dc.contributor.authorLing Adam Muhd Hasyim Ling
dc.date.accessioned2017-04-18T01:10:45Z
dc.date.available2017-04-18T01:10:45Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/10356/70248
dc.description.abstractBiosignals are any signal from any living being that can be recorded and analyzed. There are many different forms of biosignals, namely electrical or mechanical. Examples of such signals include skin conductivity and muscle contraction signals. These signals have also been used in many different applications, such as in the medical setting where biosignals from the handicapped have been recorded and analyzed in order to provide suitable healthcare to them. Biosignals have also been recorded with the intention of foreseeing the emotions elicited by a subject. Methods such as statistical classification have been implemented in previous studies in which the prediction of emotions have been successfully achieved by a machine. This project aims to manipulate recorded biosignals from a previously obtained dataset, analyze and process these signals via feature extraction. After which, the extracted features will be supplied to a k-Nearest Neighbor classifier as a training set to establish a model which is able to predict the emotion that is associated with the different biosignals elicited by the subject in the data set.en_US
dc.format.extent34 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Computer science and engineering::Computer applicationsen_US
dc.titleBiosignal processing - 2en_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorDeepu Rajanen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Engineering)en_US


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