{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T16:52:44Z","timestamp":1768323164880,"version":"3.49.0"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T00:00:00Z","timestamp":1664496000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T00:00:00Z","timestamp":1664496000000},"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":["62076114"],"award-info":[{"award-number":["62076114"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71874025"],"award-info":[{"award-number":["71874025"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Humanities and Social Sciences Research Planning Foundation of the Ministry of Education of China","award":["20YJA630058"],"award-info":[{"award-number":["20YJA630058"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Wireless Com Network"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>At present, it has become very convenient to collect channel state information (CSI) from ubiquitous commercial WiFi network cards, and the location or activity of a human who affects the CSI can be recognized by analyzing the change of the CSI. Therefore, wireless sensing technology based on the CSI has received widespread attention. However, the existing CSI-based gesture recognition methods still have some problems, which include that subcarrier selection is not optimized and motion interval extraction is not accurate enough, so the accuracy of gesture recognition methods still needs to be further improved. In response to the above problems, a gesture recognition method based on misalignment mean absolute deviation (MMAD) and KL divergence is proposed in the paper, which is called MMAD-KL-GR method. This method uses the proposed MMAD algorithm to extract the CSI amplitude intervals containing gesture information, then selects subcarriers by comparing the KL divergence of the CSI amplitude, and finally uses the subspace K-nearest neighbor (KNN) algorithm to recognize the gestures. Several experiments show that the MMAD-KL-GR method can effectively improve the accuracy of the gesture recognition.<\/jats:p>","DOI":"10.1186\/s13638-022-02178-4","type":"journal-article","created":{"date-parts":[[2022,9,29]],"date-time":"2022-09-29T23:04:02Z","timestamp":1664492642000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Gesture recognition method based on misalignment mean absolute deviation and KL divergence"],"prefix":"10.1186","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0664-1437","authenticated-orcid":false,"given":"Yong","family":"Tian","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chuanzhen","family":"Zhuang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiadong","family":"Cui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Runjie","family":"Qiao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuejun","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,9,30]]},"reference":[{"key":"2178_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10462-012-9356-9","volume":"43","author":"SS Rautaray","year":"2015","unstructured":"S.S. Rautaray, A. Agrawal, Vision based hand gesture recognition for human computer interaction: a survey. Artif. Intell. Rev. 43, 1\u201354 (2015)","journal-title":"Artif. Intell. Rev."},{"key":"2178_CR2","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1016\/j.imavis.2017.01.010","volume":"60","author":"S Herath","year":"2017","unstructured":"S. Herath, M. Harandi, F. Porikli, Going deeper into action recognition: a survey. Image Vis. Comput. 60, 4\u201321 (2017)","journal-title":"Image Vis. Comput."},{"key":"2178_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.infrared.2020.103464","volume":"111","author":"J Wang","year":"2020","unstructured":"J. Wang, T. Liu, X. Wang, Infrared hand gesture recognition with convolutional neural networks in double-teachers instruction mode classroom. Infrared Phys. Technol. 111, 103464 (2020)","journal-title":"Infrared Phys. Technol."},{"key":"2178_CR4","doi-asserted-by":"publisher","first-page":"2501","DOI":"10.1109\/TSMC.2018.2819026","volume":"50","author":"C Shen","year":"2020","unstructured":"C. Shen, Y. Chen, G. Yang et al., Toward hand-dominated activity recognition systems with wristband-interaction behavior analysis. IEEE Trans. Syst. Man Cybern. Syst. 50, 2501\u20132511 (2020)","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"2178_CR5","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1145\/1925861.1925870","volume":"41","author":"D Halperin","year":"2011","unstructured":"D. Halperin, W. Hu, A. Sheth et al., Tool release: Gathering 802.11n traces with channel state information. ACM SIGCOMM Comput. Commun. Rev. 41, 53 (2011)","journal-title":"ACM SIGCOMM Comput. Commun. Rev."