{"id":"https://openalex.org/W4320516947","doi":"https://doi.org/10.48550/arxiv.2208.01095","title":"Efficient Personalized Learning for Wearable Health Applications using HyperDimensional Computing","display_name":"Efficient Personalized Learning for Wearable Health Applications using HyperDimensional Computing","publication_year":2022,"publication_date":"2022-08-01","ids":{"openalex":"https://openalex.org/W4320516947","doi":"https://doi.org/10.48550/arxiv.2208.01095"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2208.01095","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2208.01095","pdf_url":"https://arxiv.org/pdf/2208.01095","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2208.01095","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000229090","display_name":"Sina Shahhosseini","orcid":"https://orcid.org/0000-0002-7967-4547"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shahhosseini, Sina","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107947136","display_name":"Yang Ni","orcid":"https://orcid.org/0000-0003-0794-1949"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ni, Yang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024899750","display_name":"Hamidreza Alikhani","orcid":"https://orcid.org/0000-0002-0983-1260"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alikhani, Hamidreza","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021900330","display_name":"Emad Kasaeyan Naeini","orcid":"https://orcid.org/0000-0002-7438-2641"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Naeini, Emad Kasaeyan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033221192","display_name":"Mohsen Imani","orcid":"https://orcid.org/0000-0002-5761-0622"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Imani, Mohsen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007817952","display_name":"Nikil Dutt","orcid":"https://orcid.org/0000-0002-3060-8119"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dutt, Nikil","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5042140592","display_name":"Amir M. Rahmani","orcid":"https://orcid.org/0000-0003-0725-1155"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rahmani, Amir M.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5000229090"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/personalization","display_name":"Personalization","score":0.8035356402397156},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7663359642028809},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.7473839521408081},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.7216284275054932},{"id":"https://openalex.org/keywords/wearable-technology","display_name":"Wearable technology","score":0.5763517618179321},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.5309735536575317},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5251526236534119},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47981691360473633},{"id":"https://openalex.org/keywords/resilience","display_name":"Resilience (materials science)","score":0.47152623534202576},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46237868070602417},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45206910371780396},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.41628116369247437},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.333919882774353},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.12738901376724243},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.09654903411865234}],"concepts":[{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.8035356402397156},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7663359642028809},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.7473839521408081},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.7216284275054932},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.5763517618179321},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5309735536575317},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5251526236534119},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47981691360473633},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.47152623534202576},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46237868070602417},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45206910371780396},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.41628116369247437},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.333919882774353},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.12738901376724243},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.09654903411865234},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2208.01095","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2208.01095","pdf_url":"https://arxiv.org/pdf/2208.01095","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2208.01095","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2208.01095","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2208.01095","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2208.01095","pdf_url":"https://arxiv.org/pdf/2208.01095","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.8899999856948853,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3090300519","https://openalex.org/W2514492205","https://openalex.org/W4250401876","https://openalex.org/W2943851981","https://openalex.org/W2566526749","https://openalex.org/W2907667791","https://openalex.org/W3047461507","https://openalex.org/W3126390843","https://openalex.org/W4245880644","https://openalex.org/W4312415459"],"abstract_inverted_index":{"Health":[0],"monitoring":[1,27],"applications":[2],"increasingly":[3],"rely":[4],"on":[5,58,71,95],"machine":[6,83],"learning":[7,32,70,84,105],"techniques":[8],"to":[9,36,67,80,90,93,157],"learn":[10],"end-user":[11],"physiological":[12,43],"and":[13,42,45,110,124,130,144],"behavioral":[14,41],"patterns":[15],"in":[16,26],"everyday":[17],"settings.":[18],"Considering":[19],"the":[20,52,65,82,87,135,150,161],"significant":[21],"role":[22],"of":[23,60,137,153],"wearable":[24,62,96],"devices":[25,63,109],"human":[28],"body":[29],"parameters,":[30],"on-device":[31,104,128],"can":[33],"be":[34,91],"utilized":[35],"build":[37],"personalized":[38],"models":[39,85],"for":[40,49,107,113],"patterns,":[44],"provide":[46],"data":[47],"privacy":[48,131],"users":[50],"at":[51],"same":[53],"time.":[54],"However,":[55],"resource":[56],"constraints":[57],"most":[59],"these":[61],"prevent":[64],"ability":[66],"perform":[68],"online":[69],"them.":[72],"To":[73],"address":[74],"this":[75],"issue,":[76],"it":[77],"is":[78],"required":[79],"rethink":[81],"from":[86],"algorithmic":[88],"perspective":[89],"suitable":[92],"run":[94],"devices.":[97],"Hyperdimensional":[98],"computing":[99],"(HDC)":[100],"offers":[101,119],"a":[102,170],"well-suited":[103],"solution":[106],"resource-constrained":[108],"provides":[111],"support":[112],"privacy-preserving":[114],"personalization.":[115],"Our":[116],"HDC-based":[117],"method":[118],"flexibility,":[120],"high":[121],"efficiency,":[122],"resilience,":[123],"performance":[125],"while":[126,168],"enabling":[127],"personalization":[129],"protection.":[132],"We":[133],"evaluate":[134],"efficacy":[136],"our":[138,147],"approach":[139],"using":[140],"three":[141],"case":[142],"studies":[143],"show":[145],"that":[146],"system":[148],"improves":[149],"energy":[151],"efficiency":[152],"training":[154],"by":[155],"up":[156],"$45.8\\times$":[158],"compared":[159],"with":[160],"state-of-the-art":[162],"Deep":[163],"Neural":[164],"Network":[165],"(DNN)":[166],"algorithms":[167],"offering":[169],"comparable":[171],"accuracy.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2023-02-14T00:00:00"}
