{"id":"https://openalex.org/W4413096118","doi":"https://doi.org/10.1109/smacd65553.2025.11092090","title":"A Cost-Efficient Implementation of an SSVEP-Based Brain-Controlled Robotic Arm System","display_name":"A Cost-Efficient Implementation of an SSVEP-Based Brain-Controlled Robotic Arm System","publication_year":2025,"publication_date":"2025-07-07","ids":{"openalex":"https://openalex.org/W4413096118","doi":"https://doi.org/10.1109/smacd65553.2025.11092090"},"language":"en","primary_location":{"id":"doi:10.1109/smacd65553.2025.11092090","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smacd65553.2025.11092090","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 21st International Conference on Synthesis, Modeling, Analysis and Simulation Methods, and Applications to Circuits Design (SMACD)","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/A5100654418","display_name":"Hongliang Chen","orcid":"https://orcid.org/0000-0001-5786-9493"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongliang Chen","raw_affiliation_strings":["Shenzhen University,College of Electronic and Information Engineering,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University,College of Electronic and Information Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101860041","display_name":"Weiwei Shi","orcid":"https://orcid.org/0000-0003-4551-8420"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Shi","raw_affiliation_strings":["Shenzhen University,College of Electronic and Information Engineering,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University,College of Electronic and Information Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100654418"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24333788,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998000264167786,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9817000031471252,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9502000212669373,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/robotic-arm","display_name":"Robotic arm","score":0.7682225704193115},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6981188654899597},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.4945933520793915},{"id":"https://openalex.org/keywords/arm-architecture","display_name":"ARM architecture","score":0.42796722054481506},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41453081369400024},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37704572081565857},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.24501356482505798},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.1564238965511322},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.1311689019203186},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07686570286750793}],"concepts":[{"id":"https://openalex.org/C150415221","wikidata":"https://www.wikidata.org/wiki/Q40687","display_name":"Robotic arm","level":2,"score":0.7682225704193115},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6981188654899597},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.4945933520793915},{"id":"https://openalex.org/C26771161","wikidata":"https://www.wikidata.org/wiki/Q16980","display_name":"ARM architecture","level":2,"score":0.42796722054481506},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41453081369400024},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37704572081565857},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.24501356482505798},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.1564238965511322},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.1311689019203186},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07686570286750793}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smacd65553.2025.11092090","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smacd65553.2025.11092090","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 21st International Conference on Synthesis, Modeling, Analysis and Simulation Methods, and Applications to Circuits Design (SMACD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2605492512","https://openalex.org/W2801003907","https://openalex.org/W3091798308","https://openalex.org/W3127224190","https://openalex.org/W3174004144","https://openalex.org/W3183638985","https://openalex.org/W4377079833","https://openalex.org/W4385327052","https://openalex.org/W4387123758","https://openalex.org/W4396559916","https://openalex.org/W4399193331","https://openalex.org/W4403024427","https://openalex.org/W4403212942"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"This":[0,77],"study":[1,118],"presents":[2],"a":[3,8,24,33,53,60,120],"low-cost":[4],"FPGA":[5,93],"implementation":[6],"of":[7,16,43,82],"single":[9],"channel":[10],"SSVEP-BCI":[11],"system,":[12],"achieved":[13],"real-time":[14,126],"control":[15,115],"the":[17,38,80,83],"robotic":[18,113],"arm.":[19],"The":[20],"proposed":[21],"architecture":[22],"integrates":[23],"hybrid":[25],"preprocessing":[26],"chain":[27],"that":[28,123],"merges":[29],"differential":[30],"filtering":[31],"with":[32,86],"coefficient-symmetric":[34],"FIR":[35],"design,":[36],"achieving":[37],"reduction":[39,68],"in":[40,69,112],"hardware":[41],"resource":[42,71],"42.8%.":[44],"A":[45],"radix-4":[46],"DIF":[47],"FFT":[48],"module":[49],"is":[50],"implemented":[51],"using":[52,97],"four-stage":[54],"pipelined":[55],"SDF":[56],"structure,":[57],"optimized":[58],"by":[59],"surface-fitting-based":[61],"approximate":[62],"complex":[63],"multiplier":[64],"to":[65,108],"achieve":[66],"70.6%":[67],"DSPs":[70],"while":[72],"preserving":[73],"spectral":[74],"analysis":[75],"precision.":[76],"system":[78],"demonstrates":[79],"accuracy":[81],"classification":[84,128],"83.4%":[85],"176mW":[87],"power":[88],"consumption":[89],"on":[90],"Xilinx":[91],"Artix-7":[92],"(xc7a35tcsg324-1).":[94],"Experimental":[95],"validation":[96],"both":[98],"proprietary":[99],"datasets":[100,103],"and":[101,130],"open":[102],"confirms":[104],"superior":[105],"performance.":[106],"Compared":[107],"conventional":[109],"PC-based":[110],"solutions":[111],"arm":[114],"tasks,":[116],"this":[117],"establishes":[119],"hardware-efficient":[121],"framework":[122],"effectively":[124],"balances":[125],"operation,":[127],"accuracy,":[129],"low-power":[131],"constraints":[132],"for":[133],"practical":[134],"BCI":[135],"deployments.":[136]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}