{"id":"https://openalex.org/W2907815763","doi":"https://doi.org/10.1109/icarcv.2018.8581177","title":"Driving-PASS: An Automatic Driving Performance Assessment System for Stroke Drivers Based on ANN and SVM","display_name":"Driving-PASS: An Automatic Driving Performance Assessment System for Stroke Drivers Based on ANN and SVM","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2907815763","doi":"https://doi.org/10.1109/icarcv.2018.8581177","mag":"2907815763"},"language":"en","primary_location":{"id":"doi:10.1109/icarcv.2018.8581177","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv.2018.8581177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101832347","display_name":"Sanghoon Jeon","orcid":"https://orcid.org/0000-0001-5636-7555"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sanghoon Jeon","raw_affiliation_strings":["Department of Information and Communication Engineering, DGIST, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, DGIST, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070305779","display_name":"Joonwoo Son","orcid":"https://orcid.org/0000-0003-1040-065X"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Joonwoo Son","raw_affiliation_strings":["HumanLab, DGIST, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HumanLab, DGIST, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072489062","display_name":"Myoungouk Park","orcid":null},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Myoungouk Park","raw_affiliation_strings":["HumanLab, DGIST, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HumanLab, DGIST, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015168181","display_name":"Bawul Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Bawul Kim","raw_affiliation_strings":["HumanLab, DGIST, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HumanLab, DGIST, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012886088","display_name":"Sang H. Son","orcid":"https://orcid.org/0000-0003-0070-5951"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sang Hyuk Son","raw_affiliation_strings":["Department of Information and Communication Engineering, DGIST, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, DGIST, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027782566","display_name":"Yongsoon Eun","orcid":"https://orcid.org/0000-0002-2304-7106"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yongsoon Eun","raw_affiliation_strings":["Department of Information and Communication Engineering, DGIST, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, DGIST, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4332,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74104345,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"64","issue":null,"first_page":"1367","last_page":"1373"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12315","display_name":"Older Adults Driving Studies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/3612","display_name":"Physical Therapy, Sports Therapy and Rehabilitation"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T12315","display_name":"Older Adults Driving Studies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/3612","display_name":"Physical Therapy, Sports Therapy and Rehabilitation"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10227","display_name":"Acute Ischemic Stroke Management","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6646838188171387},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5896111130714417},{"id":"https://openalex.org/keywords/risk-assessment","display_name":"Risk assessment","score":0.5643587708473206},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.528913140296936},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5162341594696045},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4835071861743927},{"id":"https://openalex.org/keywords/decision-support-system","display_name":"Decision support system","score":0.45924049615859985},{"id":"https://openalex.org/keywords/driving-simulator","display_name":"Driving simulator","score":0.4363865256309509},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.13265201449394226}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6646838188171387},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5896111130714417},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.5643587708473206},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.528913140296936},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5162341594696045},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4835071861743927},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.45924049615859985},{"id":"https://openalex.org/C2780689630","wikidata":"https://www.wikidata.org/wiki/Q2081815","display_name":"Driving simulator","level":2,"score":0.4363865256309509},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.13265201449394226}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icarcv.2018.8581177","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv.2018.8581177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W190437827","https://openalex.org/W576432894","https://openalex.org/W1556772844","https://openalex.org/W1623006543","https://openalex.org/W1847168837","https://openalex.org/W1988889496","https://openalex.org/W2003061524","https://openalex.org/W2038347332","https://openalex.org/W2044033713","https://openalex.org/W2078089692","https://openalex.org/W2078962597","https://openalex.org/W2090206425","https://openalex.org/W2097524879","https://openalex.org/W2117207990","https://openalex.org/W2140160267","https://openalex.org/W2141403362","https://openalex.org/W2154186770","https://openalex.org/W2154280008","https://openalex.org/W2169689115","https://openalex.org/W2220251786","https://openalex.org/W2397483391","https://openalex.org/W2403169154","https://openalex.org/W2464356638","https://openalex.org/W4235309947","https://openalex.org/W6607693206","https://openalex.org/W6633136847","https://openalex.org/W6636749155"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2012353789","https://openalex.org/W2530420969","https://openalex.org/W2051187167","https://openalex.org/W1980100242"],"abstract_inverted_index":{"Although":[0,33],"many":[1],"stroke":[2,56,67,232],"survivors":[3],"are":[4,105],"not":[5,85,178],"fully":[6],"capable":[7],"of":[8,21,31,65,134,149,187,191,199,203,226],"driving,":[9,48],"they":[10],"drive":[11],"again":[12],"without":[13],"any":[14],"formal":[15],"assessment":[16,41,91,131,136,152,165,182,210],"due":[17],"to":[18,27,46,53,83,99,222],"an":[19,28,34,71,146],"absence":[20],"valid":[22],"screening":[23],"tools.":[24],"This":[25],"leads":[26],"elevated":[29],"risk":[30,225],"accidents.":[32],"on-road":[35,60],"test":[36],"is":[37,114],"considered":[38],"a":[39,95,117,129,155],"standard":[40],"method":[42,132,148,153],"for":[43,77],"items":[44,92,104,137,183],"relevant":[45],"actual":[47],"it":[49],"may":[50],"be":[51,214],"dangerous":[52],"evaluate":[54],"all":[55],"drivers":[57,79,233],"with":[58,154,234],"the":[59,111,124,150,180,195,224],"test.":[61],"For":[62,122],"safe":[63],"pre-screening":[64,230],"unsuitable":[66,231],"drivers,":[68],"we":[69,126,144],"propose":[70,128,145],"automatic":[72],"Driving":[73],"Performance":[74],"Assessment":[75],"System":[76],"Stroke":[78],"(Driving-PASS).":[80],"Driving-PASS":[81,175,207],"aims":[82],"provide":[84],"only":[86,179],"information":[87],"about":[88,97],"problematic":[89,102],"driving":[90,103,217],"but":[93,193],"also":[94,194],"decision":[96,112,118,140,196],"fitness":[98],"drive.":[100],"The":[101],"classified":[106],"by":[107,116,163,229],"abnormal":[108],"classifiers":[109],"while":[110],"item":[113,197],"determined":[115],"classifier":[119],"in":[120,216],"Driving-PASS.":[121],"designing":[123],"system,":[125],"firstly":[127],"subjective":[130,151],"consisting":[133],"ten":[135,181],"and":[138,161,189,201,220,237],"one":[139],"item.":[141],"And":[142],"then,":[143],"automated":[147],"machine":[156],"learning":[157],"approach":[158],"(i.e.,":[159],"ANN":[160],"SVM)":[162],"using":[164],"criteria":[166],"from":[167],"five":[168],"expert's":[169],"judgments.":[170],"Evaluation":[171],"results":[172,211],"demonstrate":[173],"that":[174,212],"automatically":[176],"assess":[177],"(total":[184],"average":[185],"Accuracy":[186],"90%":[188],"F1-score":[190,202],"88%)":[192],"(Accuracy":[198],"93%":[200],"92%).":[204],"We":[205],"expect":[206],"provides":[208],"analytical":[209],"can":[213],"used":[215],"rehabilitation":[218],"programs":[219],"contributes":[221],"reducing":[223],"vehicle":[227],"accidents":[228],"high":[235],"accuracy":[236],"reliability.":[238]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}