.09 MBAdobe PDFView/Open
07_chapter_3.pdf592.69 kBAdobe PDFView/Open
08_chapter_4.pdf1.91 MBAdobe PDFView/Open
09_chapter_5.pdf1.67 MBAdobe PDFView/Open
10_chapter_6.pdf471.65 kBAdobe PDFView/Open
11_annexures.pdf6.19 MBAdobe PDFView/Open
80_recommendation.pdf106.06 kBAdobe PDFView/Open


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