计算机科学技术学报 ›› 2023,Vol. 38 ›› Issue (1): 25-63.doi: 10.1007/s11390-023-3073-5

所属专题： 综述； Computer Networks and Distributed Computing

• • 上一篇    下一篇

基于WiFi和声波信号的泛在感知：原理、技术与应用

  

  • 收稿日期:2023-01-04 修回日期:2023-01-23 接受日期:2023-01-23 出版日期:2023-02-28 发布日期:2023-02-28

Ubiquitous WiFi and Acoustic Sensing: Principles, Technologies, and Applications

Jia-Ling Huang1,† (黄佳玲), Yun-Shu Wang1,† (王云舒), Yong-Pan Zou1,* (邹永攀), Member, CCF, ACM, IEEE, Kai-Shun Wu1 (伍楷舜), Fellow, IEEE, and Lionel Ming-shuan Ni2,3 (倪明选), Life Fellow, IEEE        

  1. 1 The IoT Research Center, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060 China
    2 The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511455, China
    3 The Hong Kong University of Science and Technology, Hong Kong, China
  • Received:2023-01-04 Revised:2023-01-23 Accepted:2023-01-23 Online:2023-02-28 Published:2023-02-28
  • Contact: Yong-Pan Zou E-mail:yongpan@szu.edu.cn
  • About author:Yong-Pan Zou received his Ph.D. degree in computer science and engineering from The Hong Kong University of Science and Technology, Hong Kong, in 2017. He is currently an associate professor in the College of Computer Science and Software Engineering, Shenzhen University, Shenzhen. His main research interests include intelligent sensing, ubiquitous computing, and HCI.
  • Supported by:
    This work is supported by the National Natural Science Foundation of China under Grant Nos. 62172286 and U2001207, the Natural Science Foundation of Guangdong Province of China under Grant Nos. 2022A1515011509 and 2017A030312008, and the Guangdong "Pearl River Talent Recruitment Program'' under Grant No. 2019ZT08X603.

PDF (PC)

74

补充材料

2

1、 背景：
随着手机、音响和可穿戴设备等智能终端的日益普及，基于各种感知媒介的智能感知技术引起了研究者的广泛关注。由于不同类型的传感介质中WiFi信号具有普适性突出、硬件成本近零、对光照、温度、湿度等环境条件鲁棒性强，声信号具有对环境变化更强的敏感性和适应性的优点。越来越多的研究人员开始关注基于WiFi和声学信号的新型传感技术，也涌现出了许多优秀的研究工作。
2、 目的：
为了让读者全面了解WiFi和声波感知的相关原理、技术和应用，增进读者对于该研究领域的兴趣与了解，本文对相关领域的研究工作进行了充分细致的调研和总结。
3、 方法：
本文按照WiFi和声波感知的背景、技术、应用、以及现有技术的局限和讨论可能的开放性课题四个方面对相关领域进行综述。在介绍WiFi和声学感知的各项应用时，本文围绕了数百项相关工作进行讨论。本文选择这些相关工作的标准是，它们是该领域近十年来最具代表性的论文。
4、 结果：
本文综合介绍了基于WiFi感知和声波感知的背景与相关技术如OFDM、RSI、CSSI、FMCW、CIR、Doppler Shift、MFCC、ranging、tracking等；并从行为识别与追踪、健康相关、定位、隐私安全四个应用方面分别展示了相关的工作，以及主要工作的核心内容、创新、性能及表现。
5、 结论：
随着无线信号(如WiFi、声学等)的普及，无线感知技术在人类行为识别等诸多领域有着广泛的应用。为了全面了解无线传感技术，本文仔细回顾了围绕WiFi和声信号感知的数百项相关工作。本文首先介绍了多径效应、OFDM、CSI等无线感知技术的基本原理，然后介绍了这些工作中用到的基本技术，最后展示了这些技术在不同应用领域中的应用。本文最后讨论了现有研究工作的局限性，并提出了一些有待进一步研究的问题。通过此综述，我们希望读者能对无线传感有一个整体的认识。

关键词: WiFi感知, 声波感知, 人机交互, 行为识别

Abstract: With the increasing pervasiveness of mobile devices such as smartphones, smart TVs, and wearables, smart sensing, transforming the physical world into digital information based on various sensing medias, has drawn researchers' great attention. Among different sensing medias, WiFi and acoustic signals stand out due to their ubiquity and zero hardware cost. Based on different basic principles, researchers have proposed different technologies for sensing applications with WiFi and acoustic signals covering human activity recognition, motion tracking, indoor localization, health monitoring, and the like. To enable readers to get a comprehensive understanding of ubiquitous wireless sensing, we conduct a survey of existing work to introduce their underlying principles, proposed technologies, and practical applications. Besides we also discuss some open issues of this research area. Our survey reals that as a promising research direction, WiFi and acoustic sensing technologies can bring about fancy applications, but still have limitations in hardware restriction, robustness, and applicability.

Key words: WiFi sensing, acoustic sensing, human-computer interaction, human activity recognition