},{"key":"2178_CR6","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1186\/s13638-018-1230-2","volume":"2018","author":"X Dang","year":"2018","unstructured":"X. Dang, Y. Huang, Z. Hao et al., PCA-Kalman: device-free indoor human behavior detection with commodity Wi-Fi. EURASIP J. Wirel. Commun. Netw. 2018, 214 (2018)","journal-title":"EURASIP J. Wirel. Commun. Netw."},{"key":"2178_CR7","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1186\/s13638-019-1371-y","volume":"2019","author":"L Zhang","year":"2019","unstructured":"L. Zhang, E. Ding, Y. Hu et al., A novel CSI-based fingerprinting for localization with a single AP. EURASIP J. Wirel. Commun. Netw. 2019, 51 (2019)","journal-title":"EURASIP J. Wirel. Commun. Netw."},{"key":"2178_CR8","doi-asserted-by":"publisher","first-page":"7678","DOI":"10.1109\/JIOT.2020.2988291","volume":"7","author":"J Wang","year":"2020","unstructured":"J. Wang, L. Zhang, C. Wang et al., Device-free human gesture recognition with generative adversarial networks. IEEE Internet Things J. 7, 7678\u20137688 (2020)","journal-title":"IEEE Internet Things J."},{"key":"2178_CR9","doi-asserted-by":"publisher","first-page":"101393","DOI":"10.1016\/j.pmcj.2021.101393","volume":"73","author":"X Shen","year":"2021","unstructured":"X. Shen, Z. Ni, L. Liu et al., WIPass: 1D-CNN-based smartphone keystroke recognition using WiFi signals. Pervasive Mob. Comput. 73, 101393 (2021)","journal-title":"Pervasive Mob. Comput."},{"key":"2178_CR10","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2022.3198248","author":"X Cheng","year":"2022","unstructured":"X. Cheng, B. Huang, CSI-based human continuous activity recognition using GMM-HMM. IEEE Sens. J. (2022). https:\/\/doi.org\/10.1109\/JSEN.2022.3198248","journal-title":"IEEE Sens. J."},{"key":"2178_CR11","doi-asserted-by":"publisher","first-page":"1659","DOI":"10.1109\/TVT.2016.2555986","volume":"66","author":"J Wang","year":"2017","unstructured":"J. Wang, X. Zhang, Q. Gao et al., Device-free simultaneous wireless localization and activity recognition with wavelet feature. IEEE Trans. Veh. Technol. 66, 1659\u20131669 (2017)","journal-title":"IEEE Trans. Veh. Technol."},{"key":"2178_CR12","doi-asserted-by":"publisher","first-page":"5632298","DOI":"10.1155\/2021\/5632298","volume":"2021","author":"Y Tian","year":"2021","unstructured":"Y. Tian, S. Li, C. Chen et al., Small CSI samples-based activity recognition: a deep learning approach using multidimensional features. Secur. Commun. Netw. 2021, 5632298 (2021)","journal-title":"Secur. Commun. Netw."},{"key":"2178_CR13","doi-asserted-by":"publisher","first-page":"1950050","DOI":"10.1142\/S0219691319500504","volume":"17","author":"L Yang","year":"2019","unstructured":"L. Yang, H. Su, C. Zhong et al., Hyperspectral image classification using wavelet transform-based smooth ordering. Int. J. Wavelets Multiresolut. Inf. Process. 17, 1950050 (2019)","journal-title":"Int. J. Wavelets Multiresolut. Inf. Process."},{"key":"2178_CR14","doi-asserted-by":"publisher","first-page":"304","DOI":"10.3390\/e21030304","volume":"21","author":"E Guariglia","year":"2019","unstructured":"E. Guariglia, Primality, fractality and image analysis. Entropy 21, 304 (2019)","journal-title":"Entropy"},{"key":"2178_CR15","doi-asserted-by":"publisher","first-page":"1696","DOI":"10.1109\/TSP.2019.2896246","volume":"67","author":"X Zheng","year":"2019","unstructured":"X. Zheng, Y. Tang, J. Zhou, A framework of adaptive multiscale wavelet decomposition for signals on undirected graphs. IEEE Trans. Signal Process. 67, 1696\u20131711 (2019)","journal-title":"IEEE Trans. Signal Process."},{"key":"2178_CR16","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.cviu.2017.08.002","volume":"162","author":"X Liu","year":"2017","unstructured":"X. Liu, H. Zhang, Y. Cheung et al., Efficient single image dehazing and denoising: An efficient multi-scale correlated wavelet approach. Comput. Vis. Image Underst. 162, 23\u201333 (2017)","journal-title":"Comput. Vis. Image Underst."