{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T04:46:02Z","timestamp":1778301962843,"version":"3.51.4"},"reference-count":38,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2021,6,23]],"date-time":"2021-06-23T00:00:00Z","timestamp":1624406400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"NSFC A3 Project","award":["62061146001"],"award-info":[{"award-number":["62061146001"]}]},{"name":"PKU-NTU collaboration Project"},{"name":"PKU-Baidu Funded Project","award":["2019BD005"],"award-info":[{"award-number":["2019BD005"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61802007,62022005,12071460"],"award-info":[{"award-number":["61802007,62022005,12071460"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2021,6,23]]},"abstract":"<jats:p>Gesture recognition on the back surface of mobile phone, not limited to the touch screen, is an enabling Human-Computer Interaction (HCI) mechanism which enriches the user interaction experiences. However, there are two main limitations in the existing Back-of-Device (BoD) gesture recognition systems. They can only handle coarse-grained gesture recognition such as tap detection and cannot avoid the air-borne propagation suffering from the interference in the air. In this paper, we propose StruGesture, a fine-grained gesture recognition system using the back of mobile phones with ultrasonic signals. The key technique is to use the structure-borne sounds (i.e., sound propagation via structure of the device) to recognize sliding gestures on the back of mobile phones. StruGesture can fully extract the structure-borne component from the hybrid Channel Impulse Response (CIR) based on Peak Selection Algorithm. We develop a deep adversarial learning architecture to learn the gesture-specific representation for robust and effective recognition. Extensive experiments are designed to evaluate the robustness over nine deployment scenarios. The results show that StruGesture outperforms the competitive state-of-the-art classifiers by achieving an average recognition accuracy of 99.5% over 10 gestures.<\/jats:p>","DOI":"10.1145\/3463522","type":"journal-article","created":{"date-parts":[[2021,6,24]],"date-time":"2021-06-24T16:29:19Z","timestamp":1624552159000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":38,"title":["Watching Your Phone's Back"],"prefix":"10.1145","volume":"5","author":[{"given":"Lei","family":"Wang","sequence":"first","affiliation":[{"name":"Peking University, China"}]},{"given":"Xiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of New South Wales, Australia and Harvard University, United States"}]},{"given":"Yuanshuang","family":"Jiang","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Advanced Technology, CAS, China"}]},{"given":"Yong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Advanced Technology, CAS, China"}]},{"given":"Chenren","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Electronics Engineering and Computer Science, Peking University, Beijing, China"}]},{"given":"Ruiyang","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Electronics Engineering and Computer Science, Peking University, Beijing, China"}]},{"given":"Daqing","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electronics Engineering and Computer Science, Peking University, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2021,6,24]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2015.7218525"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2789168.2790109"},{"key":"e_1_2_1_3_1","volume-title":"Proceedings of ACM UbiComp.","author":"Islam Aumi Md Tanvir","year":"2013","unstructured":"Md Tanvir Islam Aumi , Sidhant Gupta , Mayank Goel , Eric Larson , and Shwetak Patel . 2013 . 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