<table class="reference-tab" style="background-color:#FFFFFF;width:914.104px;color:#333333;font-family:Calibri, Arial, 微软雅黑, "font-size:16px;"> <tbody> <tr class="document-box" id="b1"> <td valign="top" class="td1"> [1] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Bahl P, Padmanabhan V N. RADAR: An in-building RF-based user location and tracking system. In <i>Proc</i>. <i>the 19th</i><i> Annual Joint Conference of the IEEE Computer and Communications Societies</i>, Mar. 2000. DOI: <a href="https://doi.org/10.1109/INFCOM.2000.832252">10.1109/INFCOM.2000.832252</a>. </div> </td> </tr> <tr class="document-box" id="b2"> <td valign="top" class="td1"> [2] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Halperin D, Hu W J, Sheth A, Wetherall D. Tool release: Gathering 802.11n traces with channel state information. <i>ACM SIGCOMM Computer Communication Review</i>, 2011, 41(1): 53. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/1925861.1925870" target="_blank">10.1145/1925861.1925870</a>. </div> </td> </tr> <tr class="document-box" id="b3"> <td valign="top" class="td1"> [3] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Liu J, Wang Y, Chen Y Y, Yang J, Cheng J. Tracking vital signs during sleep leveraging off-the-shelf WiFi. In <i>Proc</i>. <i>the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing</i>, Jun. 2015, pp.267–276. DOI: <a href="https://doi.org/10.1145/2746285.2746303">10.1145/2746285.2746303</a>. </div> </td> </tr> <tr class="document-box" id="b4"> <td valign="top" class="td1"> [4] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Liu X F, Cao J N, Tang S J, Wen J Q. Wi-Sleep: Contactless sleep monitoring via WiFi signals. In <i>Proc</i>. <i>the 2014 IEEE Real-Time Systems Symposium</i>, Dec. 2014, pp.346–355. DOI: <a href="https://doi.org/10.1109/RTSS.2014.30">10.1109/RTSS.2014.30</a>. </div> </td> </tr> <tr class="document-box" id="b5"> <td valign="top" class="td1"> [5] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wu C S, Yang Z, Zhou Z M, Liu X F, Liu Y H, Cao J N. Non-invasive detection of moving and stationary human with WiFi. <i>IEEE Journal on Selected Areas in Communications</i>, 2015, 33(11): 2329–2342. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/JSAC.2015.2430294" target="_blank">10.1109/JSAC.2015.2430294</a>. </div> </td> </tr> <tr class="document-box" id="b6"> <td valign="top" class="td1"> [6] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Liu J, Chen Y Y, Wang Y, Chen X, Cheng J, Yang J. Monitoring vital signs and postures during sleep using WiFi signals. <i>IEEE Internet of Things Journal</i>, 2018, 5(3): 2071–2084. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/JIOT.2018.2822818" target="_blank">10.1109/JIOT.2018.2822818</a>. </div> </td> </tr> <tr class="document-box" id="b7"> <td valign="top" class="td1"> [7] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang X Y, Yang C, Mao S W. PhaseBeat: Exploiting CSI phase data for vital sign monitoring with commodity WiFi devices. In <i>Proc</i>. <i>the 37th IEEE International Conference on Distributed Computing Systems</i>, Jun. 2017, pp.1230–1239. DOI: <a href="https://doi.org/10.1109/ICDCS.2017.206">10.1109/ICDCS.2017.206</a>. </div> </td> </tr> <tr class="document-box" id="b8"> <td valign="top" class="td1"> [8] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang X Y, Yang C, Mao S W. On CSI-based vital sign monitoring using commodity WiFi. <i>ACM Trans. Computing for Healthcare</i>, 2020, 1(3): Article No. 12. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3377165" target="_blank">10.1145/3377165</a>. </div> </td> </tr> <tr class="document-box" id="b9"> <td valign="top" class="td1"> [9] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang Y X, Wu K S, Ni L M. WiFall: Device-free fall detection by wireless networks. <i>IEEE Trans. Mobile Computing</i>, 2017, 16(2): 581–594. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TMC.2016.2557792" target="_blank">10.1109/TMC.2016.2557792</a>. </div> </td> </tr> <tr class="document-box" id="b10"> <td valign="top" class="td1"> [10] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang H, Zhang D Q, Wang Y S, Ma J Y, Wang Y X, Li S J. RT-Fall: A real-time and contactless fall detection system with commodity WiFi devices. <i>IEEE Trans. Mobile Computing</i>, 2017, 16(2): 511–526. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TMC.2016.2557795" target="_blank">10.1109/TMC.2016.2557795</a>. </div> </td> </tr> <tr class="document-box" id="b11"> <td valign="top" class="td1"> [11] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zhang L, Wang Z R, Yang L. Commercial Wi-Fi based fall detection with environment influence mitigation. In <i>Proc</i>. <i>the 16th Annual IEEE International Conference on Sensing</i>, <i>Communication</i>, <i>and Networking (SECON)</i>, Jun. 2019. DOI: <a href="https://doi.org/10.1109/SAHCN.2019.8824989">10.1109/SAHCN.2019.8824989</a>. </div> </td> </tr> <tr class="document-box" id="b12"> <td valign="top" class="td1"> [12] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Palipana S, Rojas D, Agrawal P, Pesch D. FallDeFi: Ubiquitous fall detection using commodity Wi-Fi devices. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2018, 1(4): Article No. 155. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3161183" target="_blank">10.1145/3161183</a>. </div> </td> </tr> <tr class="document-box" id="b13"> <td valign="top" class="td1"> [13] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Hu Y Q, Zhang F, Wu C S, Wang B B, Liu K J R. DeFall: Environment-independent passive fall detection using WiFi. <i>IEEE Internet of Things Journal</i>, 2022, 9(11): 8515–8530. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/JIOT.2021.3116136" target="_blank">10.1109/JIOT.2021.3116136</a>. </div> </td> </tr> <tr class="document-box" id="b14"> <td valign="top" class="td1"> [14] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Chen S, Yang W, Yang X, Geng Y Y, Xin B Z, Huang L S. AFall: Wi-Fi-based device-free fall detection system using spatial angle of arrival. <i>IEEE Trans</i>. <i>Mobile Computing</i>, 2022. DOI: <a href="https://doi.org/10.1109/TMC.2022.3157666">10.1109/TMC.2022.3157666</a>. </div> </td> </tr> <tr class="document-box" id="b15"> <td valign="top" class="td1"> [15] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Ji S J, Xie Y X, Li M. SiFall: Practical online fall detection with RF sensing. arXiv: 2301.03773, 2023. <a href="https://arxiv.org/abs/2301.03773">https://arxiv.org/abs/2301.03773</a>, Jan. 2023. </div> </td> </tr> <tr class="document-box" id="b16"> <td valign="top" class="td1"> [16] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Yang Z, Zhang Y, Zhang Q. Rethinking fall detection with Wi-Fi. <i>IEEE Trans</i>. <i>Mobile Computing</i>, 2022. DOI: <a href="https://doi.org/10.1109/TMC.2022.3188779">10.1109/TMC.2022.3188779</a>. </div> </td> </tr> <tr class="document-box" id="b17"> <td valign="top" class="td1"> [17] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang Y C, Yang S, Li F, Wu Y, Wang Y. FallViewer: A fine-grained indoor fall detection system with ubiquitous Wi-Fi devices. <i>IEEE Internet of Things Journal</i>, 2021, 8(15): 12455–12466. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/JIOT.2021.3063531" target="_blank">10.1109/JIOT.2021.3063531</a>. </div> </td> </tr> <tr class="document-box" id="b18"> <td valign="top" class="td1"> [18] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Ali K, Liu A X, Wang W, Shahzad M. Keystroke recognition using WiFi signals. In <i>Proc</i>. <i>the 21st Annual Int. Conf. Mobile Computing and Networking</i>, Sept. 2015, pp.90–102. DOI: <a href="https://doi.org/10.1145/2789168.2790109">10.1145/2789168.2790109</a>. </div> </td> </tr> <tr class="document-box" id="b19"> <td valign="top" class="td1"> [19] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Ouyang Z, Srinivasan K. Mudra: User-friendly fine-grained gesture recognition using WiFi signals. In <i>Proc</i>. <i>the 12th International Conference on Emerging Networking EXperiments and Technologies</i>, Dec. 2016, pp.83–96. DOI: <a href="https://doi.org/10.1145/2999572.2999582">10.1145/2999572.2999582.</a> </div> </td> </tr> <tr class="document-box" id="b20"> <td valign="top" class="td1"> [20] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> He W F, Wu K S, Zou Y P, Ming Z. WiG: WiFi-based gesture recognition system. In <i>Proc</i>. <i>the 24th International Conference on Computer Communication and Networks (ICCCN)</i>, Aug. 2015. DOI: <a href="https://doi.org/10.1109/ICCCN.2015.7288485">10.1109/ICCCN.2015.7288485</a>. </div> </td> </tr> <tr class="document-box" id="b21"> <td valign="top" class="td1"> [21] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zhang Y, Zheng Y, Qian K, Zhang G D, Liu Y H, Wu C S, Yang Z. Widar3.0: Zero-effort cross-domain gesture recognition with Wi-Fi. <i>IEEE Trans. Pattern Analysis and Machine Intelligence</i>, 2022, 44(11): 8671–8688. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TPAMI.2021.3105387" target="_blank">10.1109/TPAMI.2021.3105387</a>. </div> </td> </tr> <tr class="document-box" id="b22"> <td valign="top" class="td1"> [22] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Venkatnarayan R H, Mahmood S, Shahzad M. WiFi based multi-user gesture recognition. <i>IEEE Trans. Mobile Computing</i>, 2021, 20(3): 1242–1256. