{"_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": ["user-uy"]}, "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\u0027t 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", "download_preview_message": "", "file_order": 0, "filename": "Microcontroller-Implemented Artificial Neural Network for electrooculography-based wearable drowsiness detection with Alert System.pdf", "filesize": [{"value": "1199 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 1199000.0, "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"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000002433", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-03-05"}, "publish_date": "2020-03-05", "publish_status": "0", "recid": "2433", "relation": {}, "relation_version_is_last": true, "title": ["MICROCONTROLLER-IMPLEMENTED ARTIFICIAL NEURAL NETWORK FOR ELECTROOCULOGRAPHY-BASED WEARABLE DROWSINESS DETECTION WITH ALERTSYSTEM"], "weko_shared_id": -1}