{"id":"https://openalex.org/W4405490995","doi":"https://doi.org/10.1109/embc53108.2024.10781668","title":"From Sprint to Recovery: LSTM-Powered Heart Rate Recovery Forecasting in HIIT Sessions","display_name":"From Sprint to Recovery: LSTM-Powered Heart Rate Recovery Forecasting in HIIT Sessions","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4405490995","doi":"https://doi.org/10.1109/embc53108.2024.10781668","pmid":"https://pubmed.ncbi.nlm.nih.gov/40039643"},"language":"en","primary_location":{"id":"doi:10.1109/embc53108.2024.10781668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc53108.2024.10781668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5080845073","display_name":"\u0406\u043b\u043b\u044f \u0424\u0435\u0434\u043e\u0440\u0456\u043d","orcid":"https://orcid.org/0000-0002-0611-9120"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Illia Fedorin","raw_affiliation_strings":["Samsung R&D Institute Ukraine,Strategy & Innovations Department,Kyiv,Ukraine"],"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute Ukraine,Strategy & Innovations Department,Kyiv,Ukraine","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038106668","display_name":"Anastasiia Smielova","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anastasiia Smielova","raw_affiliation_strings":["Samsung R&D Institute Ukraine,Strategy & Innovations Department,Kyiv,Ukraine"],"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute Ukraine,Strategy & Innovations Department,Kyiv,Ukraine","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086591960","display_name":"Margaryta Nastenko","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Margaryta Nastenko","raw_affiliation_strings":["Samsung R&D Institute Ukraine,Strategy & Innovations Department,Kyiv,Ukraine"],"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute Ukraine,Strategy & Innovations Department,Kyiv,Ukraine","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063857882","display_name":"Illia Krasnoshchok","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Illia Krasnoshchok","raw_affiliation_strings":["Samsung R&D Institute Ukraine,Strategy & Innovations Department,Kyiv,Ukraine"],"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute Ukraine,Strategy & Innovations Department,Kyiv,Ukraine","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5080845073"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.43569621,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2024","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9965000152587891,"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"}},"topics":[{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9965000152587891,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9955000281333923,"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/T11700","display_name":"Hemodynamic Monitoring and Therapy","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sprint","display_name":"Sprint","score":0.889032244682312},{"id":"https://openalex.org/keywords/heart-rate","display_name":"Heart rate","score":0.48690760135650635},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4532058537006378},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.3395649194717407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32740092277526855},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.28996020555496216},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.28053146600723267},{"id":"https://openalex.org/keywords/physical-therapy","display_name":"Physical therapy","score":0.22177225351333618},{"id":"https://openalex.org/keywords/blood-pressure","display_name":"Blood pressure","score":0.12405708432197571}],"concepts":[{"id":"https://openalex.org/C2776868573","wikidata":"https://www.wikidata.org/wiki/Q46855","display_name":"Sprint","level":2,"score":0.889032244682312},{"id":"https://openalex.org/C2777953023","wikidata":"https://www.wikidata.org/wiki/Q1073121","display_name":"Heart rate","level":3,"score":0.48690760135650635},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4532058537006378},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.3395649194717407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32740092277526855},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.28996020555496216},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.28053146600723267},{"id":"https://openalex.org/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"score":0.22177225351333618},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.12405708432197571}],"mesh":[{"descriptor_ui":"D000072696","descriptor_name":"High-Intensity Interval Training","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000072696","descriptor_name":"High-Intensity Interval Training","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000072696","descriptor_name":"High-Intensity Interval Training","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006339","descriptor_name":"Heart Rate","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D006339","descriptor_name":"Heart Rate","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D006339","descriptor_name":"Heart Rate","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc53108.2024.10781668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc53108.2024.10781668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:40039643","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40039643","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1598053028","https://openalex.org/W1886855146","https://openalex.org/W1976200630","https://openalex.org/W2905810301","https://openalex.org/W3022926411","https://openalex.org/W3081877814","https://openalex.org/W3084813517","https://openalex.org/W3095676345","https://openalex.org/W3107335993","https://openalex.org/W3162090373","https://openalex.org/W3197040406","https://openalex.org/W3208297018","https://openalex.org/W4200394775","https://openalex.org/W4207033168","https://openalex.org/W4295485608","https://openalex.org/W4361205581","https://openalex.org/W4362452418","https://openalex.org/W4386167565","https://openalex.org/W4386253020","https://openalex.org/W4386958277","https://openalex.org/W4389002680","https://openalex.org/W4389577101"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2899084033","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W2748952813","https://openalex.org/W1531601525"],"abstract_inverted_index":{"In":[0,81],"recent":[1],"years,":[2],"the":[3,11,16,70,127,141,175,191,197],"growing":[4],"interest":[5],"in":[6,15,30,184],"applying":[7],"artificial":[8],"intelligence":[9],"to":[10,94,111,126],"healthcare":[12],"domain,":[13],"especially":[14],"monitoring":[17,59],"and":[18,32,36,56,116,144,166,193],"control":[19],"of":[20,67,72,83],"health":[21,58],"status":[22],"during":[23,121],"fitness":[24],"activities,":[25],"has":[26,170],"opened":[27],"new":[28],"opportunities":[29],"understanding":[31],"enhancing":[33],"human":[34],"performance":[35],"health.":[37],"This":[38,99,152,168],"interdisciplinary":[39],"approach,":[40],"merging":[41],"cutting-edge":[42],"AI":[43],"with":[44,106,174],"exercise":[45,68],"physiology,":[46],"offers":[47],"promising":[48,172],"avenues":[49],"for":[50,190,196],"personalized":[51],"healthcare,":[52],"optimized":[53],"athletic":[54],"training,":[55],"advanced":[57,107],"techniques.":[60],"Current":[61],"study":[62],"addressing":[63],"a":[64,86,131,146],"critical":[65],"aspect":[66],"physiology:":[69],"forecasting":[71,186],"heart":[73],"rate":[74],"(HR)":[75],"recovery":[76,97],"patterns":[77],"following":[78],"high-intensity":[79,122],"intervals.":[80],"pursuit":[82],"this":[84],"objective,":[85],"comprehensive":[87],"deep":[88,108],"learning":[89,109],"framework":[90],"is":[91,130,150,187],"developed,":[92],"designed":[93],"forecast":[95],"HR":[96,114,119,158,163,185],"patterns.":[98],"system":[100],"integrates":[101],"signal":[102],"processing":[103],"techniques":[104],"combined":[105],"architectures":[110],"facilitate":[112],"real-time":[113],"measurements":[115],"predict":[117],"future":[118],"dynamics":[120],"interval":[123],"training.":[124],"Central":[125],"proposed":[128],"approach":[129,169],"long":[132],"short-term":[133],"memory":[134],"(LSTM)":[135],"based":[136],"encoder-decoder":[137],"architecture.":[138],"To":[139],"enhance":[140],"model's":[142],"accuracy":[143],"robustness,":[145],"task-specific":[147],"loss":[148],"function":[149,153],"employed.":[151],"not":[154],"only":[155],"calculates":[156],"standard":[157],"errors":[159],"but":[160],"also":[161],"incorporates":[162],"pattern":[164],"slopes":[165],"angles.":[167],"achieved":[171],"results,":[173],"model":[176],"demonstrating":[177],"strong":[178],"performance.":[179],"The":[180],"mean":[181],"absolute":[182],"error":[183],"3.5":[188],"bpm":[189,195],"encoder":[192],"3.8":[194],"decoder":[198],"parts.":[199]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}