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TMC.2019.2954891" target="_blank">10.1109/TMC.2019.2954891</a>. </div> </td> </tr> <tr class="document-box" id="b23"> <td valign="top" class="td1"> [23] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Li C N, Liu M N, Cao Z C. WiHF: Gesture and user recognition with WiFi. <i>IEEE Trans. Mobile Computing</i>, 2022, 21(2): 757–768. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TMC.2020.3009561" target="_blank">10.1109/TMC.2020.3009561</a>. </div> </td> </tr> <tr class="document-box" id="b24"> <td valign="top" class="td1"> [24] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Tan S, Yang J, Chen Y Y. Enabling fine-grained finger gesture recognition on commodity WiFi devices. <i>IEEE Trans. Mobile Computing</i>, 2022, 21(8): 2789–2802. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TMC.2020.3045635" target="_blank">10.1109/TMC.2020.3045635</a>. </div> </td> </tr> <tr class="document-box" id="b25"> <td valign="top" class="td1"> [25] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Niu K, Zhang F S, Wang X Z, Lv Q, Luo H T, Zhang D Q. Understanding WiFi signal frequency features for position-independent gesture sensing. <i>IEEE Trans. Mobile Computing</i>, 2021, 21(11): 4156–4171. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TMC.2021.3063135" target="_blank">10.1109/TMC.2021.3063135</a>. </div> </td> </tr> <tr class="document-box" id="b26"> <td valign="top" class="td1"> [26] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Xiao R, Liu J W, Han J S, Ren K. OneFi: One-shot recognition for unseen gesture via COTS WiFi. In <i>Proc</i>. <i>the 19th ACM Conference on Embedded Networked Sensor Systems</i>, Nov. 2021, pp.206–219. DOI: <a href="https://doi.org/10.1145/3485730.3485936">10.1145/3485730.3485936</a>. </div> </td> </tr> <tr class="document-box" id="b27"> <td valign="top" class="td1"> [27] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Gao R Y, Li W W, Xie Y X, Yi E Z, Wang L Y, Wu D, Zhang D Q. Towards robust gesture recognition by characterizing the sensing quality of WiFi signals. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2022, 6(1): Article No. 11. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3517241" target="_blank">10.1145/3517241</a>. </div> </td> </tr> <tr class="document-box" id="b28"> <td valign="top" class="td1"> [28] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zhou Y X, Chen H X, Huang C Y, Zhang Q. WiADv: Practical and robust adversarial attack against WiFi-based gesture recognition system. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2022, 6(2): Article No. 92. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3534618" target="_blank">10.1145/3534618</a>. </div> </td> </tr> <tr class="document-box" id="b29"> <td valign="top" class="td1"> [29] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wu D, Gao R Y, Zeng Y W, Liu J Y, Wang L Y, Gu T, Zhang D Q. FingerDraw: Sub-wavelength level finger motion tracking with WiFi signals. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2020, 4(1): Article No. 31. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3380981" target="_blank">10.1145/3380981</a>. </div> </td> </tr> <tr class="document-box" id="b30"> <td valign="top" class="td1"> [30] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Sun L, Sen S, Koutsonikolas D, Kim K H. WiDraw: Enabling hands-free drawing in the air on commodity WiFi devices. In <i>Proc</i>. <i>the 21st Annual International Conference on Mobile Computing and Networking</i>, Sept. 2015, pp.77–89. DOI: <a href="https://doi.org/10.1145/2789168.2790129">10.1145/2789168.2790129</a>. </div> </td> </tr> <tr class="document-box" id="b31"> <td valign="top" class="td1"> [31] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Hernandez S M, Bulut E. Performing WiFi sensing with off-the-shelf smartphones. In <i>Proc</i>. <i>the 2020 IEEE Int. Conf. Pervasive Computing and Communications Workshops (PerCom Workshops)</i>, Mar. 2020. DOI: <a href="https://doi.org/10.1109/PerComWorkshops48775.2020.9156194">10.1109/PerComWorkshops48775.2020.9156194</a>. </div> </td> </tr> <tr class="document-box" id="b32"> <td valign="top" class="td1"> [32] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zeng Y W, Wu D, Xiong J, Yi E Z, Gao R Y, Zhang D Q. FarSense: Pushing the range limit of WiFi-based respiration sensing with CSI ratio of two antennas. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2019, 3(3): Article No. 121. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3351279" target="_blank">10.1145/3351279</a>. </div> </td> </tr> <tr class="document-box" id="b33"> <td valign="top" class="td1"> [33] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang G H, Zou Y P, Zhou Z M, Wu K S, Ni L M. We can hear you with Wi-Fi! In <i>Proc</i>. <i>the 20th ACM Annual International Conference on Mobile Computing and Networking (MobiCom)</i>, Sept. 2014, pp.593–604. DOI: <a href="https://doi.org/10.1145/2639108.2639112">10.1145/2639108.2639112</a>. </div> </td> </tr> <tr class="document-box" id="b34"> <td valign="top" class="td1"> [34] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Du C L, Yuan X Q, Lou W J, Hou Y T. Context-free fine-grained motion sensing using WiFi. In <i>Proc</i>. <i>the 15th Annual IEEE International Conference on Sensing</i>, <i>Communication</i>, <i>and Networking (SECON)</i>, Jun. 2018. DOI: <a href="https://doi.org/10.1109/SAHCN.2018.8397118">10.1109/SAHCN.2018.8397118</a>. </div> </td> </tr> <tr class="document-box" id="b35"> <td valign="top" class="td1"> [35] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Guo X N, Liu B, Shi C, Liu H B, Chen Y Y, Chuah M C. WiFi-enabled smart human dynamics monitoring. In <i>Proc. the 15th ACM Conference on Embedded Network Sensor Systems</i>, Nov. 2017, Article No. 16. DOI: <a href="https://doi.org/10.1145/3131672.3131692">10.1145/3131672.3131692</a>. </div> </td> </tr> <tr class="document-box" id="b36"> <td valign="top" class="td1"> [36] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Xi W, Zhao J Z, Li X Y, Zhao K, Tang S J, Liu X, Jiang Z P. Electronic frog eye: Counting crowd using WiFi. In <i>Proc. the 2014 IEEE Conference on Computer Communications</i>, Apr. 27–May 2, 2014, pp.361–369. DOI: <a href="https://doi.org/10.1109/INFOCOM.2014.6847958">10.1109/INFOCOM.2014.6847958</a>. </div> </td> </tr> <tr class="document-box" id="b37"> <td valign="top" class="td1"> [37] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zou H, Zhou Y X, Yang J F, Jiang H, Xie L H, Spanos C J. DeepSense: Device-free human activity recognition via autoencoder long-term recurrent convolutional network. In <i>Proc</i>. <i>the 2018 IEEE International Conference on Communications (ICC 2018)</i>, May 2018. DOI: <a href="https://doi.org/10.1109/ICC.2018.8422895">10.1109/ICC.2018.8422895</a>. </div> </td> </tr> <tr class="document-box" id="b38"> <td valign="top" class="td1"> [38] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Jiang W J, Miao C L, Ma F L, Yao S C, Wang Y Q, Yuan Y, Xue H F, Song C, Ma X, Koutsonikolas D, Xu W Y, Su L. Towards environment independent device free human activity recognition. In <i>Proc</i>. <i>the 24th Annual Int. Conf. Mobile Computing and Networking</i>, Oct. 2018, pp.289–304. DOI: <a href="https://doi.org/10.1145/3241539.3241548">10.1145/3241539.3241548</a>. </div> </td> </tr> <tr class="document-box" id="b39"> <td valign="top" class="td1"> [39] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Xue H F, Jiang W J, Miao C L, Ma F L, Wang S Y, Yuan Y, Yao S C, Zhang A D, Su L. DeepMV: Multi-view deep learning for device-free human activity recognition. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2020, 4(1): Article No. 34. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3380980" target="_blank">10.1145/3380980</a>. </div> </td> </tr> <tr class="document-box" id="b40"> <td valign="top" class="td1"> [40] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Chen Z H, Zhang L, Jiang C Y, Cao Z G, Cui W. WiFi CSI based passive human activity recognition using attention based BLSTM. <i>IEEE Trans. Mobile Computing</i>, 2018, 18(11): 2714–2724. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TMC.2018.2878233" target="_blank">10.1109/TMC.2018.2878233</a>. </div> </td> </tr> <tr class="document-box" id="b41"> <td valign="top" class="td1"> [41] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang W, Liu A X, Shahzad M, Ling K, Lu S L. Understanding and modeling of WiFi signal based human activity recognition. In <i>Proc</i>. <i>the 21st Annual International Conference on Mobile Computing and Networking</i>, Sept. 2015, pp.65–76. DOI: <a href="https://doi.org/10.1145/2789168.2790093">10.1145/2789168.2790093</a>. </div> </td> </tr> <tr class="document-box" id="b42"> <td valign="top" class="td1"> [42] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zhang F, Wu C S, Wang B B, Lai H Q, Han Y, Liu K J R. WiDetect: Robust motion detection with a statistical electromagnetic model. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2019, 3(3): Article No. 122. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3351280" target="_blank">10.1145/3351280</a>. </div> </td> </tr> <tr class="document-box" id="b43"> <td valign="top" class="td1"> [43] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang W, Liu A X, Shahzad M, Ling K, Lu S L. Understanding and modeling of WiFi signal based human activity recognition. In <i>Proc</i>. <i>the 21st Annual International Conference on Mobile Computing and Networking</i>, Sept. 2015, pp.65–76. DOI: <a href="https://doi.org/10.1145/2789168.2790093.">10.1145/2789168.2790093.