{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:37:21Z","timestamp":1760236641821,"version":"build-2065373602"},"reference-count":21,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T00:00:00Z","timestamp":1639094400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents an ultra-low power hand gesture sensor using electrostatic induction for mobile devices. Two electrodes, which consist of electret foils stacked on metal sheets, are used to recognize two gestures such as hand movements from left to right and right to left. The hand gesture recognition is realized by detecting the electrostatic induction currents induced by hand movements. However, the electrostatic induction currents are significantly small; hence, a hand gesture recognition chip is first designed in this study to amplify and detect the small electrostatic induction currents with low power. This chip is fabricated in a commercial 180 nm complementary metal oxide semiconductor (CMOS) process, and the measurement results indicate that the fabricated gesture recognition chip consumes 406 nW, which is less than 1\/100th of the power dissipation of conventional gesture sensors.<\/jats:p>","DOI":"10.3390\/s21248268","type":"journal-article","created":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T08:17:58Z","timestamp":1639124278000},"page":"8268","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Ultra-Low Power Hand Gesture Sensor Using Electrostatic Induction"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0171-6679","authenticated-orcid":false,"given":"Hiroshi","family":"Fuketa","sequence":"first","affiliation":[{"name":"AI Chip Design Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki 305-8568, Japan"},{"name":"Device Technology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki 305-8568, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2000261","DOI":"10.1002\/advs.202000261","article-title":"Machine Learning Glove Using Self-Powered Conductive Superhydrophobic Triboelectric Textile for Gesture Recognition in VR\/AR Applications","volume":"7","author":"Wen","year":"2020","journal-title":"Adv. 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