FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4308052683> ?p ?o ?g. }

• W4308052683 endingPage "217" @default.
• W4308052683 startingPage "208" @default.
• W4308052683 abstract "The design of prosthetic controllers by means of neurophysiological signals still poses a crucial challenge to bioengineers. State of the art of electromyographic (EMG) continuous pattern recognition controllers rely on the questionable assumption that repeated muscular contractions produce repeatable patterns of steady-state EMG signals. Conversely, we propose an algorithm that decodes wrist and hand movements by processing the signals that immediately follow the onset of contraction (i.e., the transient EMG). We collected EMG data from the forearms of 14 non-amputee and 5 transradial amputee participants while they performed wrist flexion/extension, pronation/supination, and four hand grasps (power, lateral, bi-digital, open). We firstly identified the combination of wrist and hand movements that yielded the best control performance for the same participant (intra-subject classification). Then, we assessed the ability of our algorithm to classify participant data that were not included in the training set (cross-subject classification). Our controller achieved a median accuracy of ~96% with non-amputees, while it achieved heterogeneous outcomes with amputees, with a median accuracy of ~89%. Importantly, for each amputee, it produced at least one acceptable combination of wrist-hand movements (i.e., with accuracy >85%). Regarding the cross-subject classifier, while our algorithm obtained promising results with non-amputees (accuracy up to ~80%), they were not as good with amputees (accuracy up to ~35%), possibly suggesting further assessments with domain-adaptation strategies. In general, our offline outcomes, together with a preliminary online assessment, support the hypothesis that the transient EMG decoding could represent a viable pattern recognition strategy, encouraging further online assessments." @default.
• W4308052683 created "2022-11-07" @default.
• W4308052683 creator A5000054939 @default.
• W4308052683 creator A5002959295 @default.
• W4308052683 creator A5006415512 @default.
• W4308052683 creator A5030921314 @default.
• W4308052683 creator A5062169154 @default.
• W4308052683 creator A5062966636 @default.
• W4308052683 date "2023-01-01" @default.
• W4308052683 modified "2023-10-17" @default.
• W4308052683 title "Decoding of Multiple Wrist and Hand Movements Using a Transient EMG Classifier" @default.
• W4308052683 cites W1971702085 @default.
• W4308052683 cites W1984002649 @default.
• W4308052683 cites W1984252493 @default.
• W4308052683 cites W1986953135 @default.
• W4308052683 cites W2001451792 @default.
• W4308052683 cites W2013463953 @default.
• W4308052683 cites W2022327534 @default.
• W4308052683 cites W2024075334 @default.
• W4308052683 cites W2086184552 @default.
• W4308052683 cites W2093016265 @default.
• W4308052683 cites W2095549742 @default.
• W4308052683 cites W2096553993 @default.
• W4308052683 cites W2123167643 @default.
• W4308052683 cites W2134408600 @default.
• W4308052683 cites W2137502844 @default.
• W4308052683 cites W2152093652 @default.
• W4308052683 cites W2165619603 @default.
• W4308052683 cites W2166060802 @default.
• W4308052683 cites W2171188488 @default.
• W4308052683 cites W2243789297 @default.
• W4308052683 cites W2333529830 @default.
• W4308052683 cites W2418845879 @default.
• W4308052683 cites W2619944123 @default.
• W4308052683 cites W2700703022 @default.
• W4308052683 cites W2765226128 @default.
• W4308052683 cites W2789760074 @default.
• W4308052683 cites W2891117137 @default.
• W4308052683 cites W2915782394 @default.
• W4308052683 cites W2951262163 @default.
• W4308052683 cites W2953030885 @default.
• W4308052683 cites W2954664426 @default.
• W4308052683 cites W2956204178 @default.
• W4308052683 cites W2962879438 @default.
• W4308052683 cites W2998114800 @default.
• W4308052683 cites W3019274887 @default.
• W4308052683 cites W3049774894 @default.
• W4308052683 cites W3083944853 @default.
• W4308052683 cites W3109719334 @default.
• W4308052683 cites W4242470988 @default.
• W4308052683 cites W629053621 @default.
• W4308052683 doi "https://doi.org/10.1109/tnsre.2022.3218430" @default.
• W4308052683 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36327175" @default.
• W4308052683 hasPublicationYear "2023" @default.
• W4308052683 type Work @default.
• W4308052683 citedByCount "2" @default.
• W4308052683 crossrefType "journal-article" @default.
• W4308052683 hasAuthorship W4308052683A5000054939 @default.
• W4308052683 hasAuthorship W4308052683A5002959295 @default.
• W4308052683 hasAuthorship W4308052683A5006415512 @default.
• W4308052683 hasAuthorship W4308052683A5030921314 @default.
• W4308052683 hasAuthorship W4308052683A5062169154 @default.
• W4308052683 hasAuthorship W4308052683A5062966636 @default.
• W4308052683 hasBestOaLocation W43080526831 @default.
• W4308052683 hasConcept C126322002 @default.
• W4308052683 hasConcept C126838900 @default.
• W4308052683 hasConcept C153180895 @default.
• W4308052683 hasConcept C154945302 @default.
• W4308052683 hasConcept C197525751 @default.
• W4308052683 hasConcept C24998067 @default.
• W4308052683 hasConcept C2777515770 @default.
• W4308052683 hasConcept C2777766275 @default.
• W4308052683 hasConcept C2778216619 @default.
• W4308052683 hasConcept C28490314 @default.
• W4308052683 hasConcept C41008148 @default.
• W4308052683 hasConcept C71924100 @default.
• W4308052683 hasConcept C95623464 @default.
• W4308052683 hasConcept C99508421 @default.
• W4308052683 hasConceptScore W4308052683C126322002 @default.
• W4308052683 hasConceptScore W4308052683C126838900 @default.
• W4308052683 hasConceptScore W4308052683C153180895 @default.
• W4308052683 hasConceptScore W4308052683C154945302 @default.
• W4308052683 hasConceptScore W4308052683C197525751 @default.
• W4308052683 hasConceptScore W4308052683C24998067 @default.
• W4308052683 hasConceptScore W4308052683C2777515770 @default.
• W4308052683 hasConceptScore W4308052683C2777766275 @default.
• W4308052683 hasConceptScore W4308052683C2778216619 @default.
• W4308052683 hasConceptScore W4308052683C28490314 @default.
• W4308052683 hasConceptScore W4308052683C41008148 @default.
• W4308052683 hasConceptScore W4308052683C71924100 @default.
• W4308052683 hasConceptScore W4308052683C95623464 @default.
• W4308052683 hasConceptScore W4308052683C99508421 @default.
• W4308052683 hasFunder F4320311224 @default.
• W4308052683 hasFunder F4320322581 @default.
• W4308052683 hasFunder F4320324633 @default.
• W4308052683 hasFunder F4320338335 @default.
• W4308052683 hasLocation W43080526831 @default.
• W4308052683 hasLocation W43080526832 @default.

• next