{"id":"https://openalex.org/W2916879374","doi":"https://doi.org/10.1109/tbme.2019.2899927","title":"Rehab-Net: Deep Learning Framework for Arm Movement Classification Using Wearable Sensors for Stroke Rehabilitation","display_name":"Rehab-Net: Deep Learning Framework for Arm Movement Classification Using Wearable Sensors for Stroke Rehabilitation","publication_year":2019,"publication_date":"2019-02-19","ids":{"openalex":"https://openalex.org/W2916879374","doi":"https://doi.org/10.1109/tbme.2019.2899927","mag":"2916879374","pmid":"https://pubmed.ncbi.nlm.nih.gov/30794162"},"language":"en","primary_location":{"id":"doi:10.1109/tbme.2019.2899927","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbme.2019.2899927","pdf_url":null,"source":{"id":"https://openalex.org/S5240358","display_name":"IEEE Transactions on Biomedical Engineering","issn_l":"0018-9294","issn":["0018-9294","1558-2531"],"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 Biomedical Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5059843828","display_name":"Madhuri Panwar","orcid":"https://orcid.org/0000-0003-4763-0707"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Madhuri Panwar","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Hyderabad"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Hyderabad","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060076901","display_name":"Dwaipayan Biswas","orcid":"https://orcid.org/0000-0002-1087-3433"},"institutions":[{"id":"https://openalex.org/I196972281","display_name":"Imec the Netherlands","ror":"https://ror.org/01ezq2j76","country_code":"NL","type":"facility","lineage":["https://openalex.org/I196972281"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Dwaipayan Biswas","raw_affiliation_strings":["Biomedical Circuits and Systems Group, IMEC"],"affiliations":[{"raw_affiliation_string":"Biomedical Circuits and Systems Group, IMEC","institution_ids":["https://openalex.org/I196972281"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015317306","display_name":"Harsh P. Bajaj","orcid":null},"institutions":[{"id":"https://openalex.org/I122964287","display_name":"National Institute of Technology Tiruchirappalli","ror":"https://ror.org/047x65e68","country_code":"IN","type":"education","lineage":["https://openalex.org/I122964287"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Harsh Bajaj","raw_affiliation_strings":["Department of Electrical and Electronics, National Institute of Technology Trichy"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics, National Institute of Technology Trichy","institution_ids":["https://openalex.org/I122964287"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109506536","display_name":"Michael J\u00f6bges","orcid":null},"institutions":[{"id":"https://openalex.org/I4210158660","display_name":"Universit\u00e4tsklinikum Brandenburg an der Havel","ror":"https://ror.org/04999hq03","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I4210158660"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Jobges","raw_affiliation_strings":["Brandenburg Klinik"],"affiliations":[{"raw_affiliation_string":"Brandenburg Klinik","institution_ids":["https://openalex.org/I4210158660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076279781","display_name":"Ruth Turk","orcid":"https://orcid.org/0000-0001-6332-5353"},"institutions":[{"id":"https://openalex.org/I43439940","display_name":"University of Southampton","ror":"https://ror.org/01ryk1543","country_code":"GB","type":"education","lineage":["https://openalex.org/I43439940"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ruth Turk","raw_affiliation_strings":["Faculty of Heath Sciences, University of Southampton"],"affiliations":[{"raw_affiliation_string":"Faculty of Heath Sciences, University of Southampton","institution_ids":["https://openalex.org/I43439940"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080441536","display_name":"Koushik Maharatna","orcid":"https://orcid.org/0000-0001-6518-2755"},"institutions":[{"id":"https://openalex.org/I43439940","display_name":"University of Southampton","ror":"https://ror.org/01ryk1543","country_code":"GB","type":"education","lineage":["https://openalex.org/I43439940"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Koushik Maharatna","raw_affiliation_strings":["School of Electronics and Computer Science, University of Southampton"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Computer Science, University of Southampton","institution_ids":["https://openalex.org/I43439940"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044085104","display_name":"Amit Acharyya","orcid":"https://orcid.org/0000-0002-5636-0676"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Amit Acharyya","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Hyderabad, Telangana, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Hyderabad, Telangana, India","institution_ids":["https://openalex.org/I65181880"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5059843828"],"corresponding_institution_ids":["https://openalex.org/I65181880"],"apc_list":null,"apc_paid":null,"fwci":12.9496,"has_fulltext":false,"cited_by_count":160,"citation_normalized_percentile":{"value":0.99114166,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"66","issue":"11","first_page":"3026","last_page":"3037"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10510","display_name":"Stroke Rehabilitation and Recovery","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2742","display_name":"Rehabilitation"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10510","display_name":"Stroke Rehabilitation and Recovery","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2742","display_name":"Rehabilitation"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9948999881744385,"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/T10784","display_name":"Muscle