{"id":"https://openalex.org/W4413283375","doi":"https://doi.org/10.3390/computers14080334","title":"Time\u2013Frequency Feature Fusion Approach for Hemiplegic Gait Recognition","display_name":"Time\u2013Frequency Feature Fusion Approach for Hemiplegic Gait Recognition","publication_year":2025,"publication_date":"2025-08-18","ids":{"openalex":"https://openalex.org/W4413283375","doi":"https://doi.org/10.3390/computers14080334"},"language":"en","primary_location":{"id":"doi:10.3390/computers14080334","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers14080334","pdf_url":"https://www.mdpi.com/2073-431X/14/8/334/pdf?version=1755510746","source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-431X/14/8/334/pdf?version=1755510746","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042497062","display_name":"Lihao Mao","orcid":null},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Linglong Mao","raw_affiliation_strings":["College of Computer Science and Cybersecurity, Chengdu University of Technology, Chengdu 610059, China"],"raw_orcid":"https://orcid.org/0009-0000-9612-3272","affiliations":[{"raw_affiliation_string":"College of Computer Science and Cybersecurity, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011774979","display_name":"Zhanyong Mei","orcid":null},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhanyong Mei","raw_affiliation_strings":["College of Computer Science and Cybersecurity, Chengdu University of Technology, Chengdu 610059, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Cybersecurity, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5011774979","https://openalex.org/A5042497062"],"corresponding_institution_ids":["https://openalex.org/I31595395"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":0.8446,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.72743243,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"14","issue":"8","first_page":"334","last_page":"334"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9991000294685364,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9750000238418579,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/gait","display_name":"Gait","score":0.711376428604126},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.538709282875061},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5120521187782288},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5017602443695068},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.493186891078949},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45339325070381165},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4062034785747528},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.37048494815826416},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.22449031472206116}],"concepts":[{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.711376428604126},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.538709282875061},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5120521187782288},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5017602443695068},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.493186891078949},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45339325070381165},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4062034785747528},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.37048494815826416},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.22449031472206116},{"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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/computers14080334","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers14080334","pdf_url":"https://www.mdpi.com/2073-431X/14/8/334/pdf?version=1755510746","source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a82b21ee3ab74d6a8fc42abfa5d931de","is_oa":true,"landing_page_url":"https://doaj.org/article/a82b21ee3ab74d6a8fc42abfa5d931de","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computers, Vol 14, Iss 8, p 334 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/computers14080334","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers14080334","pdf_url":"https://www.mdpi.com/2073-431X/14/8/334/pdf?version=1755510746","source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2644296213","display_name":null,"funder_award_id":"2021-YF05\u201302175-SN","funder_id":"https://openalex.org/F4320322922","funder_display_name":"Department of Science and Technology of Sichuan Province"},{"id":"https://openalex.org/G2684495600","display_name":null,"funder_award_id":"2021-YF05\u201302175-SN","funder_id":"https://openalex.org/F4320326670","funder_display_name":"Chengdu Science and Technology Bureau"},{"id":"https://openalex.org/G8544280510","display_name":null,"funder_award_id":"2023YFG0271","funder_id":"https://openalex.org/F4320322922","funder_display_name":"Department of Science and Technology of Sichuan Province"}],"funders":[{"id":"https://openalex.org/F4320322922","display_name":"Department of Science and Technology of Sichuan Province","ror":"https://ror.org/04323m874"},{"id":"https://openalex.org/F4320326670","display_name":"Chengdu Science and Technology Bureau","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4413283375.pdf","grobid_xml":"https://content.openalex.org/works/W4413283375.