{"id":"https://openalex.org/W7151365475","doi":"https://doi.org/10.48550/arxiv.2604.04832","title":"When One Sensor Fails: Tolerating Dysfunction in Multi-Sensor Prototypes","display_name":"When One Sensor Fails: Tolerating Dysfunction in Multi-Sensor Prototypes","publication_year":2026,"publication_date":"2026-04-06","ids":{"openalex":"https://openalex.org/W7151365475","doi":"https://doi.org/10.48550/arxiv.2604.04832"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.04832","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04832","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.04832","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104435547","display_name":"Freek Hens","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hens, Freek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133080105","display_name":"Amirhossein Sadough","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sadough, Amirhossein","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133092662","display_name":"Aleksa Bok\u0161an","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bok\u0161an, Aleksa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070228671","display_name":"Mahyar Shahsavari","orcid":"https://orcid.org/0000-0001-7703-6835"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shahsavari, Mahyar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5065991691","display_name":"Mohammad Mahdi Dehshibi","orcid":"https://orcid.org/0000-0001-8112-5419"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dehshibi, Mohammad Mahdi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.8547000288963318,"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/T10784","display_name":"Muscle activation and electromyography studies","score":0.8547000288963318,"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/T10338","display_name":"Advanced Sensor and Energy Harvesting Materials","score":0.025800000876188278,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.01640000008046627,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/electromyography","display_name":"Electromyography","score":0.6302000284194946},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5620999932289124},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5566999912261963},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5424000024795532},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5266000032424927},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.42289999127388},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.34549999237060547}],"concepts":[{"id":"https://openalex.org/C2777515770","wikidata":"https://www.wikidata.org/wiki/Q507369","display_name":"Electromyography","level":2,"score":0.6302000284194946},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6100000143051147},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6068000197410583},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5620999932289124},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5566999912261963},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5424000024795532},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5266000032424927},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3249000012874603},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2969000041484833},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2964000105857849},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.2703999876976013},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.04832","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04832","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.04832","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04832","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6861700415611267}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Surface":[0],"electromyography":[1],"(sEMG)":[2],"sensors":[3],"are":[4],"widely":[5],"used":[6],"in":[7,31,94],"human-computer":[8],"interaction,":[9],"yet":[10],"the":[11,51],"failure":[12],"of":[13,39,79],"a":[14,23,28,77],"single":[15],"sensor":[16,71,90],"can":[17],"compromise":[18],"system":[19],"usability.":[20],"We":[21],"propose":[22],"methodological":[24],"framework":[25],"for":[26],"implementing":[27],"fail-safe":[29],"mechanism":[30],"multi-sensor":[32],"sEMG":[33,37],"systems.":[34],"Using":[35],"arm":[36],"recordings":[38],"rock-paper-scissors":[40],"gestures,":[41],"we":[42],"extracted":[43],"hand-crafted":[44],"features":[45],"and":[46,67,73,92,96],"quantified":[47],"class":[48],"separability":[49],"via":[50],"maximum":[52],"Fisher":[53],"discriminant":[54],"ratio":[55],"(FDR).":[56],"A":[57],"multi-layer":[58],"perceptron":[59],"validated":[60],"our":[61],"approach,":[62],"consistent":[63],"with":[64],"prior":[65],"findings":[66],"physiological":[68],"evidence.":[69],"Systematic":[70],"ablations":[72],"FDR":[74],"analysis":[75],"produced":[76],"ranking":[78,85],"crucial":[80],"versus":[81],"replaceable":[82],"sensors.":[83],"This":[84],"informs":[86],"robust":[87],"device":[88],"design,":[89],"redundancy,":[91],"reliability":[93],"clinical":[95],"practical":[97],"applications.":[98]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-08T00:00:00"}