Matches in SemOpenAlex for { <https://semopenalex.org/work/W3045899631> ?p ?o ?g. }
Showing items 1 to 84 of
84
with 100 items per page.
- W3045899631 endingPage "138276" @default.
- W3045899631 startingPage "138264" @default.
- W3045899631 abstract "To boost the usability of a robotic prosthetic hand, providing degrees of freedom to every single finger is inevitable. Under the name of simultaneous proportional control (SPC), many studies have proposed methods to achieve this goal. In this paper, we propose a method to generate a regression model of a neuromuscular system called the Constrained AutoEncoder Network (CAEN) that estimates finger forces using a surface electromyogram (sEMG). Modifying the autoencoder from deep learning, the model is generated in a semi-unsupervised manner where only sEMG data and finger labels are used. In the learning process, the finger labels are used at the central layer of the network, where the three finger forces are estimated, to prevent penetration of other finger signals to each finger node and the network is trained in the constrained manner. This process results in independence among estimated finger forces such that the manipulability of multiple fingers is highly improved. The proposed model was compared with four previously reported SPC models in two tests: offline and online tests. In the offline test, the CAEN showed good results but not the best results. However, in the online test, which involved reaching target positions for three fingers simultaneously and proportionally, the proposed model showed the best results for three of six online performance indices (the completion rate, completion time, and throughput). Emphasizing the independence among estimated finger forces in the training process is the key point of the proposed method distinct from previous studies and the results showed that it was effective in the online control." @default.
- W3045899631 created "2020-08-03" @default.
- W3045899631 creator A5026617161 @default.
- W3045899631 creator A5036348885 @default.
- W3045899631 creator A5058505853 @default.
- W3045899631 date "2020-01-01" @default.
- W3045899631 modified "2023-09-29" @default.
- W3045899631 title "Estimating Simultaneous and Proportional Finger Force Intention Based on sEMG Using a Constrained Autoencoder" @default.
- W3045899631 cites W1168853092 @default.
- W3045899631 cites W1964025242 @default.
- W3045899631 cites W1965769973 @default.
- W3045899631 cites W2080596365 @default.
- W3045899631 cites W2092102206 @default.
- W3045899631 cites W2096869840 @default.
- W3045899631 cites W2097092203 @default.
- W3045899631 cites W2097292795 @default.
- W3045899631 cites W2099391160 @default.
- W3045899631 cites W2099391470 @default.
- W3045899631 cites W2099509424 @default.
- W3045899631 cites W2100338757 @default.
- W3045899631 cites W2113190957 @default.
- W3045899631 cites W2122936696 @default.
- W3045899631 cites W2166474928 @default.
- W3045899631 cites W2261736307 @default.
- W3045899631 cites W2294478862 @default.
- W3045899631 cites W2501245757 @default.
- W3045899631 cites W2569969175 @default.
- W3045899631 cites W2570357259 @default.
- W3045899631 cites W2735762883 @default.
- W3045899631 cites W2758171466 @default.
- W3045899631 cites W2765452429 @default.
- W3045899631 cites W2792578571 @default.
- W3045899631 cites W2793187201 @default.
- W3045899631 cites W2899373823 @default.
- W3045899631 cites W2909970681 @default.
- W3045899631 cites W2923078152 @default.
- W3045899631 cites W2946154472 @default.
- W3045899631 cites W2971316385 @default.
- W3045899631 doi "https://doi.org/10.1109/access.2020.3012741" @default.
- W3045899631 hasPublicationYear "2020" @default.
- W3045899631 type Work @default.
- W3045899631 sameAs 3045899631 @default.
- W3045899631 citedByCount "4" @default.
- W3045899631 countsByYear W30458996312021 @default.
- W3045899631 countsByYear W30458996312022 @default.
- W3045899631 countsByYear W30458996312023 @default.
- W3045899631 crossrefType "journal-article" @default.
- W3045899631 hasAuthorship W3045899631A5026617161 @default.
- W3045899631 hasAuthorship W3045899631A5036348885 @default.
- W3045899631 hasAuthorship W3045899631A5058505853 @default.
- W3045899631 hasBestOaLocation W30458996311 @default.
- W3045899631 hasConcept C101738243 @default.
- W3045899631 hasConcept C153180895 @default.
- W3045899631 hasConcept C154945302 @default.
- W3045899631 hasConcept C28490314 @default.
- W3045899631 hasConcept C41008148 @default.
- W3045899631 hasConcept C50644808 @default.
- W3045899631 hasConceptScore W3045899631C101738243 @default.
- W3045899631 hasConceptScore W3045899631C153180895 @default.
- W3045899631 hasConceptScore W3045899631C154945302 @default.
- W3045899631 hasConceptScore W3045899631C28490314 @default.
- W3045899631 hasConceptScore W3045899631C41008148 @default.
- W3045899631 hasConceptScore W3045899631C50644808 @default.
- W3045899631 hasLocation W30458996311 @default.
- W3045899631 hasLocation W30458996312 @default.
- W3045899631 hasOpenAccess W3045899631 @default.
- W3045899631 hasPrimaryLocation W30458996311 @default.
- W3045899631 hasRelatedWork W2592385986 @default.
- W3045899631 hasRelatedWork W2772780115 @default.
- W3045899631 hasRelatedWork W2775464024 @default.
- W3045899631 hasRelatedWork W2785535669 @default.
- W3045899631 hasRelatedWork W2897995864 @default.
- W3045899631 hasRelatedWork W2966657595 @default.
- W3045899631 hasRelatedWork W2998168123 @default.
- W3045899631 hasRelatedWork W3090006671 @default.
- W3045899631 hasRelatedWork W4281924768 @default.
- W3045899631 hasRelatedWork W4287995534 @default.
- W3045899631 hasVolume "8" @default.
- W3045899631 isParatext "false" @default.
- W3045899631 isRetracted "false" @default.
- W3045899631 magId "3045899631" @default.
- W3045899631 workType "article" @default.