Hand Gesture Classification Using Inertial Based Sensors via a Neural Network

dc.authorwosidUslu, Baran/AAR-1071-2020
dc.contributor.authorAkan, Erhan
dc.contributor.authorTora, Hakan
dc.contributor.authorUslu, Baran
dc.contributor.otherAirframe and Powerplant Maintenance
dc.contributor.otherDepartment of Electrical & Electronics Engineering
dc.date.accessioned2024-10-06T11:12:08Z
dc.date.available2024-10-06T11:12:08Z
dc.date.issued2017
dc.departmentAtılım Universityen_US
dc.department-temp[Akan, Erhan; Uslu, Baran] Atilim Univ, Elect & Elect Engn, Ankara, Turkey; [Tora, Hakan] Atilim Univ, Avion Elect & Elect Engn, Ankara, Turkeyen_US
dc.description.abstractIn this study, a mobile phone equipped with four types of sensors namely, accelerometer, gyroscope, magnetometer and orientation, is used for gesture classification. Without feature selection, the raw data from the sensor outputs are processed and fed into a Multi-Layer Perceptron classifier for recognition. The user independent, single user dependent and multiple user dependent cases are all examined. Accuracy values of 91.66% for single user dependent case, 87.48% for multiple user dependent case and 60% for the user independent case are obtained. In addition, performance of each sensor is assessed separately and the highest performance is achieved with the orientation sensor.en_US
dc.description.woscitationindexConference Proceedings Citation Index - Science
dc.identifier.citation7
dc.identifier.doi[WOS-DOI-BELIRLENECEK-156]
dc.identifier.endpage143en_US
dc.identifier.isbn9781538619117
dc.identifier.scopusqualityN/A
dc.identifier.startpage140en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14411/9114
dc.identifier.wosWOS:000426974200033
dc.identifier.wosqualityN/A
dc.institutionauthorAkan, Erhan
dc.institutionauthorTora, Hakan
dc.language.isoenen_US
dc.publisherIeeeen_US
dc.relation.ispartof24th IEEE International Conference on Electronics, Circuits and Systems (ICECS) -- DEC 05-08, 2017 -- Batumi, GEORGIAen_US
dc.relation.ispartofseriesIEEE International Conference on Electronics Circuits and Systems
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectgesture recognitionen_US
dc.subjectneural networken_US
dc.subjectaccelerometeren_US
dc.subjectmagnetometeren_US
dc.subjectgyroscopeen_US
dc.subjectorientation sensoren_US
dc.titleHand Gesture Classification Using Inertial Based Sensors via a Neural Networken_US
dc.typeConference Objecten_US
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscovery6206b957-7a99-4d81-be17-52b7cc69c3c4
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