</a> </div> </td> </tr> <tr class="document-box" id="b44"> <td valign="top" class="td1"> [44] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Li S J, Liu Z P, Zhang Y, Lv Q, Niu X P, Wang L Y, Zhang D Q. WiBorder: Precise Wi-Fi based boundary sensing via through-wall discrimination. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2020, 4(3): Article No. 89. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3411834" target="_blank">10.1145/3411834</a>. </div> </td> </tr> <tr class="document-box" id="b45"> <td valign="top" class="td1"> [45] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Li H J, He X, Chen X K, Fang Y Y, Fang Q. Wi-Motion: A robust human activity recognition using WiFi signals. <i>IEEE Access</i>, 2019, 7: 153287–153299. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/ACCESS.2019.2948102" target="_blank">10.1109/ACCESS.2019.2948102</a>. </div> </td> </tr> <tr class="document-box" id="b46"> <td valign="top" class="td1"> [46] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Pu Q, Gupta S, Gollakota S, Patel S. Whole-home gesture recognition using wireless signals. In <i>Proc</i>. <i>the 19th Annual International Conference on Mobile Computing & Networking</i>, Sept. 2013, pp.27–38. DOI: <a href="https://doi.org/10.1145/2500423.2500436">10.1145/2500423.2500436</a>. </div> </td> </tr> <tr class="document-box" id="b47"> <td valign="top" class="td1"> [47] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zheng X L, Wang J L, Shangguan L F, Zhou Z M, Liu Y H. Smokey: Ubiquitous smoking detection with commercial WiFi infrastructures. In <i>Proc</i>. <i>the 35th Annual IEEE Int. Conf. Computer Communications</i>, Apr. 2016. DOI: <a href="https://doi.org/10.1109/INFOCOM.2016.7524399">10.1109/INFOCOM.2016.7524399</a>. </div> </td> </tr> <tr class="document-box" id="b48"> <td valign="top" class="td1"> [48] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wu X H, Chu Z B, Yang P L, Xiang C C, Zheng X, Huang W C. TW-See: Human activity recognition through the wall with commodity Wi-Fi devices. <i>IEEE Trans. Vehicular Technology</i>, 2019, 68(1): 306–319. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TVT.2018.2878754" target="_blank">10.1109/TVT.2018.2878754</a>. </div> </td> </tr> <tr class="document-box" id="b49"> <td valign="top" class="td1"> [49] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang H, Zhang D Q, Ma J Y, Wang Y S, Wang Y X, Wu D, Gu T, Xie B. Human respiration detection with commodity WiFi devices: Do user location and body orientation matter? In <i>Proc</i>. <i>the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing</i>, Sept. 2016, pp.25–36. DOI: <a href="https://doi.org/10.1145/2971648.2971744">10.1145/2971648.2971744</a>. </div> </td> </tr> <tr class="document-box" id="b50"> <td valign="top" class="td1"> [50] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Liu J Y, Zeng Y W, Gu T, Wang L Y, Zhang D Q. WiPhone: Smartphone-based respiration monitoring using ambient reflected WiFi signals. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2021, 5(1): Article No. 23. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3448092" target="_blank">10.1145/3448092</a>. </div> </td> </tr> <tr class="document-box" id="b51"> <td valign="top" class="td1"> [51] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Yin Y Q, Yang X, Xiong J, Lee S I, Chen P P, Niu Q. Ubiquitous smartphone-based respiration sensing with Wi-Fi signal. <i>IEEE Internet of Things Journal</i>, 2022, 9(2): 1479–1490. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/JIOT.2021.3088338" target="_blank">10.1109/JIOT.2021.3088338</a>. </div> </td> </tr> <tr class="document-box" id="b52"> <td valign="top" class="td1"> [52] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Korany B, Karanam C R, Cai H, Mostofi Y. XModal-ID: Using WiFi for through-wall person identification from candidate video footage. In <i>Proc</i>. <i>the 25th Annual Int. Conf. Mobile Computing and Networking</i>, Aug. 2019, Article No. 36. DOI: <a href="https://doi.org/10.1145/3300061.3345437">10.1145/3300061.3345437</a>. </div> </td> </tr> <tr class="document-box" id="b53"> <td valign="top" class="td1"> [53] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zeng Y Z, Pathak P H, Mohapatra P. WiWho: WiFi-based person identification in smart spaces. In <i>Proc</i>. <i>the 15th ACM/IEEE International Conference on Information Processing in Sensor Networks</i>, Apr. 2016. DOI: <a href="https://doi.org/10.1109/IPSN.2016.7460727">10.1109/IPSN.2016.7460727</a>. </div> </td> </tr> <tr class="document-box" id="b54"> <td valign="top" class="td1"> [54] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zhang J, Wei B, Hu W, Kanhere S S. WiFi-ID: Human identification using WiFi signal. In <i>Proc</i>. <i>the 2016 Int. Conf. Distributed Computing in Sensor Systems</i>, May 2016, pp.75–82. DOI: <a href="https://doi.org/10.1109/DCOSS.2016.30">10.1109/DCOSS.2016.30</a>. </div> </td> </tr> <tr class="document-box" id="b55"> <td valign="top" class="td1"> [55] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Xu Y, Yang W, Wang J X, Zhou X, Li H, Huang L S. WiStep: Device-free step counting with WiFi signals. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2018, 1(4): Article No. 172. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3161415" target="_blank">10.1145/3161415</a>. </div> </td> </tr> <tr class="document-box" id="b56"> <td valign="top" class="td1"> [56] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Li X, Li S J, Zhang D Q, Xiong J, Wang Y S, Mei H. Dynamic-MUSIC: Accurate device-free indoor localization. In <i>Proc</i>. <i>the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing</i>, Sept. 2016, pp.196–207. DOI: <a href="https://doi.org/10.1145/2971648.2971665">10.1145/2971648.2971665</a>. </div> </td> </tr> <tr class="document-box" id="b57"> <td valign="top" class="td1"> [57] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Qian K, Wu C S, Yang Z, Liu Y H, Jamieson K. Widar: Decimeter-level passive tracking via velocity monitoring with commodity Wi-Fi. In <i>Proc</i>. <i>the 18th ACM International Symposium on Mobile Ad Hoc Networking and Computing</i>, Jul. 2017, Article No. 6. DOI: <a href="https://doi.org/10.1145/3084041.3084067">10.1145/3084041.3084067</a>. </div> </td> </tr> <tr class="document-box" id="b58"> <td valign="top" class="td1"> [58] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Qian K, Wu C S, Zhang Y, Zhang G D, Yang Z, Liu Y H. Widar2.0: Passive human tracking with a single Wi-Fi link. In <i>Proc</i>. <i>the 16th Annual International Conference on Mobile Systems</i>, <i>Applications</i>, <i>and Services</i>, Jun. 2018, pp.350–361. DOI: <a href="https://doi.org/10.1145/3210240.3210314">10.1145/3210240.3210314</a>. </div> </td> </tr> <tr class="document-box" id="b59"> <td valign="top" class="td1"> [59] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Xie Y X, Xiong J, Li M, Jamieson K. mD-Track: Leveraging multi-dimensionality for passive indoor Wi-Fi tracking. In <i>Proc</i>. <i>the 25th Annual International Conference on Mobile Computing and Networking</i>, Aug. 2019, Article No. 8. DOI: <a href="https://doi.org/10.1145/3300061.3300133">10.1145/3300061.3300133</a>. </div> </td> </tr> <tr class="document-box" id="b60"> <td valign="top" class="td1"> [60] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Abdel-Nasser H, Samir R, Sabek I, Youssef M. MonoPHY: Mono-stream-based device-free WLAN localization via physical layer information. In <i>Proc</i>. <i>the 2013 IEEE Wireless Communications and Networking Conference</i>, Apr. 2013, pp.4546–4551. DOI: <a href="https://doi.org/10.1109/WCNC.2013.6555311">10.1109/WCNC.2013.6555311</a>. </div> </td> </tr> <tr class="document-box" id="b61"> <td valign="top" class="td1"> [61] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang X Y, Gao L J, Mao S W, Pandey S. DeepFi: Deep learning for indoor fingerprinting using channel state information. In <i>Proc</i>. <i>the 2015 IEEE Wireless Communications and Networking Conference (WCNC)</i>, Mar. 2015, pp.1666–1671. DOI: <a href="https://doi.org/10.1109/WCNC.2015.7127718">10.1109/WCNC.2015.7127718</a>. </div> </td> </tr> <tr class="document-box" id="b62"> <td valign="top" class="td1"> [62] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Li H, Chen X, Wang J, Wu D, Liu X. DAFI: WiFi-based device-free indoor localization via domain adaptation. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2021, 5(4): Article No. 167. