{"created":"2020-03-08T23:37:19.556700+00:00","id":2433,"links":{},"metadata":{"_buckets":{"deposit":"4828c45c-de26-405e-852f-0d68a6a0fc03"},"_deposit":{"id":"2433","owners":[],"pid":{"revision_id":0,"type":"recid","value":"2433"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/2433","sets":["1582963390870:1582967549708"]},"communities":["ccm","ccp","kyauksetu","ltc","maas","miit","mlmu","mmu","mtlu","mtu","mub","mude","mufl","pathein","scu","suoe","tcu","tgu","tuh","tum","ucsm","ucsmtla","ucsmub","ucspathein","ucstaungoo","ucsy","udmm","udmy","uit","um","um1","um2","umkn","umm","uphy","urj","uvs","uy","yau","ydbu","ytu","yude","yueco","yufl","yuoe"],"control_number":"2433","item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"MICROCONTROLLER-IMPLEMENTED ARTIFICIAL NEURAL NETWORK FOR ELECTROOCULOGRAPHY-BASED WEARABLE DROWSINESS DETECTION WITH ALERTSYSTEM","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Drowsiness has been one of the leading causes of work-related accidents. One reason that is pointed out by the Royal Society for the Prevention of Accidents (2001) is that, drowsiness tends to reduce the reaction time and attentiveness of a person resulting to poor performance on attention-based activities. This is due to the fact that the speed at which information is processed in the brain is also reduced by drowsiness (NCSDR/NHTSA 1998).\r Different methods have been explored to develop an effective drowsiness detection system (DDS) to give drivers warning of impending drowsiness. However, no study implemented a wearable and standalone DDS. Most of the existing DDS require the use of a computer application or a separate processor for signal processing and drowsiness detection. The present study aimed to design a wearable electrooculography (EOG)-based DDS that doesn't require a computer to operate; to implement an artificial neural network (ANN) into a microcontroller; to determine the best electrode placement setup on the visor cap for optimal extraction of EOG signals; to test the accuracy, precision and sensitivity of the system in real-time; and to evaluate the system in terms of comfort and unobtrusiveness. Figure 1 below shows the methodology from which the development of the system was based upon."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"Artificial neural network"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2020-05-05"}],"displaytype":"preview","filename":"Microcontroller-Implemented Artificial Neural Network for electrooculography-based wearable drowsiness detection with Alert System.pdf","filesize":[{"value":"1199 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/2433/files/Microcontroller-Implemented Artificial Neural Network for electrooculography-based wearable drowsiness detection with Alert System.pdf"},"version_id":"c1f9001f-b6d5-4e2e-be16-6573806b0147"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_journal_title":"8th AUN/SEED-Net Regional Conference on Electrical and Electronics Engineering"}]},"item_1583103147082":{"attribute_name":"Conference papaers","attribute_value_mlt":[{}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_supervisor(s)":[]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Tabar, Keith Marlon R."},{"subitem_authors_fullname":"Caluyo, Felicito S."},{"subitem_authors_fullname":"Ibarra, Joseph Bryan G."}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Other"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Other"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2015"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"https://uyr.uy.edu.mm/handle/123456789/375"},"item_title":"MICROCONTROLLER-IMPLEMENTED ARTIFICIAL NEURAL NETWORK FOR ELECTROOCULOGRAPHY-BASED WEARABLE DROWSINESS DETECTION WITH ALERTSYSTEM","item_type_id":"21","owner":"1","path":["1582967549708"],"publish_date":"2020-03-05","publish_status":"0","recid":"2433","relation_version_is_last":true,"title":["MICROCONTROLLER-IMPLEMENTED ARTIFICIAL NEURAL NETWORK FOR ELECTROOCULOGRAPHY-BASED WEARABLE DROWSINESS DETECTION WITH ALERTSYSTEM"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T03:03:23.627794+00:00"}