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1963831245","https://openalex.org/W2064675550","https://openalex.org/W2091858323","https://openalex.org/W2119821739","https://openalex.org/W2295598076","https://openalex.org/W2790360611","https://openalex.org/W2804715912","https://openalex.org/W2911964244","https://openalex.org/W2942807621","https://openalex.org/W2980102731","https://openalex.org/W2984360020","https://openalex.org/W3163465952","https://openalex.org/W3213333456","https://openalex.org/W4313275909","https://openalex.org/W4321788898","https://openalex.org/W4389428552","https://openalex.org/W4395448599","https://openalex.org/W4401101416","https://openalex.org/W4401909595","https://openalex.org/W4402125693","https://openalex.org/W6752061487","https://openalex.org/W6793164127","https://openalex.org/W6871587425"],"related_works":["https://openalex.org/W4321378240","https://openalex.org/W2998375644","https://openalex.org/W3147584709","https://openalex.org/W2099421762","https://openalex.org/W2530546662","https://openalex.org/W2113408265","https://openalex.org/W1989734657","https://openalex.org/W4226004263","https://openalex.org/W4210601529","https://openalex.org/W2528228280"],"abstract_inverted_index":{"Accurately":[0],"distinguishing":[1],"hemiplegic":[2,33,40,87,105],"gait":[3,6,34,41,88],"from":[4,25,103],"healthy":[5,109],"is":[7],"significant":[8],"for":[9,32],"alleviating":[10],"clinicians\u2019":[11],"diagnostic":[12],"workloads":[13],"and":[14,107,113,132,157,182,196,220],"enhancing":[15],"rehabilitation":[16],"efficiency.":[17],"The":[18,90,198],"center":[19],"of":[20,123,187,212],"pressure":[21,26,46,100],"(CoP)":[22],"trajectory":[23,96,126],"extracted":[24],"sensor":[27,101],"arrays":[28],"can":[29],"be":[30],"utilized":[31],"recognition.":[35,89],"Existing":[36],"research":[37],"studies":[38],"on":[39,44,75],"recognition":[42,55,215],"based":[43,74],"plantar":[45],"have":[47],"paid":[48],"limited":[49],"attention":[50],"to":[51,141,170,180],"the":[52,115,124,184,202],"differences":[53],"in":[54,214,218,222],"performance":[56,185],"offered":[57],"by":[58,166],"CoP":[59,95,125],"trajectories":[60],"along":[61],"different":[62,188],"directions.":[63],"To":[64],"address":[65],"this,":[66],"this":[67],"paper":[68],"proposes":[69],"a":[70,99,143],"neural":[71],"network":[72,83],"model":[73],"time\u2013frequency":[76],"domain":[77,81,121,139],"feature":[78],"interaction\u2014the":[79],"temporal\u2013frequency":[80],"interaction":[82],"(TFDI-Net)\u2014to":[84],"achieve":[85],"efficient":[86],"work":[91],"encompasses:":[92],"(1)":[93],"collecting":[94],"data":[97,162],"using":[98],"array":[102],"19":[104],"patients":[106],"29":[108],"subjects;":[110],"(2)":[111],"designing":[112],"implementing":[114],"TFDI-Net":[116,204],"architecture,":[117],"which":[118],"extracts":[119],"frequency":[120],"features":[122,140],"via":[127],"fast":[128],"Fourier":[129],"transform":[130],"(FFT)":[131],"interacts":[133],"or":[134],"fuses":[135],"them":[136],"with":[137,152],"time":[138],"construct":[142],"discriminative":[144],"joint":[145],"representation;":[146],"(3)":[147],"conducting":[148],"five-fold":[149],"cross-validation":[150],"comparisons":[151],"traditional":[153,206],"machine":[154,207],"learning":[155,159,208],"methods":[156],"deep":[158],"methods.":[160],"Intra-fold":[161],"augmentation":[163],"was":[164],"performed":[165],"adding":[167],"Gaussian":[168],"noise":[169],"each":[171],"training":[172],"fold":[173],"during":[174],"partitioning.":[175],"Box":[176],"plots":[177],"were":[178],"employed":[179],"visualize":[181],"analyze":[183],"metrics":[186],"models":[189],"across":[190],"test":[191],"folds,":[192],"revealing":[193],"their":[194],"stability":[195],"advantages.":[197],"results":[199],"demonstrate":[200],"that":[201],"proposed":[203],"outperforms":[205],"models,":[209],"achieving":[210],"improvements":[211],"2.89%":[213],"rate,":[216],"4.6%":[217],"F1-score,":[219],"8.25%":[221],"recall.":[223]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