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3494954" target="_blank">10.1145/3494954</a>. </div> </td> </tr> <tr class="document-box" id="b63"> <td valign="top" class="td1"> [63] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Alkandari M, Basu D, Hasan S F. A Wi-Fi based passive technique for speed estimation in indoor environments. In <i>Proc</i>. <i>the 2nd Workshop on Recent Trends in Telecommunications Research</i>, Feb. 2017. DOI: <a href="https://doi.org/10.1109/RTTR.2017.7887877">10.1109/RTTR.2017.7887877</a>. </div> </td> </tr> <tr class="document-box" id="b64"> <td valign="top" class="td1"> [64] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Basu D, Hasan S F. Assessing device-free passive localization with a single access point. In <i>Proc</i>. <i>the 14th International Conference on Dependable, Autonomic and Secure Computing, 14th International Conference on Pervasive Intelligence and Computing, 2nd International Conference on Big Data Intelligence and Computing and Cyber Science and Technology Congress</i>, Aug. 2016, pp.493–496. DOI: <a href="https://doi.org/10.1109/DASC-PICom-DataCom-CyberSciTec.2016.96">10.1109/DASC-PICom-DataCom-CyberSciTec.2016.96</a>. </div> </td> </tr> <tr class="document-box" id="b65"> <td valign="top" class="td1"> [65] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Oguntala G, Obeidat H, Al Khambashi M, Elmegri F, Abd-Alhameed R A, Yuxiang T, Noras J. Design framework for unobtrusive patient location recognition using passive RFID and particle filtering. In <i>Proc</i>. <i>the 2017 Internet Technologies and Applications</i>, Sept. 2017, pp.212–217. DOI: <a href="https://doi.org/10.1109/ITECHA.2017.8101941">10.1109/ITECHA.2017.8101941</a>. </div> </td> </tr> <tr class="document-box" id="b66"> <td valign="top" class="td1"> [66] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Xiao J, Wu K S, Yi Y W, Wang L, Ni L M. FIMD: Fine-grained device-free motion detection. In <i>Proc</i>. <i>the 18th</i> <i>IEEE International Conference on Parallel and Distributed Systems</i>, Dec. 2012, pp.229–235. DOI: <a href="https://doi.org/10.1109/ICPADS.2012.40">10.1109/ICPADS.2012.40</a>. </div> </td> </tr> <tr class="document-box" id="b67"> <td valign="top" class="td1"> [67] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wu K S, Xiao J, Yi Y W, Gao M, Ni L M. FILA: Fine-grained indoor localization. In <i>Proc</i>. <i>the 2012 IEEE INFOCOM</i>, Mar. 2012, pp.2210–2218. DOI: <a href="https://doi.org/10.1109/INFCOM.2012.6195606">10.1109/INFCOM.2012.6195606</a>. </div> </td> </tr> <tr class="document-box" id="b68"> <td valign="top" class="td1"> [68] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Jiang G Y, Li M L, Liu X J, Liu W P, Jia Y F, Jiang H B, Lei J L, Xiao F, Zhang K. WiDE: WiFi distance based group profiling via machine learning. <i>IEEE Trans. Mobile Computing</i>, 2023, 22(1): 607–620. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TMC.2021.3073848" target="_blank">10.1109/TMC.2021.3073848</a>. </div> </td> </tr> <tr class="document-box" id="b69"> <td valign="top" class="td1"> [69] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Chen X, Li H, Zhou C Y, Liu X, Wu D, Dudek G. Fidora: Robust WiFi-based indoor localization via unsupervised domain adaptation. <i>IEEE Internet of Things Journal</i>, 2022, 9(12): 9872–9888. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/JIOT.2022.3163391" target="_blank">10.1109/JIOT.2022.3163391</a>. </div> </td> </tr> <tr class="document-box" id="b70"> <td valign="top" class="td1"> [70] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Bai Y H, Wang Z J, Zheng K Y, Wang X R, Wang J M. WiDrive: Adaptive WiFi-based recognition of driver activity for real-time and safe takeover. In <i>Proc</i>. <i>the 39th IEEE Int. Conf. Distributed Computing Systems</i>, Jul. 2019, pp.901–911. DOI: <a href="https://doi.org/10.1109/ICDCS.2019.00094">10.1109/ICDCS.2019.00094</a>. </div> </td> </tr> <tr class="document-box" id="b71"> <td valign="top" class="td1"> [71] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Peng H J, Jia W J. WiFind: Driver fatigue detection with fine-grained Wi-Fi signal features. In <i>Proc</i>. <i>the 2017 IEEE Global Communications Conference</i>, Dec. 2017. DOI: <a href="https://doi.org/10.1109/GLOCOM.2017.8253925">10.1109/GLOCOM.2017.8253925</a>. </div> </td> </tr> <tr class="document-box" id="b72"> <td valign="top" class="td1"> [72] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Kong H, Lu L, Yu J D, Chen Y Y, Kong L H, Li M L. FingerPass: Finger gesture-based continuous user authentication for smart homes using commodity WiFi. In <i>Proc</i>. <i>the 20th ACM International Symposium on Mobile Ad Hoc Networking and Computing</i>, Jul. 2019, pp.201–210. DOI: <a href="https://doi.org/10.1145/3323679.3326518">10.1145/3323679.3326518</a>. </div> </td> </tr> <tr class="document-box" id="b73"> <td valign="top" class="td1"> [73] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Lu H, Pan W, Lane N D, Choudhury T, Campbell A T. SoundSense: Scalable sound sensing for people-centric applications on mobile phones. In <i>Proc</i>. <i>the 7th Int. Conf. Mobile Systems</i>, <i>Applications</i>, <i>and Services</i>, Jun. 2009, pp.165–178. DOI: <a href="https://doi.org/10.1145/1555816.1555834">10.1145/1555816.1555834</a>. </div> </td> </tr> <tr class="document-box" id="b74"> <td valign="top" class="td1"> [74] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Yatani K, Truong K N. BodyScope: A wearable acoustic sensor for activity recognition. In <i>Proc</i>. <i>the 2012 ACM Conference on Ubiquitous Computing</i>, Sept. 2012, pp.341–350. DOI: <a href="https://doi.org/10.1145/2370216.2370269">10.1145/2370216.2370269</a>. </div> </td> </tr> <tr class="document-box" id="b75"> <td valign="top" class="td1"> [75] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Prakash J, Yang Z J, Wei Y L, Hassanieh H, Choudhury R R. EarSense: Earphones as a teeth activity sensor. In <i>Proc</i>. <i>the 26th Annual International Conference on Mobile Computing and Networking</i>, Apr. 2020, Article No. 40. DOI: <a href="https://doi.org/10.1145/3372224.3419197">10.1145/3372224.3419197</a>. </div> </td> </tr> <tr class="document-box" id="b76"> <td valign="top" class="td1"> [76] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Xie Y D, Li F, Wu Y, Wang Y. HearFit: Fitness monitoring on smart speakers via active acoustic sensing. In <i>Proc</i>. <i>the 2021 IEEE Conference on Computer Communications</i>, May 2021. DOI: <a href="https://doi.org/10.1109/INFOCOM42981.2021.9488811">10.1109/INFOCOM42981.2021.9488811</a>. </div> </td> </tr> <tr class="document-box" id="b77"> <td valign="top" class="td1"> [77] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Liang D W, Thomaz E. Audio-based activities of daily living (ADL) recognition with large-scale acoustic embeddings from online videos. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2019, 3(1): Article No. 17. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3314404" target="_blank">10.1145/3314404</a>. </div> </td> </tr> <tr class="document-box" id="b78"> <td valign="top" class="td1"> [78] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Nicolaou P, Efstratiou C. Tracking daily routines of elderly users through acoustic sensing: An unsupervised learning approach. In <i>Proc</i>. <i>the 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and Other Affiliated Events (PerCom Workshops)</i>, Mar. 2022, pp.391–396. DOI: <a href="https://doi.org/10.1109/PerComWorkshops53856.2022.9767404">10.1109/PerComWorkshops53856.2022.9767404</a>. </div> </td> </tr> <tr class="document-box" id="b79"> <td valign="top" class="td1"> [79] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Aumi M T I, Gupta S, Goel M, Larson E, Patel S. DopLink: Using the Doppler effect for multi-device interaction. In <i>Proc</i>. <i>the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing</i>, Sept. 2013, pp.583–586. DOI: <a href="https://doi.org/10.1145/2493432.2493515">10.1145/2493432.2493515</a>. </div> </td> </tr> <tr class="document-box" id="b80"> <td valign="top" class="td1"> [80] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Yang Q F, Tang H, Zhao X B, Li Y, Zhang S F. Dolphin: Ultrasonic-based gesture recognition on smartphone platform. In <i>Proc</i>. <i>the 17th IEEE International Conference on Computational Science and Engineering</i>, Dec. 2014, pp.1461–1468. DOI: <a href="https://doi.org/10.1109/CSE.2014.273">10.1109/CSE.2014.273</a>. </div> </td> </tr> <tr class="document-box" id="b81"> <td valign="top" class="td1"> [81] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Sun K, Zhao T, Wang W, Xie L. VSkin: Sensing touch gestures on surfaces of mobile devices using acoustic signals. In <i>Proc</i>. <i>the 24th Annual International Conference on Mobile Computing and Networking</i>, Oct. 2018, pp.591–605. DOI: <a href="https://doi.org/10.1145/3241539.3241568">10.1145/3241539.3241568</a>. </div> </td> </tr> <tr class="document-box" id="b82"> <td valign="top" class="td1"> [82] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zhang Y T, Wang J L, Wang W Y, Wang Z, Liu Y H. Vernier: Accurate and fast acoustic motion tracking using mobile devices. In <i>Proc</i>. <i>the 2018 IEEE Conference on Computer Communications</i>, Apr. 2018, pp.1709–1717. DOI: <a href="https://doi.org/10.1109/INFOCOM.2018.8486365">10.1109/INFOCOM.2018.8486365</a>. </div> </td> </tr> <tr class="document-box" id="b83"> <td valign="top" class="td1"> [83] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Luo G, Chen M S, Li P, Zhang M T, Yang P L. SoundWrite II: Ambient acoustic sensing for noise tolerant device-free gesture recognition. In <i>Proc</i>. <i>the 23rd IEEE International Conference on Parallel and Distributed Systems (ICPADS)</i>, Dec. 2017, pp.121–126. DOI: <a href="https://doi.org/10.1109/ICPADS.2017.00027">10.1109/ICPADS.2017.00027</a>. </div> </td> </tr> <tr class="document-box" id="b84"> <td valign="top" class="td1"> [84] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang W, Liu A X, Sun K. Device-free gesture tracking using acoustic signals. In <i>Proc</i>. <i>the 22nd Annual International Conference on Mobile Computing and Networking</i>, Oct. 2016, pp.82–94. DOI: <a href="https://doi.org/10.1145/2973750.2973764">10.1145/2973750.2973764</a>. </div> </td> </tr> <tr class="document-box" id="b85"> <td valign="top" class="td1"> [85] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Ling K, Dai H P, Liu Y T, Liu A X, Wang W, Gu Q. UltraGesture: Fine-grained gesture sensing and recognition. <i>IEEE Trans. Mobile Computing</i>, 2020, 21(7): 2620–2636. