{"id":"https://openalex.org/W4407574647","doi":"https://doi.org/10.1109/tcsi.2025.3540564","title":"WASENN: Wavelet Assisted Stochastic Enabled Neural Network for Human Activity Recognition","display_name":"WASENN: Wavelet Assisted Stochastic Enabled Neural Network for Human Activity Recognition","publication_year":2025,"publication_date":"2025-02-14","ids":{"openalex":"https://openalex.org/W4407574647","doi":"https://doi.org/10.1109/tcsi.2025.3540564"},"language":"en","primary_location":{"id":"doi:10.1109/tcsi.2025.3540564","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsi.2025.3540564","pdf_url":null,"source":{"id":"https://openalex.org/S116977442","display_name":"IEEE Transactions on Circuits and Systems I Regular Papers","issn_l":"1549-8328","issn":["1549-8328","1558-0806"],"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 Transactions on Circuits and Systems I: Regular Papers","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/A5079070222","display_name":"Roshwin Sengupta","orcid":"https://orcid.org/0009-0004-7970-6619"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Roshwin Sengupta","raw_affiliation_strings":["Institute of Computer Architecture and Computer Engineering, University of Stuttgart, Stuttgart, Germany"],"raw_orcid":"https://orcid.org/0009-0004-7970-6619","affiliations":[{"raw_affiliation_string":"Institute of Computer Architecture and Computer Engineering, University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027416202","display_name":"Ilia Polian","orcid":"https://orcid.org/0000-0002-6563-2725"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ilia Polian","raw_affiliation_strings":["Institute of Computer Architecture and Computer Engineering, University of Stuttgart, Stuttgart, Germany"],"raw_orcid":"https://orcid.org/0000-0002-6563-2725","affiliations":[{"raw_affiliation_string":"Institute of Computer Architecture and Computer Engineering, University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101995490","display_name":"John P. Hayes","orcid":"https://orcid.org/0000-0002-4747-492X"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John P. Hayes","raw_affiliation_strings":["Computer Engineering Laboratory, University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":"https://orcid.org/0000-0002-4747-492X","affiliations":[{"raw_affiliation_string":"Computer Engineering Laboratory, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7655,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.67032849,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"72","issue":"10","first_page":"5761","last_page":"5773"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9296000003814697,"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":0.9296000003814697,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.901199996471405,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.5938687324523926},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5839141607284546},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5691935420036316},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4589250385761261},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.4300643801689148},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41822880506515503}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5938687324523926},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5839141607284546},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5691935420036316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4589250385761261},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.4300643801689148},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41822880506515503}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsi.2025.3540564","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsi.2025.3540564","pdf_url":null,"source":{"id":"https://openalex.org/S116977442","display_name":"IEEE Transactions on Circuits and Systems I Regular Papers","issn_l":"1549-8328","issn":["1549-8328","1558-0806"],"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 Transactions on Circuits and Systems I: Regular Papers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2085225894","display_name":null,"funder_award_id":"CCF-2006704","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5982717943","display_name":null,"funder_award_id":"PO 1220/12-1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W2016053056","https://openalex.org/W2017634428","https://openalex.org/W2027269053","https://openalex.org/W2064675550","https://openalex.org/W2114997074","https://openalex.org/W2151770284","https://openalex.org/W2219995598","https://openalex.org/W2531174837","https://openalex.org/W2612910926","https://openalex.org/W2737035606","https://openalex.org/W2770265919","https://openalex.org/W2793345836","https://openalex.org/W2944495281","https://openalex.org/W2951248525","https://openalex.org/W2963993350","https://openalex.org/W2974437627","https://openalex.org/W2990925323","https://openalex.org/W3011785450","https://openalex.org/W3011864379","https://openalex.org/W3017361427","https://openalex.org/W3024761859","https://openalex.org/W3047171309","https://openalex.org/W3093799822","https://openalex.org/W3121678941","https://openalex.org/W3126697167","https://openalex.org/W3133590696","https://openalex.org/W3193054036","https://openalex.org/W3193597430","https://openalex.org/W4206703604","https://openalex.org/W4214843096","https://openalex.org/W4229456264","https://openalex.org/W4251476106","https://openalex.org/W4290043219","https://openalex.org/W4312242332","https://openalex.org/W4318820409","https://openalex.org/W4392240693","https://openalex.org/W4396520110"],"related_works":["https://openalex.org/W2382174632","https://openalex.org/W2129959498","https://openalex.org/W2784060934","https://openalex.org/W2902714807","https://openalex.org/W2537489131","https://openalex.org/W2046633342","https://openalex.org/W2394084632","https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W2077021924"],"abstract_inverted_index":{"Human":[0],"activity":[1],"recognition":[2],"(HAR)":[3],"is":[4],"a":[5],"challenging":[6],"area":[7,179],"of":[8,27,53,142,165],"research":[9],"with":[10,79,187],"widespread":[11],"applications":[12],"in":[13,18,39,66,169],"human-computer":[14],"interaction.":[15],"Recent":[16],"advances":[17],"neural":[19,115,128],"networks":[20,129],"(NNs)":[21],"have":[22],"greatly":[23],"improved":[24],"the":[25,37,59,80,112,152,163,166],"methods":[26,104],"HAR":[28,154],"feature":[29,102],"extraction":[30,103],"from":[31],"wearable":[32],"sensor":[33],"data":[34],"and":[35,72,82,100,130,139,144,148,155,171,180,184],"increased":[36],"interest":[38],"their":[40,146],"classification":[41,85,191],"using":[42,91],"NNs.":[43],"While":[44],"most":[45],"prior":[46],"work":[47],"has":[48],"relied":[49],"on":[50,151,190],"software":[51],"implementations":[52,63],"NN-based":[54],"HAR,":[55],"we":[56,124],"investigate":[57],"for":[58,64,119],"first":[60],"time":[61],"hardware":[62,93,159],"use":[65],"resource-constrained":[67],"edge":[68,71],"devices.":[69],"Emerging":[70],"near-sensor":[73],"systems":[74],"must":[75],"avoid":[76],"costly":[77],"communication":[78],"cloud":[81],"perform":[83],"complex":[84],"tasks":[86],"locally.":[87],"This":[88],"points":[89],"to":[90],"low-area":[92],"technology":[94],"such":[95,105],"as":[96,106],"stochastic":[97],"computing":[98],"(SC)":[99],"enhanced":[101],"wavelet":[107,167],"transform":[108,168],"(WT).":[109],"We":[110,135],"explore":[111],"wavelet-assisted":[113],"stochastic-enabled":[114],"network":[116],"(WASENN)":[117],"design":[118],"HAR.":[120],"The":[121],"NN":[122],"types":[123],"consider":[125],"are":[126],"convolutional":[127],"long":[131],"short-term":[132],"memory":[133],"networks.":[134],"study":[136],"both":[137],"partial":[138],"full":[140],"versions":[141],"WASENN":[143],"evaluate":[145],"performance":[147],"resource":[149],"utilization":[150],"UCI":[153],"WISDM":[156],"datasets.":[157],"Our":[158],"synthesis":[160],"results":[161],"show":[162,175],"superiority":[164],"accuracy":[170],"size.":[172],"They":[173],"also":[174],"that":[176],"SC":[177],"reduces":[178],"power":[181],"by":[182],"32%":[183],"74%":[185],"respectively":[186],"little":[188],"impact":[189],"accuracy.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}