},{"key":"2178_CR17","doi-asserted-by":"crossref","unstructured":"E. Guariglia, S. Silvestrov, Fractional-wavelet analysis of positive definite distributions and wavelets on d\u2019(c), in Engineering Mathematics II, Springer Proceedings in Mathematics and Statistics, pp. 337\u2013353 (2017)","DOI":"10.1007\/978-3-319-42105-6_16"},{"key":"2178_CR18","doi-asserted-by":"publisher","DOI":"10.1142\/8434","volume-title":"Document Analysis and Recognition by Wavelet And Fractal Theories","author":"YY Tang","year":"2012","unstructured":"Y.Y. Tang, Document Analysis and Recognition by Wavelet And Fractal Theories (The World Scientific Publishing Co, Singapore, 2012)"},{"key":"2178_CR19","doi-asserted-by":"publisher","first-page":"714","DOI":"10.3390\/e20090714","volume":"20","author":"E Guariglia","year":"2018","unstructured":"E. Guariglia, Harmonic Sierpinski gasket and applications. Entropy 20, 714 (2018)","journal-title":"Entropy"},{"key":"2178_CR20","doi-asserted-by":"publisher","first-page":"16911","DOI":"10.1109\/ACCESS.2018.2814575","volume":"6","author":"Z Tian","year":"2018","unstructured":"Z. Tian, J. Wang, X. Yang et al., WiCatch: A Wi-Fi based hand gesture recognition system. IEEE Access 6, 16911\u201316923 (2018)","journal-title":"IEEE Access"},{"key":"2178_CR21","doi-asserted-by":"publisher","first-page":"131102","DOI":"10.1109\/ACCESS.2019.2940386","volume":"7","author":"T Zhang","year":"2019","unstructured":"T. Zhang, T. Song, D. Chen et al., WiGrus: a WiFi-based gesture recognition system using software defined radio. IEEE Access 7, 131102\u2013131113 (2019)","journal-title":"IEEE Access"},{"key":"2178_CR22","doi-asserted-by":"publisher","first-page":"101289","DOI":"10.1016\/j.pmcj.2020.101289","volume":"69","author":"H Thariq","year":"2020","unstructured":"H. Thariq, H. Ahmad, K. Narasingamurthi et al., DF-WiSLR: device-free Wi-Fi-based sign language recognition. Pervasive Mob. Comput. 69, 101289 (2020)","journal-title":"Pervasive Mob. Comput."},{"key":"2178_CR23","doi-asserted-by":"publisher","first-page":"4757","DOI":"10.3390\/s20174757","volume":"20","author":"D Jiang","year":"2020","unstructured":"D. Jiang, M. Li, C. Xu, WiGAN: a WiFi based gesture recognition system with GANs. Sensors 20, 4757 (2020)","journal-title":"Sensors"},{"key":"2178_CR24","doi-asserted-by":"publisher","first-page":"4025","DOI":"10.3390\/s20144025","volume":"20","author":"Z Hao","year":"2020","unstructured":"Z. Hao, Y. Duan, X. Dang et al., Wi-SL: contactless fine-grained gesture recognition uses channel state information. Sensors 20, 4025 (2020)","journal-title":"Sensors"},{"key":"2178_CR25","doi-asserted-by":"publisher","first-page":"2789","DOI":"10.1109\/TMC.2020.3045635","volume":"21","author":"S Tan","year":"2022","unstructured":"S. Tan, J. Yang, Y. Chen, Enabling fine-grained finger gesture recognition on commodity WiFi devices. IEEE Trans. Mob. Comput. 21, 2789\u20132802 (2022)","journal-title":"IEEE Trans. Mob. Comput."},{"key":"2178_CR26","doi-asserted-by":"publisher","first-page":"8584","DOI":"10.1109\/JIOT.2021.3114309","volume":"9","author":"X Zhang","year":"2022","unstructured":"X. Zhang, C. Tang, K. Yin et al., Wifi-based cross-domain gesture recognition via modified prototypical networks. IEEE Internet Things J. 9, 8584\u20138596 (2022)","journal-title":"IEEE Internet Things J."},{"key":"2178_CR27","doi-asserted-by":"publisher","first-page":"736","DOI":"10.1109\/THMS.2022.3163189","volume":"52","author":"Y Gu","year":"2022","unstructured":"Y. Gu, X. Zhang, Y. Wang et al., WiGRUNT: WiFi-enabled gesture recognition using dual-attention network. IEEE Trans. Hum. Mach. Syst. 52, 736\u2013746 (2022)","journal-title":"IEEE Trans. Hum. Mach. Syst."},{"key":"2178_CR28","doi-asserted-by":"publisher","first-page":"782","DOI":"10.1080\/01621459.1993.10476339","volume":"88","author":"L Davies","year":"1993","unstructured":"L. Davies, U. Gather, The identification of multiple outliers. Publ. Am. Stat. Assoc. 88, 782\u2013792 (1993)","journal-title":"Publ. Am. Stat. Assoc."},{"key":"2178_CR29","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1080\/01621459.1974.10482962","volume":"69","author":"FR Hampel","year":"1974","unstructured":"F.R. Hampel, The influence curve and its role in robust estimation. J. Am. Stat. Assoc. 69, 383\u2013393 (1974)","journal-title":"J. Am. Stat. Assoc."