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TMC.2020.3037241" target="_blank">10.1109/TMC.2020.3037241</a>. </div> </td> </tr> <tr class="document-box" id="b86"> <td valign="top" class="td1"> [86] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang Y W, Shen J X, Zheng Y Q. Push the limit of acoustic gesture recognition. <i>IEEE Trans. Mobile Computing</i>, 2020, 21(5): 1798–1811. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TMC.2020.3032278" target="_blank">10.1109/TMC.2020.3032278</a>. </div> </td> </tr> <tr class="document-box" id="b87"> <td valign="top" class="td1"> [87] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang P H, Jiang R B, Liu C. Amaging: Acoustic hand imaging for self-adaptive gesture recognition. In <i>Proc</i>. <i>the 2022 IEEE Conference on Computer Communications</i>, May 2022, pp.80–89. DOI: <a href="https://doi.org/10.1109/INFOCOM48880.2022.9796906">10.1109/INFOCOM48880.2022.9796906</a>. </div> </td> </tr> <tr class="document-box" id="b88"> <td valign="top" class="td1"> [88] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Larson E C, Goel M, Boriello G, Heltshe S, Rosenfeld M, Patel S N. SpiroSmart: Using a microphone to measure lung function on a mobile phone. In <i>Proc</i>. <i>the 2012 ACM Conference on Ubiquitous Computing</i>, Sept. 2012, pp.280–289. DOI: <a href="https://doi.org/10.1145/2370216.2370261">10.1145/2370216.2370261</a>. </div> </td> </tr> <tr class="document-box" id="b89"> <td valign="top" class="td1"> [89] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Qian K, Wu C S, Xiao F, Zheng Y, Zhang Y, Yang Z, Liu Y H. Acousticcardiogram: Monitoring heartbeats using acoustic signals on smart devices. In <i>Proc</i>. <i>the 2018 IEEE Conference on Computer Communications</i>, Apr. 2018, pp.1574–1582. DOI: <a href="https://doi.org/10.1109/INFOCOM.2018.8485978">10.1109/INFOCOM.2018.8485978</a>. </div> </td> </tr> <tr class="document-box" id="b90"> <td valign="top" class="td1"> [90] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Song X Z, Yang B Y, Yang G, Chen R R, Forno E, Chen W, Gao W. SpiroSonic: Monitoring human lung function via acoustic sensing on commodity smartphones. In <i>Proc</i>. <i>the 26th Annual International Conference on Mobile Computing and Networking</i>, Apr. 2020, Article No. 52. DOI: <a href="https://doi.org/10.1145/3372224.3419209">10.1145/3372224.3419209</a>. </div> </td> </tr> <tr class="document-box" id="b91"> <td valign="top" class="td1"> [91] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wan H R, Shi S Y, Cao W Y, Wang W, Chen G H. RespTracker: Multi-user room-scale respiration tracking with commercial acoustic devices. In <i>Proc</i>. <i>the 2021 IEEE Conference on Computer Communications</i>, May 2021. DOI: <a href="https://doi.org/10.1109/INFOCOM42981.2021.9488881">10.1109/INFOCOM42981.2021.9488881</a>. </div> </td> </tr> <tr class="document-box" id="b92"> <td valign="top" class="td1"> [92] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Vernon J, Canyelles-Pericas P, Torun H, Binns R, Ng W P, Fu Y Q. Apnoea-Pi: Sleep disorder monitoring with open-source electronics and acoustics. In <i>Proc</i>. <i>the 26th Int. Conf. Automation and Computing (ICAC)</i>, Sept. 2021. DOI: <a href="https://doi.org/10.23919/ICAC50006.2021.9594073">10.23919/ICAC50006.2021.9594073</a>. </div> </td> </tr> <tr class="document-box" id="b93"> <td valign="top" class="td1"> [93] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Liu K K, Liu X X, Li X L. Guoguo: Enabling fine-grained indoor localization via smartphone. In <i>Proc</i>. <i>the 11th Annual International Conference on Mobile Systems</i>, <i>Applications</i>, <i>and Services</i>, Jun. 2013, pp.235–248. DOI: <a href="https://doi.org/10.1145/2462456.2464450">10.1145/2462456.2464450</a>. </div> </td> </tr> <tr class="document-box" id="b94"> <td valign="top" class="td1"> [94] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zhou B, Elbadry M, Gao R P, Ye F. BatMapper: Acoustic sensing based indoor floor plan construction using smartphones. In <i>Proc</i>. <i>the 15th Annual International Conference on Mobile Systems</i>, <i>Applications</i>, <i>and Services</i>, Jun. 2017, pp.42–55. DOI: <a href="https://doi.org/10.1145/3081333.3081363">10.1145/3081333.3081363</a>. </div> </td> </tr> <tr class="document-box" id="b95"> <td valign="top" class="td1"> [95] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Pradhan S, Baig G, Mao W G, Qiu L L, Chen G H, Yang B. Smartphone-based acoustic indoor space mapping. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2018, 2(2): Article No. 75. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3214278" target="_blank">10.1145/3214278</a>. </div> </td> </tr> <tr class="document-box" id="b96"> <td valign="top" class="td1"> [96] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wijers M, Loveridge A, Macdonald D W, Markham A. CARACAL: A versatile passive acoustic monitoring tool for wildlife research and conservation. <i>Bioacoustics</i>, 2021, 30(1): 41–57. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1080/09524622.2019.1685408" target="_blank">10.1080/09524622.2019.1685408</a>. </div> </td> </tr> <tr class="document-box" id="b97"> <td valign="top" class="td1"> [97] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Dong L J, Tao Q, Hu Q C, Deng S J, Chen Y C, Luo Q M, Zhang X H. Acoustic emission source location method and experimental verification for structures containing unknown empty areas. <i>International Journal of Mining Science and Technology</i>, 2022, 32(3): 487–497. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1016/j.ijmst.2022.01.002" target="_blank">10.1016/j.ijmst.2022.01.002</a>. </div> </td> </tr> <tr class="document-box" id="b98"> <td valign="top" class="td1"> [98] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Kafle M D, Fong S, Narasimhan S. Active acoustic leak detection and localization in a plastic pipe using time delay estimation. <i>Applied Acoustics</i>, 2022, 187: 108482. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1016/j.apacoust.2021.108482" target="_blank">10.1016/j.apacoust.2021.108482</a>. </div> </td> </tr> <tr class="document-box" id="b99"> <td valign="top" class="td1"> [99] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang J J, Zhao K C, Zhang X Y, Peng C Y. Ubiquitous keyboard for small mobile devices: Harnessing multipath fading for fine-grained keystroke localization. In <i>Proc</i>. <i>the 12th Annual International Conference on Mobile Systems</i>, <i>Applications</i>, <i>and Services</i>, Jun. 2014, pp.14–27. DOI: <a href="https://doi.org/10.1145/2594368.2594384">10.1145/2594368.2594384</a>. </div> </td> </tr> <tr class="document-box" id="b100"> <td valign="top" class="td1"> [100] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Alegre F, Vipperla R, Evans N, Fauve B. On the vulnerability of automatic speaker recognition to spoofing attacks with artificial signals. In <i>Proc</i>. <i>the 20th European Signal Processing Conference (EUSIPCO)</i>, Aug. 2012, pp.36–40. </div> </td> </tr> <tr class="document-box" id="b101"> <td valign="top" class="td1"> [101] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Chauhan J, Hu Y N, Seneviratne S, Misra A, Seneviratne A, Lee Y. BreathPrint: Breathing acoustics-based user authentication. In <i>Proc</i>. <i>the 15th Annual Int. Conf. Mobile Systems</i>, <i>Applications</i>, <i>and Services</i>, Jun. 2017, pp.278–291. DOI: <a href="https://doi.org/10.1145/3081333.3081355">10.1145/3081333.3081355</a>. </div> </td> </tr> <tr class="document-box" id="b102"> <td valign="top" class="td1"> [102] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zhang G M, Yan C, Ji X Y, Zhang T C, Zhang T M, Xu W Y. DolphinAttack: Inaudible voice commands. In <i>Proc</i>. <i>the 2017 ACM SIGSAC Conference on Computer and Communications Security</i>, Oct. 2017, pp.103–117. DOI: <a href="https://doi.org/10.1145/3133956.3134052">10.1145/3133956.3134052</a>. </div> </td> </tr> <tr class="document-box" id="b103"> <td valign="top" class="td1"> [103] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Yuan X J, Chen Y X, Zhao Y, Long Y H, Liu X K, Chen K, Zhang S Z, Huang H Q, Wang X F, Gunter C A. CommanderSong: A systematic approach for practical adversarial voice recognition. arXiv: 1801.08535, 2018. <a href="https://arxiv.org/abs/1801.08535">https://arxiv.org/abs/1801.08535</a>, Jan. 2023. </div> </td> </tr> <tr class="document-box" id="b104"> <td valign="top" class="td1"> [104] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Gao Y, Wang W, Phoha V V, Sun W, Jin Z P. EarEcho: Using ear canal echo for wearable authentication. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2019, 3(3): Article No. 81. