{"id":"https://openalex.org/W4390905803","doi":"https://doi.org/10.1109/aciiw59127.2023.10388137","title":"How well can PPG be an alternative to ECG for acute stress detection in nonresting state?\u2014Comprehensive evaluation using a DNN","display_name":"How well can PPG be an alternative to ECG for acute stress detection in nonresting state?\u2014Comprehensive evaluation using a DNN","publication_year":2023,"publication_date":"2023-09-10","ids":{"openalex":"https://openalex.org/W4390905803","doi":"https://doi.org/10.1109/aciiw59127.2023.10388137"},"language":"en","primary_location":{"id":"doi:10.1109/aciiw59127.2023.10388137","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aciiw59127.2023.10388137","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)","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/A5067140820","display_name":"Yasuhide Hyodo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210122684","display_name":"Sony Computer Science Laboratories","ror":"https://ror.org/02nc46417","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210122684"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasuhide Hyodo","raw_affiliation_strings":["Technology Development Laboratories, Sony Corporation,Human Technology R&D Department,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technology Development Laboratories, Sony Corporation,Human Technology R&D Department,Tokyo,Japan","institution_ids":["https://openalex.org/I4210122684"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105525601","display_name":"Kiyoshi Yoshikawa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210122684","display_name":"Sony Computer Science Laboratories","ror":"https://ror.org/02nc46417","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210122684"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kiyoshi Yoshikawa","raw_affiliation_strings":["Technology Development Laboratories, Sony Corporation,Human Technology R&D Department,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technology Development Laboratories, Sony Corporation,Human Technology R&D Department,Tokyo,Japan","institution_ids":["https://openalex.org/I4210122684"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045964273","display_name":"Takanori Ishikawa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210122684","display_name":"Sony Computer Science Laboratories","ror":"https://ror.org/02nc46417","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210122684"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takanori Ishikawa","raw_affiliation_strings":["Technology Development Laboratories, Sony Corporation,Human Technology R&D Department,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technology Development Laboratories, Sony Corporation,Human Technology R&D Department,Tokyo,Japan","institution_ids":["https://openalex.org/I4210122684"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081556756","display_name":"Yota Komoriya","orcid":null},"institutions":[{"id":"https://openalex.org/I4210122684","display_name":"Sony Computer Science Laboratories","ror":"https://ror.org/02nc46417","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210122684"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yota Komoriya","raw_affiliation_strings":["Technology Development Laboratories, Sony Corporation,Human Technology R&D Department,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technology Development Laboratories, Sony Corporation,Human Technology R&D Department,Tokyo,Japan","institution_ids":["https://openalex.org/I4210122684"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210122684"],"apc_list":null,"apc_paid":null,"fwci":0.2023,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.49194216,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":1.0,"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"}},{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9914000034332275,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/photoplethysmogram","display_name":"Photoplethysmogram","score":0.8721255660057068},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.827800989151001},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6415036916732788},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5804226398468018},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5319032669067383},{"id":"https://openalex.org/keywords/heart-rate-variability","display_name":"Heart rate variability","score":0.5110799074172974},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4433019757270813},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4413289725780487},{"id":"https://openalex.org/keywords/wrist","display_name":"Wrist","score":0.41285908222198486},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3476104140281677},{"id":"https://openalex.org/keywords/heart-rate","display_name":"Heart