activation and electromyography studies","score":0.9897000193595886,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6631024479866028},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6202878952026367},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5617750883102417},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5430895090103149},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.5394488573074341},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4624142646789551},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.43047139048576355},{"id":"https://openalex.org/keywords/thumb","display_name":"Thumb","score":0.4291078746318817},{"id":"https://openalex.org/keywords/rehabilitation","display_name":"Rehabilitation","score":0.42124372720718384},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41649484634399414},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41136419773101807},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3421916961669922},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3386431336402893},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.11084714531898499}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6631024479866028},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6202878952026367},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5617750883102417},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5430895090103149},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.5394488573074341},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4624142646789551},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.43047139048576355},{"id":"https://openalex.org/C2776881184","wikidata":"https://www.wikidata.org/wiki/Q83360","display_name":"Thumb","level":2,"score":0.4291078746318817},{"id":"https://openalex.org/C2778818304","wikidata":"https://www.wikidata.org/wiki/Q1819478","display_name":"Rehabilitation","level":2,"score":0.42124372720718384},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41649484634399414},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41136419773101807},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3421916961669922},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3386431336402893},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.11084714531898499},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.0},{"id":"https://openalex.org/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000071939","descriptor_name":"Stroke Rehabilitation","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D000071939","descriptor_name":"Stroke Rehabilitation","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D000071939","descriptor_name":"Stroke Rehabilitation","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D000076251","descriptor_name":"Wearable Electronic Devices","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000076251","descriptor_name":"Wearable Electronic Devices","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000076251","descriptor_name":"Wearable Electronic Devices","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001132","descriptor_name":"Arm","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D001132","descriptor_name":"Arm","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D001132","descriptor_name":"Arm","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006802","descriptor_name":"Human Activities","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006802","descriptor_name":"Human Activities","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006802","descriptor_name":"Human Activities","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009068","descriptor_name":"Movement","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D009068","descriptor_name":"Movement","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D009068","descriptor_name":"Movement","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1109/tbme.2019.2899927","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbme.2019.2899927","pdf_url":null,"source":{"id":"https://openalex.org/S5240358","display_name":"IEEE Transactions on Biomedical Engineering","issn_l":"0018-9294","issn":["0018-9294","1558-2531"],"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 Biomedical Engineering","raw_type":"journal-article"},{"id":"pmid:30794162","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30794162","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on bio-medical engineering","raw_type":null},{"id":"pmh:oai:eprints.soton.ac.uk:430951","is_oa":false,"landing_page_url":"https://eprints.soton.ac.uk/430951/1/TBME_01598_2018.R1_preprint.docx","pdf_url":null,"source":{"id":"https://openalex.org/S4306401020","display_name":"ePrints Soton (University of Southampton)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I43439940","host_organization_name":"University of Southampton","host_organization_lineage":["https://openalex.org/I43439940"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"},{"id":"pmh:oai:raiith.iith.ac.in:4854","is_oa":false,"landing_page_url":"http://raiith.iith.ac.in/4854/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400292","display_name":"Research Archive of Indian Institute of Technology Hyderabad (Indian Institute of Technology Hyderabad)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I65181880","host_organization_name":"Indian Institute of Technology Hyderabad","host_organization_lineage":["https://openalex.org/I65181880"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6200000047683716}],"awards":[{"id":"https://openalex.org/G2521147833","display_name":null,"funder_award_id":"ECR/2015/000148","funder_id":"https://openalex.org/F4320334771","funder_display_name":"Science and Engineering Research Board"}],"funders":[{"id":"https://openalex.org/F4320334771","display_name":"Science