{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T13:37:21Z","timestamp":1774100241988,"version":"3.50.1"},"reference-count":42,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,1,31]],"date-time":"2020-01-31T00:00:00Z","timestamp":1580428800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61403049"],"award-info":[{"award-number":["61403049"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2018CDXYTX0010"],"award-info":[{"award-number":["2018CDXYTX0010"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>As a kind of intelligent instrument, an electronic tongue (E-tongue) realizes liquid analysis with an electrode-sensor array and certain machine learning methods. The large amplitude pulse voltammetry (LAPV) is a regular E-tongue type that prefers to collect a large amount of response data at a high sampling frequency within a short time. Therefore, a fast and effective feature extraction method is necessary for machine learning methods. Considering the fact that massive common-mode components (high correlated signals) in the sensor-array responses would depress the recognition performance of the machine learning models, we have proposed an alternative feature extraction method named feature specificity enhancement (FSE) for feature specificity enhancement and feature dimension reduction. The proposed FSE method highlights the specificity signals by eliminating the common mode signals on paired sensor responses. Meanwhile, the radial basis function is utilized to project the original features into a nonlinear space. Furthermore, we selected the kernel extreme learning machine (KELM) as the recognition part owing to its fast speed and excellent flexibility. Two datasets from LAPV E-tongues have been adopted for the evaluation of the machine-learning models. One is collected by a designed E-tongue for beverage identification and the other one is a public benchmark. For performance comparison, we introduced several machine-learning models consisting of different combinations of feature extraction and recognition methods. The experimental results show that the proposed FSE coupled with KELM demonstrates obvious superiority to other models in accuracy, time consumption and memory cost. Additionally, low parameter sensitivity of the proposed model has been demonstrated as well.<\/jats:p>","DOI":"10.3390\/s20030772","type":"journal-article","created":{"date-parts":[[2020,1,31]],"date-time":"2020-01-31T05:55:46Z","timestamp":1580450146000},"page":"772","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Electronic Tongue Recognition with Feature Specificity Enhancement"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9398-7005","authenticated-orcid":false,"given":"Tao","family":"Liu","sequence":"first","affiliation":[{"name":"School of Microelectronics and Communication Engineering, Chongqing University, No. 174 Shazheng Street, Shapingba District, Chongqing 400044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanbing","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Microelectronics and Communication Engineering, Chongqing University, No. 174 Shazheng Street, Shapingba District, Chongqing 400044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongqi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Microelectronics and Communication Engineering, Chongqing University, No. 174 Shazheng Street, Shapingba District, Chongqing 400044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Microelectronics and Communication Engineering, Chongqing University, No. 174 Shazheng Street, Shapingba District, Chongqing 400044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianhua","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Microelectronics and Communication Engineering, Chongqing University, No. 174 Shazheng Street, Shapingba District, Chongqing 400044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/S0003-2670(03)00301-5","article-title":"Evaluation of Italian wine by the electronic tongue: Recognition, quantitative analysis and correlation with human sensory perception","volume":"484","author":"Legin","year":"2003","journal-title":"Analytica Chimica Acta"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"6255","DOI":"10.1109\/JSEN.2015.2455535","article-title":"Monitoring the Fermentation Process and Detection of Optimum Fermentation Time of Black Tea Using an Electronic Tongue","volume":"15","author":"Ghosh","year":"2015","journal-title":"IEEE Sensors J."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2750","DOI":"10.3390\/s7112750","article-title":"Metalloporphyrin\u2014Based Electronic Tongue: An Application for the Analysis of Italian White Wines","volume":"7","author":"Verrelli","year":"2007","journal-title":"Sensors"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3001","DOI":"10.1109\/JSEN.2013.2263125","article-title":"Electronic Tongues\u2014A Review","volume":"13","author":"Tahara","year":"2013","journal-title":"IEEE Sensors J."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/S0003-2670(00)00873-4","article-title":"Electronic tongues for environmental monitoring based on sensor arrays and pattern recognition: a review","volume":"426","author":"Stenberg","year":"2001","journal-title":"Anal. 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