},{"key":"2178_CR30","doi-asserted-by":"crossref","unstructured":"K. Ali, A.X. Liu, W. Wei et al., Keystroke recognition using WiFi signals, in The 21st Annual International Conference on Mobile Computing and Networking, 7\u201311 September 2015, Paris, France, pp. 90\u2013102 (2015)","DOI":"10.1145\/2789168.2790109"},{"key":"2178_CR31","doi-asserted-by":"publisher","first-page":"1118","DOI":"10.1109\/JSAC.2017.2679658","volume":"35","author":"W Wang","year":"2017","unstructured":"W. Wang, A.X. Liu, M. Shahzad et al., Device-free human activity recognition using commercial WiFi devices. IEEE J. Sel. Areas Commun. 35, 1118\u20131131 (2017)","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"2178_CR32","doi-asserted-by":"crossref","unstructured":"J. Liu, Y. Wang, Y. Chen et al., Tracking vital signs during sleep leveraging off-the-shelf WiFi. In, The 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing, 22\u201325 June 2015, Hangzhou, China, pp. 267\u2013276 (2015)","DOI":"10.1145\/2746285.2746303"},{"key":"2178_CR33","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1214\/aoms\/1177729694","volume":"22","author":"S Kullback","year":"1951","unstructured":"S. Kullback, R.A. Leibler, On information and sufficiency. Inst. Math. Stat. 22, 79\u201386 (1951)","journal-title":"Inst. Math. Stat."},{"key":"2178_CR34","doi-asserted-by":"publisher","first-page":"5268","DOI":"10.3390\/app9245268","volume":"9","author":"Z Akhtar","year":"2019","unstructured":"Z. Akhtar, H. Wang, WiFi-based gesture recognition for vehicular infotainment system\u2014an integrated approach. Appl. Sci. 9, 5268 (2019)","journal-title":"Appl. Sci."},{"key":"2178_CR35","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1080\/10485252.2018.1538450","volume":"31","author":"Z Chikr-Elmezouar","year":"2019","unstructured":"Z. Chikr-Elmezouar, I.M. Almanjahie, A. Laksaci et al., FDA: strong consistency of the KNN local linear estimation of the functional conditional density and mode. J. Nonparametr. Stat. 31, 175\u2013195 (2019)","journal-title":"J. Nonparametr. Stat."},{"key":"2178_CR36","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1016\/j.neucom.2015.12.012","volume":"179","author":"RC Guido","year":"2016","unstructured":"R.C. Guido, A tutorial on signal energy and its applications. Neurocomputing 179, 264\u2013282 (2016)","journal-title":"Neurocomputing"},{"key":"2178_CR37","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1016\/j.knosys.2016.05.011","volume":"105","author":"RC Guido","year":"2016","unstructured":"R.C. Guido, ZCR-aided neurocomputing: a study with applications. Knowl.-Based Syst. 105, 248\u2013269 (2016)","journal-title":"Knowl.-Based Syst."},{"key":"2178_CR38","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1016\/j.inffus.2017.09.006","volume":"41","author":"RC Guido","year":"2018","unstructured":"R.C. Guido, A tutorial-review on entropy-based handcrafted feature extraction for information fusion. Inf. Fus. 41, 161\u2013175 (2018)","journal-title":"Inf. Fus."},{"key":"2178_CR39","doi-asserted-by":"publisher","first-page":"2346","DOI":"10.1016\/j.jfranklin.2018.12.007","volume":"356","author":"RC Guido","year":"2019","unstructured":"R.C. Guido, Enhancing teager energy operator based on a novel and appealing concept: signal mass. J. Franklin Inst. 356, 2346\u20132352 (2019)","journal-title":"J. Franklin Inst."}],"container-title":["EURASIP Journal on Wireless Communications and Networking"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13638-022-02178-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13638-022-02178-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13638-022-02178-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,29]],"date-time":"2022-09-29T23:26:08Z","timestamp":1664493968000},"score":1,"resource":{"primary":{"URL":"https:\/\/jwcn-eurasipjournals.springeropen.com\/articles\/10.1186\/s13638-022-02178-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,30]]},"references-count":39,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["2178"],"URL":"https:\/\/doi.org\/10.1186\/s13638-022-02178-4","relation":{},"ISSN":["1687-1499"],"issn-type":[{"value":"1687-1499","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,30]]},"assertion":[{"value":"29 November 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 September 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 September 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"96"}}