{"id":"https://openalex.org/W4312242332","doi":"https://doi.org/10.1109/iscas48785.2022.9937939","title":"Wavelet Transform Assisted Neural Networks for Human Activity Recognition","display_name":"Wavelet Transform Assisted Neural Networks for Human Activity Recognition","publication_year":2022,"publication_date":"2022-05-28","ids":{"openalex":"https://openalex.org/W4312242332","doi":"https://doi.org/10.1109/iscas48785.2022.9937939"},"language":"en","primary_location":{"id":"doi:10.1109/iscas48785.2022.9937939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas48785.2022.9937939","pdf_url":null,"source":{"id":"https://openalex.org/S4363604393","display_name":"2022 IEEE International Symposium on Circuits and Systems (ISCAS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Circuits and Systems (ISCAS)","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/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":true,"raw_author_name":"Roshwin Sengupta","raw_affiliation_strings":["Institute of Computer Architecture and Computer Engineering, University of Stuttgart,Stuttgart,Germany","Institute of Computer Architecture and Computer Engineering, University of Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Architecture and Computer Engineering, University of Stuttgart,Stuttgart,Germany","institution_ids":["https://openalex.org/I100066346"]},{"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","Institute of Computer Architecture and Computer Engineering, University of Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Architecture and Computer Engineering, University of Stuttgart,Stuttgart,Germany","institution_ids":["https://openalex.org/I100066346"]},{"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\u2013Ann Arbor","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":["University of Michigan,Computer Engineering Laboratory,Ann Arbor,Michigan,USA","Computer Engineering Laboratory, University of Michigan, Ann Arbor, Michigan, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan,Computer Engineering Laboratory,Ann Arbor,Michigan,USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"Computer Engineering Laboratory, University of Michigan, Ann Arbor, Michigan, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5079070222"],"corresponding_institution_ids":["https://openalex.org/I100066346"],"apc_list":null,"apc_paid":null,"fwci":0.3612,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.67923856,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1254","last_page":"1258"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.998199999332428,"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":0.998199999332428,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9923999905586243,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.987500011920929,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8578453063964844},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.7329707145690918},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6263440251350403},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6212429404258728},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.6054462194442749},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5285904407501221},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.515494167804718},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4799111783504486},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.47077223658561707},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4265994131565094},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.4215222895145416},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41532814502716064},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.3994901776313782},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3909878134727478},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.34340474009513855},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.24085551500320435}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8578453063964844},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.7329707145690918},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6263440251350403},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6212429404258728},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.6054462194442749},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5285904407501221},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.515494167804718},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4799111783504486},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.47077223658561707},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4265994131565094},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.4215222895145416},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41532814502716064},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.3994901776313782},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3909878134727478},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.34340474009513855},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.24085551500320435},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas48785.2022.9937939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas48785.2022.9937939","pdf_url":null,"source":{"id":"https://openalex.org/S4363604393","display_name":"2022 IEEE International Symposium on Circuits and Systems (ISCAS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":24,"referenced_works":["https://openalex.org/W1923002919","https://openalex.org/W2016053056","https://openalex.org/W2017634428","https://openalex.org/W2064675550","https://openalex.org/W2097117768","https://openalex.org/W2098866314","https://openalex.org/W2219995598","https://openalex.org/W2247209766","https://openalex.org/W2506886870","https://openalex.org/W2531174837","https://openalex.org/W2540822603","https://openalex.org/W2607941059","https://openalex.org/W2737035606","https://openalex.org/W2793345836","https://openalex.org/W2794717185","https://openalex.org/W2807963368","https://openalex.org/W2912361013","https://openalex.org/W2951248525","https://openalex.org/W3011785450","https://openalex.org/W3017361427","https://openalex.org/W3126697167","https://openalex.org/W6674872755","https://openalex.org/W6728817311","https://openalex.org/W6752381170"],"related_works":["https://openalex.org/W2120447654","https://openalex.org/W2977179488","https://openalex.org/W2144453115","https://openalex.org/W2128223750","https://openalex.org/W4238532390","https://openalex.org/W2188872161","https://openalex.org/W2961779879","https://openalex.org/W797688974","https://openalex.org/W2002978035","https://openalex.org/W2209382646"],"abstract_inverted_index":{"Human":[0],"activity":[1],"recognition":[2],"(HAR)":[3],"is":[4,94,122],"a":[5,79,95,172],"challenging":[6],"area":[7],"of":[8,24,53,134,160],"research":[9],"with":[10],"many":[11],"applications":[12],"in":[13,18,39,69,164],"human-computer":[14],"interaction.":[15],"With":[16],"advances":[17],"artificial":[19],"neural":[20],"networks":[21,170],"(ANNs),":[22],"methods":[23],"HAR":[25,147],"feature":[26,108],"extraction":[27],"from":[28],"wearable":[29],"sensor":[30],"data":[31],"have":[32,36],"greatly":[33],"improved":[34],"and":[35,88,119,137,141,148,166],"increased":[37],"interest":[38],"their":[40,139],"classification":[41],"using":[42],"ANNs.":[43],"Most":[44],"prior":[45],"work":[46],"has":[47],"only":[48],"investigated":[49],"the":[50,60,86,124,145,158,161],"software":[51],"implementations":[52,66,133],"ANN-based":[54],"HAR.":[55],"Here,":[56],"we":[57,76,82],"investigate,":[58],"for":[59,67,127],"first":[61,78],"time,":[62],"two":[63],"novel":[64],"hardware":[65,132],"use":[68],"resource-constrained":[70,128],"edge":[71],"devices.":[72],"Through":[73],"architecture":[74],"exploration,":[75],"identify":[77],"hybrid":[80],"ANN":[81],"call":[83],"DCLSTM":[84],"incorporating":[85],"convolutional":[87],"long-short-term":[89],"memory":[90],"techniques.":[91],"The":[92],"second":[93],"much":[96],"more":[97],"compact":[98],"implementation":[99],"WCLSTM":[100],"that":[101],"uses":[102],"wavelet":[103],"transforms":[104],"(WTs)":[105],"to":[106],"enhance":[107],"extraction;":[109],"it":[110,121],"can":[111],"achieve":[112,171],"even":[113],"better":[114,125,173],"accuracy":[115,165,174],"while":[116],"being":[117],"smaller":[118],"simpler;":[120],"therefore":[123],"choice":[126],"applications.":[129],"We":[130],"present":[131],"these":[135],"ANNs":[136],"evaluate":[138],"performance":[140],"resource":[142],"utilization":[143],"on":[144,153],"UCI":[146],"WISDM":[149],"datasets.":[150],"Synthesis":[151],"results":[152],"an":[154],"FPGA":[155],"platform":[156],"show":[157],"superiority":[159],"WT-assisted":[162],"version":[163],"size.":[167],"Moreover,":[168],"our":[169],"than":[175],"earlier":[176],"published":[177],"works.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}