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3351239" target="_blank">10.1145/3351239</a>. </div> </td> </tr> <tr class="document-box" id="b105"> <td valign="top" class="td1"> [105] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Lu L, Yu J D, Chen Y Y, Liu H B, Zhu Y M, Liu Y F, Li M L. LipPass: Lip reading-based user authentication on smartphones leveraging acoustic signals. In <i>Proc</i>. <i>the 2018 IEEE Conference on Computer Communications</i>, Apr. 2018, pp.1466–1474. DOI: <a href="https://doi.org/10.1109/INFOCOM.2018.8486283">10.1109/INFOCOM.2018.8486283</a>. </div> </td> </tr> <tr class="document-box" id="b106"> <td valign="top" class="td1"> [106] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Chen M Q, Lin J W, Zou Y P, Ruby R, Wu K S. SilentSign: Device-free handwritten signature verification through acoustic sensing. In <i>Proc</i>. <i>the 2020 IEEE International Conference on Pervasive Computing and Communications (PerCom)</i>, Mar. 2020. DOI: <a href="https://doi.org/10.1109/PerCom45495.2020.9127372">10.1109/PerCom45495.2020.9127372</a>. </div> </td> </tr> <tr class="document-box" id="b107"> <td valign="top" class="td1"> [107] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Ferlini A, Ma D, Harle R, Mascolo C. EarGate: Gait-based user identification with in-ear microphones. In <i>Proc</i>. <i>the 27th Annual International Conference on Mobile Computing and Networking</i>, Oct. 2021, pp.337–349. DOI: <a href="https://doi.org/10.1145/3447993.3483240">10.1145/3447993.3483240</a>. </div> </td> </tr> <tr class="document-box" id="b108"> <td valign="top" class="td1"> [108] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Ren Y Z, Wen P, Liu H B, Zheng Z R, Chen Y Y, Huang P C, Li H W. Proximity-Echo: Secure two factor authentication using active sound sensing. In <i>Proc</i>. <i>the 2021 IEEE Conference on Computer Communications</i>, May 2021. DOI: <a href="https://doi.org/10.1109/INFOCOM42981.2021.9488866">10.1109/INFOCOM42981.2021.9488866</a>. </div> </td> </tr> <tr class="document-box" id="b109"> <td valign="top" class="td1"> [109] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Balagani K, Cardaioli M, Cecconello S, Conti M, Tsudik G. We can hear your PIN drop: An acoustic side-channel attack on ATM PIN pads. In <i>Proc</i>. <i>the 27th European Symposium on Research in Computer Security</i>, Sept. 2022, pp.633–652. DOI: <a href="https://doi.org/10.1007/978-3-031-17140-6_31">10.1007/978-3-031-17140-6_31</a>. </div> </td> </tr> <tr class="document-box" id="b110"> <td valign="top" class="td1"> [110] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Xie Y D, Li F, Wu Y, Chen H J, Zhao Z Y, Wang Y. TeethPass: Dental occlusion-based user authentication via in-ear acoustic sensing. In <i>Proc</i>. <i>the 2022 IEEE Conference on Computer Communications</i>, May 2022, pp.1789–1798. DOI: <a href="https://doi.org/10.1109/INFOCOM48880.2022.9796951">10.1109/INFOCOM48880.2022.9796951</a>. </div> </td> </tr> <tr class="document-box" id="b111"> <td valign="top" class="td1"> [111] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang Z, Ren Y L, Chen Y Y, Yang J. ToothSonic: Earable authentication via acoustic toothprint. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2022, 6(2): Article No. 78. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3534606" target="_blank">10.1145/3534606</a>. </div> </td> </tr> <tr class="document-box" id="b112"> <td valign="top" class="td1"> [112] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Ma Y S, Zhou G, Wang S Q. WiFi sensing with channel state information: A survey. <i>ACM Computing Surveys</i>, 2019, 52(3): Article No. 46. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3310194" target="_blank">10.1145/3310194</a>. </div> </td> </tr> <tr class="document-box" id="b113"> <td valign="top" class="td1"> [113] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Xie Y X, Li Z J, Li M. Precise power delay profiling with commodity WiFi. In <i>Proc</i>. <i>the 21st Annual International Conference on Mobile Computing and Networking</i>, Sept. 2015, pp.53–64. DOI: <a href="https://doi.org/10.1145/2789168.2790124">10.1145/2789168.2790124</a>. </div> </td> </tr> <tr class="document-box" id="b114"> <td valign="top" class="td1"> [114] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Jiang Z P, Luan T H, Ren X C, Lv D T, Hao H, Wang J, Zhao K, Xi W, Xu Y S, Li R. Eliminating the barriers: Demystifying Wi-Fi baseband design and introducing the PicoScenes Wi-Fi sensing platform. <i>IEEE Internet of Things Journal</i>, 2022, 9(6): 4476–4496. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/JIOT.2021.3104666" target="_blank">10.1109/JIOT.2021.3104666</a>. </div> </td> </tr> <tr class="document-box" id="b115"> <td valign="top" class="td1"> [115] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zheng F, Zhang G L, Song Z J. Comparison of different implementations of MFCC. <i>Journal of Computer Science and Technology</i>, 2001, 16(6): 582–589. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1007/BF02943243" target="_blank">10.1007/BF02943243</a>. </div> </td> </tr> <tr class="document-box" id="b116"> <td valign="top" class="td1"> [116] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Pedretti L W, Early M B. Occupational Therapy: Practice Skills for Physical Dysfunction. Mosby London, 2001. </div> </td> </tr> <tr class="document-box" id="b117"> <td valign="top" class="td1"> [117] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Santhalingam P S, Hosain A A, Zhang D, Pathak P, Rangwala H, Kushalnagar R. mmASL: Environment-independent ASL gesture recognition using 60 GHz millimeter-wave signals. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2020, 4(1): Article No. 26. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3381010" target="_blank">10.1145/3381010</a>. </div> </td> </tr> <tr class="document-box" id="b118"> <td valign="top" class="td1"> [118] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Gallo P, Mangione S. RSS-eye: Human-assisted indoor localization without radio maps. In <i>Proc</i>. <i>the 2015 IEEE International Conference on Communications</i>, Jun. 2015, pp.1553–1558. DOI: <a href="https://doi.org/10.1109/ICC.2015.7248545">10.1109/ICC.2015.7248545</a>. </div> </td> </tr> <tr class="document-box" id="b119"> <td valign="top" class="td1"> [119] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Liu H, Darabi H, Banerjee P, Liu J. Survey of wireless indoor positioning techniques and systems. <i>IEEE Trans. Systems, Man, and Cybernetics, Part C (Applications and Reviews)</i>, 2007, 37(6): 1067–1080. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TSMCC.2007.905750" target="_blank">10.1109/TSMCC.2007.905750</a>. </div> </td> </tr> <tr class="document-box" id="b120"> <td valign="top" class="td1"> [120] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Pahlavan K, Li X R, Makela J P. Indoor geolocation science and technology. <i>IEEE Communications Magazine</i>, 2002, 40(2): 112–118. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/35.983917" target="_blank">10.1109/35.983917</a>. </div> </td> </tr> <tr class="document-box" id="b121"> <td valign="top" class="td1"> [121] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Chen K Y, Ashbrook D, Goel M, Lee S H, Patel S. AirLink: Sharing files between multiple devices using in-air gestures. In <i>Proc</i>. <i>the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing</i>, Sept. 2014, pp.565–569. DOI: <a href="https://doi.org/10.1145/2632048.2632090">10.1145/2632048.2632090</a>. </div> </td> </tr> <tr class="document-box" id="b122"> <td valign="top" class="td1"> [122] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zhang M T, Yang P L, Tian C, Shi L, Tang S J, Xiao F. SoundWrite: Text input on surfaces through mobile acoustic sensing. In <i>Proc</i>. <i>the 1st International Workshop on Experiences with the Design and Implementation of Smart Objects</i>, Sept. 2015, pp.13–17. DOI: <a href="https://doi.org/10.1145/2797044.2797045">10.1145/2797044.2797045</a>. </div> </td> </tr> <tr class="document-box" id="b123"> <td valign="top" class="td1"> [123] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang X, Sun K, Zhao T, Wang W, Gu Q. Dynamic speed warping: Similarity-based one-shot learning for device-free gesture signals. In <i>Proc</i>. <i>the 2020 IEEE Conference on Computer Communications</i>, Jul. 2020, pp.556–565. DOI: <a href="https://doi.org/10.1109/INFOCOM41043.2020.9155491">10.1109/INFOCOM41043.2020.9155491</a>. </div> </td> </tr> <tr class="document-box" id="b124"> <td valign="top" class="td1"> [124] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Weiss K, Khoshgoftaar T M, Wang D D. A survey of transfer learning. <i>Journal of Big Data</i>, 2016, 3(1): Article No. 9. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1186/s40537-016-0043-6" target="_blank">10.1186/s40537-016-0043-6</a>. </div> </td> </tr> <tr class="document-box" id="b125"> <td valign="top" class="td1"> [125] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang Y Q, Yao Q M, Kwok J T, Ni L M. Generalizing from a few examples: A survey on few-shot learning. <i>ACM Computing Surveys</i>, 2021, 53(3): Article No. 63. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3386252" target="_blank">10.1145/3386252</a>. </div> </td> </tr> <tr class="document-box" id="b126"> <td valign="top" class="td1"> [126] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Yi X, Walia E, Babyn P. Generative adversarial network in medical imaging: A review. <i>Medical Image Analysis</i>, 2019, 58: 101552. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1016/j.media.2019.101552" target="_blank">10.1016/j.media.2019.101552</a>. </div> </td> </tr> <tr class="document-box" id="b127"> <td valign="top" class="td1"> [127] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Ozcan T, Basturk A. Transfer learning-based convolutional neural networks with heuristic optimization for hand gesture recognition. <i>Neural Computing and Applications</i>, 2019, 31(12): 8955–8970. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1007/s00521-019-04427-y" target="_blank">10.1007/s00521-019-04427-y</a>. </div> </td> </tr> <tr class="document-box" id="b128"> <td valign="top" class="td1"> [128] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Rahimian E, Zabihi S, Asif A, Farina D, Atashzar S F, Mohammadi A. FS-HGR: Few-shot learning for hand gesture recognition via electromyography. <i>IEEE Trans. Neural Systems and Rehabilitation Engineering</i>, 2021, 29: 1004–1015. