{"id":"https://openalex.org/W4406276240","doi":"https://doi.org/10.1109/bibm62325.2024.10822335","title":"Mental Stress Detection Using PPG Signals Based on Transformer-LSTM Model","display_name":"Mental Stress Detection Using PPG Signals Based on Transformer-LSTM Model","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406276240","doi":"https://doi.org/10.1109/bibm62325.2024.10822335"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10822335","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822335","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5107498911","display_name":"Zhiqiang Liu","orcid":"https://orcid.org/0000-0001-7863-1759"},"institutions":[{"id":"https://openalex.org/I152238500","display_name":"Chosun University","ror":"https://ror.org/01zt9a375","country_code":"KR","type":"education","lineage":["https://openalex.org/I152238500"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Zhiqiang Liu","raw_affiliation_strings":["Chosun University,AI Healthcare Research Center,Gwangju,Korea,61452"],"affiliations":[{"raw_affiliation_string":"Chosun University,AI Healthcare Research Center,Gwangju,Korea,61452","institution_ids":["https://openalex.org/I152238500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008998270","display_name":"Ziyu Shi","orcid":"https://orcid.org/0000-0001-5411-575X"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyu Shi","raw_affiliation_strings":["Jilin University,College of Instrumentation and Electrical Engineering,Changchun,China,130061"],"affiliations":[{"raw_affiliation_string":"Jilin University,College of Instrumentation and Electrical Engineering,Changchun,China,130061","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081936566","display_name":"Gengjia Zhang","orcid":"https://orcid.org/0000-0001-8479-2903"},"institutions":[{"id":"https://openalex.org/I152238500","display_name":"Chosun University","ror":"https://ror.org/01zt9a375","country_code":"KR","type":"education","lineage":["https://openalex.org/I152238500"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gengjia Zhang","raw_affiliation_strings":["Chosun University,AI Healthcare Research Center,Gwangju,Korea,61452"],"affiliations":[{"raw_affiliation_string":"Chosun University,AI Healthcare Research Center,Gwangju,Korea,61452","institution_ids":["https://openalex.org/I152238500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103037153","display_name":"Jaehyo Jung","orcid":"https://orcid.org/0000-0003-1852-3267"},"institutions":[{"id":"https://openalex.org/I152238500","display_name":"Chosun University","ror":"https://ror.org/01zt9a375","country_code":"KR","type":"education","lineage":["https://openalex.org/I152238500"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaehyo Jung","raw_affiliation_strings":["Chosun University,AI Healthcare Research Center,Gwangju,Korea,61452"],"affiliations":[{"raw_affiliation_string":"Chosun University,AI Healthcare Research Center,Gwangju,Korea,61452","institution_ids":["https://openalex.org/I152238500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101517307","display_name":"Meina Li","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meina Li","raw_affiliation_strings":["Jilin University,College of Instrumentation and Electrical Engineering,Changchun,China,130061"],"affiliations":[{"raw_affiliation_string":"Jilin University,College of Instrumentation and Electrical Engineering,Changchun,China,130061","institution_ids":["https://openalex.org/I194450716"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5107498911"],"corresponding_institution_ids":["https://openalex.org/I152238500"],"apc_list":null,"apc_paid":null,"fwci":1.9473,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.87601684,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"7095","last_page":"7097"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.7455000281333923,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.7455000281333923,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.6700999736785889,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.6574000120162964,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/transformer","display_name":"Transformer","score":0.5817018151283264},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.577013373374939},{"id":"https://openalex.org/keywords/stress","display_name":"Stress (linguistics)","score":0.44682776927948},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3847231864929199},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3803131580352783},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13324612379074097},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.12120577692985535},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.08728858828544617}],"concepts":[{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5817018151283264},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.577013373374939},{"id":"https://openalex.org/C21036866","wikidata":"https://www.wikidata.org/wiki/Q181767","display_name":"Stress (linguistics)","level":2,"score":0.44682776927948},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3847231864929199},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3803131580352783},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13324612379074097},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.12120577692985535},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.08728858828544617},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm62325.2024.10822335","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822335","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320338440","display_name":"HORIZON EUROPE Health","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1964903747","https://openalex.org/W2064675550","https://openalex.org/W2124052799","https://openalex.org/W2894771803","https://openalex.org/W3005387090","https://openalex.org/W3109060695","https://openalex.org/W3167394498","https://openalex.org/W4361026734","https://openalex.org/W4361290388","https://openalex.org/W4376627321","https://openalex.org/W4390993490","https://openalex.org/W6739901393","https://openalex.org/W6760706080","https://openalex.org/W6776048684","https://openalex.org/W6797185979"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2129927767"],"abstract_inverted_index":{"Long-term":[0],"stress":[1,29,39,140,148,195],"not":[2,179],"only":[3],"affects":[4],"physical":[5],"health":[6],"but":[7],"also":[8],"leads":[9],"to":[10,25,36,53,97,117,131],"the":[11,45,50,80,92,101,110,115,124,133,169,172,186,192],"deterioration":[12],"of":[13,79,171,194],"mental":[14],"state.":[15],"To":[16],"prevent":[17],"such":[18],"adverse":[19],"effects,":[20],"it":[21,32],"is":[22,33,66,95,107,129],"very":[23],"important":[24,120],"detect":[26,139],"and":[27,73,99,138,146,156,190,202],"manage":[28],"promptly.":[30],"Therefore,":[31],"particularly":[34],"necessary":[35],"develop":[37,54],"effective":[38],"detection":[40],"methods.":[41],"This":[42],"study":[43],"utilizes":[44],"photoplethysmogram":[46],"(PPG)":[47],"signal":[48,65,82],"in":[49,200],"WESAD":[51],"database":[52],"a":[55,86],"deep":[56],"learning":[57],"model":[58,94,116],"for":[59],"detecting":[60],"psychological":[61],"stress.":[62],"The":[63,76,105,175],"PPG":[64,81],"preprocessed":[67],"by":[68],"data":[69,187],"filtering,":[70],"down":[71],"sampling,":[72],"sliding":[74],"windows.":[75],"local":[77,121],"features":[78,137],"are":[83,159],"extracted":[84],"using":[85],"convolutional":[87],"neural":[88],"network":[89],"(CNN).":[90],"Then,":[91],"Transformer":[93,106],"used":[96],"analyze":[98],"capture":[100],"correlation":[102],"between":[103,136],"features.":[104,122],"based":[108],"on":[109,119,143],"attention":[111],"mechanism,":[112],"which":[113],"enables":[114],"focus":[118],"Lastly,":[123],"long":[125],"short-term":[126],"memory":[127],"(LSTM)":[128],"utilized":[130],"process":[132],"temporal":[134],"relationship":[135],"status.":[141],"Evaluations":[142],"binary,":[144],"ternary,":[145],"quaternary":[147],"classification":[149],"tasks":[150],"show":[151],"significant":[152],"performance:":[153],"96.07%,":[154],"92.27%,":[155],"87.04%":[157],"accuracy":[158,193],"achieved,":[160],"respectively.":[161],"Comparison":[162],"with":[163],"other":[164],"recent":[165],"research":[166],"findings":[167],"demonstrates":[168],"superiority":[170],"proposed":[173,176],"method.":[174],"method":[177],"does":[178],"require":[180],"manual":[181],"feature":[182],"extraction":[183],"engineering,":[184],"simplifies":[185],"processing":[188],"process,":[189],"improves":[191],"detection,":[196],"indicating":[197],"its":[198],"potential":[199],"real-life":[201],"practical":[203],"applications.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}