and Engineering Research Board","ror":"https://ror.org/03ffdsr55"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W98188630","https://openalex.org/W1522301498","https://openalex.org/W1728842521","https://openalex.org/W1972208963","https://openalex.org/W1973555673","https://openalex.org/W1982434105","https://openalex.org/W1988702183","https://openalex.org/W1993492060","https://openalex.org/W1997559350","https://openalex.org/W1999712889","https://openalex.org/W2012557818","https://openalex.org/W2023302299","https://openalex.org/W2023969764","https://openalex.org/W2027279157","https://openalex.org/W2050646411","https://openalex.org/W2051552261","https://openalex.org/W2059732136","https://openalex.org/W2074172762","https://openalex.org/W2074841103","https://openalex.org/W2084553975","https://openalex.org/W2086067762","https://openalex.org/W2103408061","https://openalex.org/W2117594417","https://openalex.org/W2117727263","https://openalex.org/W2119144962","https://openalex.org/W2127095067","https://openalex.org/W2128121198","https://openalex.org/W2141778357","https://openalex.org/W2163605009","https://openalex.org/W2163901584","https://openalex.org/W2185985772","https://openalex.org/W2211696483","https://openalex.org/W2244817607","https://openalex.org/W2274499208","https://openalex.org/W2288074780","https://openalex.org/W2289514765","https://openalex.org/W2315124452","https://openalex.org/W2344094861","https://openalex.org/W2509065397","https://openalex.org/W2513424882","https://openalex.org/W2516710120","https://openalex.org/W2531174837","https://openalex.org/W2533935468","https://openalex.org/W2540822603","https://openalex.org/W2563686712","https://openalex.org/W2580792129","https://openalex.org/W2582488883","https://openalex.org/W2610332124","https://openalex.org/W2726835547","https://openalex.org/W2736191430","https://openalex.org/W2749830906","https://openalex.org/W2753969215","https://openalex.org/W2768715246","https://openalex.org/W2768919374","https://openalex.org/W2781626483","https://openalex.org/W2783144430","https://openalex.org/W2785232201","https://openalex.org/W2796551753","https://openalex.org/W2962968413","https://openalex.org/W2963855167","https://openalex.org/W2964121744","https://openalex.org/W2964299589","https://openalex.org/W3098357269","https://openalex.org/W6604091132","https://openalex.org/W6631190155","https://openalex.org/W6637572315","https://openalex.org/W6677580257","https://openalex.org/W6684191040","https://openalex.org/W6686389255","https://openalex.org/W6696429117","https://openalex.org/W6704286305","https://openalex.org/W6728817311","https://openalex.org/W6748218416"],"related_works":["https://openalex.org/W2024231062","https://openalex.org/W2914514113","https://openalex.org/W4390996027","https://openalex.org/W2416243481","https://openalex.org/W3213857688","https://openalex.org/W2039797512","https://openalex.org/W2054797264","https://openalex.org/W2125232430","https://openalex.org/W2366442391","https://openalex.org/W3214136469"],"abstract_inverted_index":{"In":[0],"this":[1,196],"paper,":[2],"we":[3],"present":[4],"a":[5,35,47,69,175],"deep":[6],"learning":[7,153],"framework":[8,90],"\"Rehab-Net\"":[9],"for":[10,129],"effectively":[11],"classifying":[12],"three":[13,76],"upper":[14],"limb":[15],"movements":[16,77],"of":[17,26,37,61,107,132,140,169,179,195,205],"the":[18,27,31,75,85,130,180,202,206,210],"human":[19],"arm,":[20],"involving":[21,103],"extension,":[22],"flexion,":[23],"and":[24,51,113,145,162,172],"rotation":[25],"forearm,":[28],"which,":[29],"over":[30],"time,":[32],"could":[33],"provide":[34],"measure":[36],"rehabilitation":[38],"progress.":[39],"The":[40,87,192],"proposed":[41,88,181],"framework,":[42],"Rehab-Net":[43,89],"is":[44,198],"formulated":[45],"with":[46,64,109,165,186],"personalized,":[48],"light":[49],"weight":[50],"low-complex,":[52],"customized":[53],"convolutional":[54],"neural":[55],"network":[56],"(CNN)":[57],"model,":[58],"using":[59],"two-layers":[60],"CNN,":[62],"interleaved":[63],"pooling":[65],"layers,":[66],"followed":[67],"by":[68],"fully":[70],"connected":[71],"layer":[72],"that":[73],"classifies":[74],"from":[78,84],"tri-axial":[79],"acceleration":[80],"input":[81],"data":[82,95,144,149],"collected":[83,96],"wrist.":[86],"was":[91],"validated":[92],"on":[93,142,147],"sensor":[94],"in":[97],"two":[98],"situations:":[99],"1)":[100],"semi-naturalistic":[101,143],"environment":[102],"an":[104,137,166,187],"archetypal":[105],"activity":[106],"\"making-tea\"":[108],"four":[110],"stroke":[111,119],"survivors":[112,120],"2)":[114],"natural":[115],"environment,":[116],"where":[117],"ten":[118],"were":[121],"free":[122],"to":[123,199],"perform":[124],"any":[125],"desired":[126],"arm":[127],"movement":[128],"duration":[131],"120":[133],"min.":[134],"We":[135],"achieved":[136],"overall":[138],"accuracy":[139,168],"97.89%":[141],"88.87%":[146],"naturalistic":[148],"which":[150],"exceeded":[151],"state-of-the-art":[152],"algorithms":[154],"namely,":[155],"linear":[156],"discriminant":[157],"analysis,":[158],"support":[159],"vector":[160],"machines,":[161],"k-means":[163],"clustering":[164],"average":[167],"48.89%,":[170],"44.14%,":[171],"27.64%.":[173],"Subsequently,":[174],"computational":[176],"complexity":[177],"analysis":[178],"model":[182],"has":[183],"been":[184],"discussed":[185],"eye":[188],"toward":[189],"hardware":[190],"implementation.":[191],"clinical":[193,203],"significance":[194],"study":[197],"accurately":[200],"monitor":[201],"progress":[204],"rehabilitated":[207],"subjects":[208],"under":[209],"ambulatory":[211],"settings.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":34},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":28},{"year":2021,"cited_by_count":29},{"year":2020,"cited_by_count":19},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}