rate","score":0.2537423372268677},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.20868337154388428},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.14471369981765747},{"id":"https://openalex.org/keywords/blood-pressure","display_name":"Blood pressure","score":0.07012936472892761},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.06289705634117126}],"concepts":[{"id":"https://openalex.org/C116390426","wikidata":"https://www.wikidata.org/wiki/Q7187885","display_name":"Photoplethysmogram","level":3,"score":0.8721255660057068},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.827800989151001},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6415036916732788},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5804226398468018},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5319032669067383},{"id":"https://openalex.org/C71635504","wikidata":"https://www.wikidata.org/wiki/Q933954","display_name":"Heart rate variability","level":4,"score":0.5110799074172974},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4433019757270813},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4413289725780487},{"id":"https://openalex.org/C2778216619","wikidata":"https://www.wikidata.org/wiki/Q185706","display_name":"Wrist","level":2,"score":0.41285908222198486},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3476104140281677},{"id":"https://openalex.org/C2777953023","wikidata":"https://www.wikidata.org/wiki/Q1073121","display_name":"Heart rate","level":3,"score":0.2537423372268677},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.20868337154388428},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.14471369981765747},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.07012936472892761},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.06289705634117126},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aciiw59127.2023.10388137","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aciiw59127.2023.10388137","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2005741801","https://openalex.org/W2534209845","https://openalex.org/W2553272317","https://openalex.org/W2575460524","https://openalex.org/W2593096495","https://openalex.org/W2792140820","https://openalex.org/W2902882282","https://openalex.org/W2912732526","https://openalex.org/W2956711847","https://openalex.org/W2958197594","https://openalex.org/W2962182608","https://openalex.org/W2979945695","https://openalex.org/W2980106875","https://openalex.org/W3005353690","https://openalex.org/W3098716956","https://openalex.org/W3205108302","https://openalex.org/W3211951101","https://openalex.org/W4295427561","https://openalex.org/W4308123703"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W3196000489","https://openalex.org/W2092419518","https://openalex.org/W2809283485","https://openalex.org/W4293768783","https://openalex.org/W4288347394","https://openalex.org/W1489924780","https://openalex.org/W2135573418"],"abstract_inverted_index":{"Heart":[0],"rate":[1],"variability":[2],"(HRV)":[3],"analysis":[4,31,53],"in":[5,64,72,86,117,121],"a":[6,23,46,59,65,73,98],"wristband":[7],"photoplethysmography":[8],"(PPG)":[9],"device":[10,68,144,166],"is":[11],"gathering":[12],"interest":[13],"for":[14,162,176],"emotion":[15],"and":[16,26,36,54,94,114,150,170],"stress":[17,56,119,137],"recognition.":[18],"However,":[19],"motion":[20,79,112],"artifacts":[21],"are":[22,82],"critical":[24],"issue,":[25],"comprehensive":[27],"evaluation":[28,49],"from":[29],"HRV":[30,52],"to":[32,106,172],"the":[33,122,130,135,141,160,163,173,177],"model":[34,92,115],"performance":[35,139,169],"interpretability":[37,116,171],"should":[38],"be":[39],"conducted.":[40],"In":[41,154],"this":[42],"study,":[43],"we":[44,90,132],"constructed":[45],"physiologically":[47],"interpretable":[48],"framework":[50],"of":[51,140],"acute":[55,118,136],"recognition":[57,120,138],"using":[58,97],"deep":[60],"neural":[61],"network":[62],"(DNN)":[63],"wrist-worn":[66,123,142,164],"PPG":[67,124,143,165],"compared":[69],"with":[70],"that":[71,100,129,159],"chest-worn":[74,178],"electrocardiography":[75],"(ECG)":[76],"device,":[77],"considering":[78],"artifacts,":[80],"which":[81],"an":[83],"important":[84],"issue":[85],"wild":[87],"environments.":[88],"Furthermore,":[89],"developed":[91,133],"training":[93],"testing":[95],"methods":[96],"DNN":[99],"takes":[101],"signal":[102],"quality":[103],"into":[104],"account":[105],"achieve":[107],"both":[108],"accuracy":[109,149],"(robustness":[110],"against":[111],"artifacts)":[113],"device.":[125,180],"The":[126],"results":[127],"suggest":[128],"method":[131,161,175],"improved":[134],"throughout":[145],"our":[146],"experiments":[147],"(78.4%":[148],"77.0%":[151],"F1":[152],"score).":[153],"addition,":[155],"it":[156],"was":[157],"observed":[158],"demonstrated":[167],"comparable":[168],"reference":[174],"ECG":[179]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}