{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T16:29:03Z","timestamp":1781886543240,"version":"3.54.5"},"reference-count":90,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T00:00:00Z","timestamp":1635811200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Union","doi-asserted-by":"publisher","award":["No 826655"],"award-info":[{"award-number":["No 826655"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009894","name":"Lodz University of Technology","doi-asserted-by":"publisher","award":["Internal University Grant"],"award-info":[{"award-number":["Internal University Grant"]}],"id":[{"id":"10.13039\/501100009894","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The increasing integration of technology in our daily lives demands the development of more convenient human\u2013computer interaction (HCI) methods. Most of the current hand-based HCI strategies exhibit various limitations, e.g., sensibility to variable lighting conditions and limitations on the operating environment. Further, the deployment of such systems is often not performed in resource-constrained contexts. Inspired by the MobileNetV1 deep learning network, this paper presents a novel hand gesture recognition system based on frequency-modulated continuous wave (FMCW) radar, exhibiting a higher recognition accuracy in comparison to the state-of-the-art systems. First of all, the paper introduces a method to simplify radar preprocessing while preserving the main information of the performed gestures. Then, a deep neural classifier with the novel Depthwise Expansion Module based on the depthwise separable convolutions is presented. The introduced classifier is optimized and deployed on the Coral Edge TPU board. The system defines and adopts eight different hand gestures performed by five users, offering a classification accuracy of 98.13% while operating in a low-power and resource-constrained environment.<\/jats:p>","DOI":"10.3390\/s21217298","type":"journal-article","created":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T22:17:23Z","timestamp":1635891443000},"page":"7298","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Highly-Optimized Radar-Based Gesture Recognition System with Depthwise Expansion Module"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8183-7042","authenticated-orcid":false,"given":"Mateusz","family":"Chmurski","sequence":"first","affiliation":[{"name":"Infineon Technologies AG, 85579 Neubiberg, Germany"},{"name":"Department of Microelectronics and Computer Science, Lodz University of Technology, 90924 Lodz, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3204-1555","authenticated-orcid":false,"given":"Gianfranco","family":"Mauro","sequence":"additional","affiliation":[{"name":"Infineon Technologies AG, 85579 Neubiberg, Germany"},{"name":"Department of Electronic and Computer Technology, University of Granada, Avenida de Fuente Nueva s\/n, 18071 Granada, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8156-3387","authenticated-orcid":false,"given":"Avik","family":"Santra","sequence":"additional","affiliation":[{"name":"Infineon Technologies AG, 85579 Neubiberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mariusz","family":"Zubert","sequence":"additional","affiliation":[{"name":"Department of Microelectronics and Computer Science, Lodz University of Technology, 90924 Lodz, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G\u00f6kberk","family":"Dagasan","sequence":"additional","affiliation":[{"name":"Infineon Technologies AG, 85579 Neubiberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,2]]},"reference":[{"key":"ref_1","unstructured":"Shehab, A.H., and Al-Janabi, S. 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