{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T14:15:06Z","timestamp":1766067306268,"version":"build-2065373602"},"reference-count":25,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,3,17]],"date-time":"2021-03-17T00:00:00Z","timestamp":1615939200000},"content-version":"vor","delay-in-days":75,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003995","name":"Natural Science Foundation of Anhui Province","doi-asserted-by":"publisher","award":["1908085MF204"],"award-info":[{"award-number":["1908085MF204"]}],"id":[{"id":"10.13039\/501100003995","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100015801","name":"Anhui Provincial Quality Engineering Project","doi-asserted-by":"publisher","award":["2018jyxm0459","2019zyrc081","2020szsfkc0294"],"award-info":[{"award-number":["2018jyxm0459","2019zyrc081","2020szsfkc0294"]}],"id":[{"id":"10.13039\/100015801","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015673","name":"Anhui Jianzhu University","doi-asserted-by":"publisher","award":["2020szkc03","2018jy03"],"award-info":[{"award-number":["2020szkc03","2018jy03"]}],"id":[{"id":"10.13039\/501100015673","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Sensors"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>A flexible tactile sensor array with 6 \u00d7 6 N\u2010type sensitive elements made of conductive rubber is presented in this paper. The property and principle of the tactile sensor are analyzed in detail. Based on the piezoresistivity of conductive rubber, this paper takes full advantage of the nonlinear approximation ability of the radial basis function neural network (RBFNN) method to approach the high\u2010dimensional mapping relation between the resistance values of the N\u2010type sensitive element and the three\u2010dimensional (3D) force and to accomplish the accurate prediction of the magnitude of 3D force loaded on the sensor. In the prediction process, the <jats:italic>k<\/jats:italic>\u2010means algorithm and recursive least square (RLS) method are used to optimize the RBFNN, and the <jats:italic>k<\/jats:italic>\u2010fold cross\u2010validation method is conducted to build the training set and testing set to improve the prediction precision of the 3D force. The optimized RBFNN with different spreads is used to verify its influence on the performance of 3D force prediction, and the results indicate that the spread value plays a very important role in the prediction process. Then, sliding window technology is introduced to build the RBFNN model. Experimental results show that setting the size of the sliding window appropriately can effectively reduce the prediction error of the 3D force exerted on the sensor and improve the performance of the RBFNN predictor, which means that the sliding window technology is very feasible and valid in 3D force prediction for the flexible tactile sensor. All of the results indicate that the optimized RBFNN with high robustness can be well applied to the 3D force prediction research of the flexible tactile sensor.<\/jats:p>","DOI":"10.1155\/2021\/8825019","type":"journal-article","created":{"date-parts":[[2021,3,17]],"date-time":"2021-03-17T14:50:09Z","timestamp":1615992609000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Three\u2010Dimensional Force Prediction of a Flexible Tactile Sensor Based on Radial Basis Function Neural Networks"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1972-3343","authenticated-orcid":false,"given":"Feilu","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1310-7320","authenticated-orcid":false,"given":"Yang","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,3,17]]},"reference":[{"key":"e_1_2_8_1_2","doi-asserted-by":"publisher","DOI":"10.3390\/s17091974"},{"key":"e_1_2_8_2_2","first-page":"1","article-title":"Touch position identification based on a flexible array-less super capacitive tactile sensor","volume":"9","author":"Liu J. 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