{"id":"https://openalex.org/W2944339549","doi":"https://doi.org/10.1109/jiot.2018.2863039","title":"A Concise Temporal Data Representation Model for Prediction in Biomedical Wearable Devices","display_name":"A Concise Temporal Data Representation Model for Prediction in Biomedical Wearable Devices","publication_year":2018,"publication_date":"2018-08-03","ids":{"openalex":"https://openalex.org/W2944339549","doi":"https://doi.org/10.1109/jiot.2018.2863039","mag":"2944339549"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2018.2863039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2018.2863039","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-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/A5088584264","display_name":"Alireza Manashty","orcid":"https://orcid.org/0000-0001-5971-3468"},"institutions":[{"id":"https://openalex.org/I106938459","display_name":"University of New Brunswick","ror":"https://ror.org/05nkf0n29","country_code":"CA","type":"education","lineage":["https://openalex.org/I106938459"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Alireza Manashty","raw_affiliation_strings":["Department of Computer Science, University of New Brunswick, Saint John, NB, Canada"],"raw_orcid":"https://orcid.org/0000-0001-5971-3468","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of New Brunswick, Saint John, NB, Canada","institution_ids":["https://openalex.org/I106938459"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044191316","display_name":"Janet Light Thompson","orcid":null},"institutions":[{"id":"https://openalex.org/I106938459","display_name":"University of New Brunswick","ror":"https://ror.org/05nkf0n29","country_code":"CA","type":"education","lineage":["https://openalex.org/I106938459"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Janet Light Thompson","raw_affiliation_strings":["Department of Computer Science, University of New Brunswick, Saint John, NB, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of New Brunswick, Saint John, NB, Canada","institution_ids":["https://openalex.org/I106938459"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081939409","display_name":"H. Rahimpour Soleimani","orcid":"https://orcid.org/0000-0002-3510-5676"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hamid Soleimani","raw_affiliation_strings":["Department of Bioengineering, Imperial College London, London, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Bioengineering, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.7365,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.74194222,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"6","issue":"2","first_page":"1438","last_page":"1445"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9810000061988831,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9750999808311462,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7971572875976562},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.5832613110542297},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5753023624420166},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5725502967834473},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5561283826828003},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.49033069610595703},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4595372676849365},{"id":"https://openalex.org/keywords/wearable-technology","display_name":"Wearable technology","score":0.4543428421020508},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4495660960674286},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.44709131121635437},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4178527295589447},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.41532260179519653},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4103284180164337},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38809770345687866}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7971572875976562},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.5832613110542297},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5753023624420166},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5725502967834473},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5561283826828003},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.49033069610595703},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4595372676849365},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.4543428421020508},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4495660960674286},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.44709131121635437},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4178527295589447},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.41532260179519653},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4103284180164337},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38809770345687866},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2018.2863039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2018.2863039","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.4699999988079071,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W163964114","https://openalex.org/W1599494361","https://openalex.org/W1988539834","https://openalex.org/W2011329709","https://openalex.org/W2021362925","https://openalex.org/W2023302299","https://openalex.org/W2054780155","https://openalex.org/W2074099390","https://openalex.org/W2079735306","https://openalex.org/W2126868529","https://openalex.org/W2130942839","https://openalex.org/W2131368080","https://openalex.org/W2146489051","https://openalex.org/W2157331557","https://openalex.org/W2162800060","https://openalex.org/W2396881363","https://openalex.org/W2404901863","https://openalex.org/W2563686712","https://openalex.org/W2768702723","https://openalex.org/W2788342393","https://openalex.org/W2963078493","https://openalex.org/W4301459152","https://openalex.org/W6679436768","https://openalex.org/W6680930200","https://openalex.org/W6748477523"],"related_works":["https://openalex.org/W3090300519","https://openalex.org/W2514492205","https://openalex.org/W4250401876","https://openalex.org/W2943851981","https://openalex.org/W2095299560","https://openalex.org/W2907667791","https://openalex.org/W3047461507","https://openalex.org/W3126390843","https://openalex.org/W4245880644","https://openalex.org/W2528680939"],"abstract_inverted_index":{"Predictive":[0],"analytics":[1],"and":[2,27,30,90,164,183,217],"event":[3],"forecasting":[4,143],"using":[5,145,218],"deep":[6,39],"learning":[7],"techniques":[8,43],"require":[9],"processing":[10],"long-term":[11,142],"historical":[12,46,165],"data":[13,84,111],"which":[14],"is":[15,105,138,224],"infeasible":[16],"in":[17,25,195,235],"low-power":[18],"wearable":[19],"devices.":[20],"Such":[21],"devices":[22],"are":[23,31],"constrained":[24],"memory":[26,209],"computational":[28],"power,":[29],"pushed":[32],"to":[33,52,72,95,140,185,192,227,232],"their":[34],"limits":[35],"by":[36],"resource":[37],"hungry":[38],"neural":[40],"networks.":[41],"Current":[42],"either":[44],"ignore":[45],"data,":[47],"or":[48,119,127],"convert":[49],"temporal":[50],"sequences":[51],"pattern":[53],"sequences,":[54],"eliminating":[55],"valuable":[56],"properties":[57,85],"such":[58,86],"as":[59,87,135],"time":[60,70,101,176,215],"and/or":[61],"recency.":[62],"The":[63],"proposed":[64],"model":[65,99,171],"maps":[66],"arbitrary-length":[67],"multivariate":[68],"discrete":[69],"series":[71,102],"a":[73,122,130,148,205],"concise":[74],"sequence,":[75],"called":[76,134],"mapped":[77],"interval":[78],"sequence":[79,123],"(MIS).":[80],"MIS":[81],"retains":[82],"original":[83],"time,":[88],"recency,":[89],"scale,":[91],"without":[92],"being":[93],"susceptible":[94],"missing":[96,240],"values.":[97,241],"Life":[98],"for":[100],"(LMts)":[103],"mapping,":[104],"capable":[106],"of":[107,110,116,124,152,177,181],"mapping":[108],"billions":[109],"elements":[112,126],"with":[113,179,204,238],"sampling":[114],"rate":[115],"several":[117],"kHz":[118],"higher":[120],"into":[121],"32":[125],"fewer.":[128],"Furthermore,":[129],"new":[131],"loss":[132],"function":[133],"tolerance":[136],"error":[137],"introduced":[139],"improve":[141],"events":[144],"LMts.":[146],"In":[147,167],"smart":[149],"health":[150,158],"Internet":[151],"Things":[153],"environment,":[154],"LMts":[155,170,198,223],"enables":[156],"real-time":[157],"predictions":[159],"depending":[160],"on":[161],"both":[162],"recent":[163],"data.":[166],"addition,":[168],"the":[169,174,200],"can":[172],"predict":[173],"approximate":[175],"events,":[178],"granularity":[180],"seconds":[182],"up":[184,231],"years.":[186],"Experimental":[187],"results":[188],"show":[189],"that,":[190],"compared":[191],"previous":[193],"studies":[194],"fall":[196,230],"prediction,":[197],"achieves":[199],"same":[201],"100%":[202],"accuracy":[203],"single":[206],"long":[207],"short-term":[208],"layer,":[210],"while":[211],"covering":[212],"16\u00d7":[213],"longer":[214],"period":[216],"80\u00d7":[219],"less":[220],"weight":[221],"parameters.":[222],"also":[225],"used":[226],"forecast":[228],"human":[229],"14":[233],"s":[234],"advance":[236],"even":[237],"50%":[239]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}