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TNSRE.2021.3077413" target="_blank">10.1109/TNSRE.2021.3077413</a>. </div> </td> </tr> <tr class="document-box" id="b129"> <td valign="top" class="td1"> [129] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang J, Zhang L, Wang C C, Ma X R, Gao Q H, Lin B. Device-free human gesture recognition with generative adversarial networks. <i>IEEE Internet of Things Journal</i>, 2020, 7(8): 7678–7688. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/JIOT.2020.2988291" target="_blank">10.1109/JIOT.2020.2988291</a>. </div> </td> </tr> <tr class="document-box" id="b130"> <td valign="top" class="td1"> [130] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Liu C, Wang P H, Jiang R B, Zhu Y M. AMT: Acoustic multi-target tracking with smartphone MIMO system. In <i>Proc</i>. <i>the 2021 IEEE Conference on Computer Communications</i>, May 2021. DOI: <a href="https://doi.org/10.1109/INFOCOM42981.2021.9488768">10.1109/INFOCOM42981.2021.9488768</a>. </div> </td> </tr> <tr class="document-box" id="b131"> <td valign="top" class="td1"> [131] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Yun S K, Chen Y C, Qiu L L. Turning a mobile device into a mouse in the air. In <i>Proc</i>. <i>the 13th Annual International Conference on Mobile Systems</i>, <i>Applications</i>, <i>and Services</i>, May 2015, pp.15–29. DOI: <a href="https://doi.org/10.1145/2742647.2742662">10.1145/2742647.2742662</a>. </div> </td> </tr> <tr class="document-box" id="b132"> <td valign="top" class="td1"> [132] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Mao W G, He J, Qiu L L. CAT: High-precision acoustic motion tracking. In <i>Proc</i>. <i>the 22nd Annual International Conference on Mobile Computing and Networking</i>, Oct. 2016, pp.69–81. DOI: <a href="https://doi.org/10.1145/2973750.2973755">10.1145/2973750.2973755</a>. </div> </td> </tr> <tr class="document-box" id="b133"> <td valign="top" class="td1"> [133] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Chen H J, Li F, Wang Y. EchoTrack: Acoustic device-free hand tracking on smart phones. In <i>Proc</i>. <i>the 2017 IEEE Conference on Computer Communications</i>, May 2017. DOI: <a href="https://doi.org/10.1109/INFOCOM.2017.8057101">10.1109/INFOCOM.2017.8057101</a>. </div> </td> </tr> <tr class="document-box" id="b134"> <td valign="top" class="td1"> [134] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Nandakumar R, Iyer V, Tan D, Gollakota S. FingerIO: Using active sonar for fine-grained finger tracking. In <i>Proc</i>. <i>the 2016 CHI Conference on Human Factors in Computing Systems</i>, May 2016, pp.1515–1525. DOI: <a href="https://doi.org/10.1145/2858036.2858580">10.1145/2858036.2858580</a>. </div> </td> </tr> <tr class="document-box" id="b135"> <td valign="top" class="td1"> [135] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Yun S K, Chen Y C, Zheng H H, Qiu L L, Mao W G. Strata: Fine-grained acoustic-based device-free tracking. In <i>Proc</i>. <i>the 15th Annual International Conference on Mobile Systems</i>, <i>Applications</i>, <i>and Services</i>, Jun. 2017, pp.15–28. DOI: <a href="https://doi.org/10.1145/3081333.3081356">10.1145/3081333.3081356</a>. </div> </td> </tr> <tr class="document-box" id="b136"> <td valign="top" class="td1"> [136] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Lu L, Liu J, Yu J D, Chen Y Y, Zhu Y M, Kong L H, Li M L. Enable traditional laptops with virtual writing capability leveraging acoustic signals. <i>The Computer Journal</i>, 2021, 64(12): 1814–1831. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1093/comjnl/bxz153" target="_blank">10.1093/comjnl/bxz153</a>. </div> </td> </tr> <tr class="document-box" id="b137"> <td valign="top" class="td1"> [137] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Liu Y, Zhang W X, Yang Y, Fang W D, Qin F, Dai X W. PAMT: Phase-based acoustic motion tracking in multipath fading environments. In <i>Proc</i>. <i>the 2019 IEEE Conference on Computer Communications</i>, Apr. 29–May 2, 2019, pp.2386–2394. DOI: <a href="https://doi.org/10.1109/INFOCOM.2019.8737366">10.1109/INFOCOM.2019.8737366</a>. </div> </td> </tr> <tr class="document-box" id="b138"> <td valign="top" class="td1"> [138] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Kumar M, Veeraraghavan A, Sabharwal A. DistancePPG: Robust non-contact vital signs monitoring using a camera. <i>Biomedical Optics Express</i>, 2015, 6(5): 1565–1588. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1364/BOE.6.001565" target="_blank">10.1364/BOE.6.001565</a>. </div> </td> </tr> <tr class="document-box" id="b139"> <td valign="top" class="td1"> [139] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Jia Z H, Bonde A, Li S G, Xu C R, Wang J X, Zhang Y Y, Howard R E, Zhang P. Monitoring a person’s heart rate and respiratory rate on a shared bed using geophones. In <i>Proc</i>. <i>the 15th ACM Conference on Embedded Network Sensor Systems (SenSys 2017)</i>, Nov. 2017, Article No. 6. DOI: <a href="https://doi.org/10.1145/3131672.3131679">10.1145/3131672.3131679</a>. </div> </td> </tr> <tr class="document-box" id="b140"> <td valign="top" class="td1"> [140] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Jia Z H, Alaziz M, Chi X, Howard R E, Zhang Y Y, Zhang P, Trappe W, Sivasubramaniam A, An N. HB-phone: A bed-mounted geophone-based heartbeat monitoring system. In <i>Proc</i>. <i>the 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)</i>, Apr. 2016. DOI: <a href="https://doi.org/10.1109/IPSN.2016.7460676">10.1109/IPSN.2016.7460676</a>. </div> </td> </tr> <tr class="document-box" id="b141"> <td valign="top" class="td1"> [141] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Li F Y, Valero M, Shahriar H, Khan R A, Ahamed S I. Wi-COVID: A COVID-19 symptom detection and patient monitoring framework using WiFi. <i>Smart Health</i>, 2021, 19: 100147. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1016/j.smhl.2020.100147" target="_blank">10.1016/j.smhl.2020.100147</a>. </div> </td> </tr> <tr class="document-box" id="b142"> <td valign="top" class="td1"> [142] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Nandakumar R, Gollakota S, Watson N. Contactless sleep apnea detection on smartphones. In <i>Proc</i>. <i>the 13th Annual International Conference on Mobile Systems</i>, <i>Applications</i>, <i>and Services</i>, May 2015, pp.45–57. DOI: <a href="https://doi.org/10.1145/2742647.2742674">10.1145/2742647.2742674</a>. </div> </td> </tr> <tr class="document-box" id="b143"> <td valign="top" class="td1"> [143] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Li Y, Zeng Z L, Popescu M, Ho K C. Acoustic fall detection using a circular microphone array. In <i>Proc</i>. <i>the 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology</i>, Aug. 31–Sept. 4, 2010, pp.2242–2245. DOI: <a href="https://doi.org/10.1109/IEMBS.2010.5627368">10.1109/IEMBS.2010.5627368</a>. </div> </td> </tr> <tr class="document-box" id="b144"> <td valign="top" class="td1"> [144] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Ren Y Z, Wang C, Yang J, Chen Y Y. Fine-grained sleep monitoring: Hearing your breathing with smartphones. In <i>Proc</i>. <i>the 2015 IEEE Conference on Computer Communications (INFOCOM)</i>, Apr. 26–May 1, 2015, pp.1194–1202. DOI: <a href="https://doi.org/10.1109/INFOCOM.2015.7218494">10.1109/INFOCOM.2015.7218494</a>. </div> </td> </tr> <tr class="document-box" id="b145"> <td valign="top" class="td1"> [145] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Yang J, Sidhom S, Chandrasekaran G, Vu T, Liu H B, Cecan N, Chen Y Y, Gruteser M, Martin R P. Detecting driver phone use leveraging car speakers. In <i>Proc</i>. <i>the 17th Annual International Conference on Mobile Computing and Networking</i>, Sept. 2011, pp.97–108. DOI: <a href="https://doi.org/10.1145/2030613.2030625">10.1145/2030613.2030625</a>. </div> </td> </tr> <tr class="document-box" id="b146"> <td valign="top" class="td1"> [146] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Xu X Y, Gao H, Yu J D, Chen Y Y, Zhu Y M, Xue G T, Li M L. ER: Early recognition of inattentive driving leveraging audio devices on smartphones. In <i>Proc</i>. <i>the 2017 IEEE Conference on Computer Communications</i>, May 2017. DOI: <a href="https://doi.org/10.1109/INFOCOM.2017.8057022">10.1109/INFOCOM.2017.8057022</a>. </div> </td> </tr> <tr class="document-box" id="b147"> <td valign="top" class="td1"> [147] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Xu X Y, Yu J D, Chen Y Y, Zhu Y M, Qian S Y, Li M L. Leveraging audio signals for early recognition of inattentive driving with smartphones. <i>IEEE Trans. Mobile Computing</i>, 2018, 17(7): 1553–1567. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TMC.2017.2772253" target="_blank">10.1109/TMC.2017.2772253</a>. </div> </td> </tr> <tr class="document-box" id="b148"> <td valign="top" class="td1"> [148] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Xu X Y, Yu J D, Chen Y Y, Zhu Y M, Kong L H, Li M L. BreathListener: Fine-grained breathing monitoring in driving environments utilizing acoustic signals. In <i>Proc</i>. <i>the 17th Annual International Conference on Mobile Systems</i>, <i>Applications</i>, <i>and Services</i>, Jun. 2019, pp.54–66. DOI: <a href="https://doi.org/10.1145/3307334.3326074">10.1145/3307334.3326074</a>. </div> </td> </tr> <tr class="document-box" id="b149"> <td valign="top" class="td1"> [149] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Liu S C, Zhou Z M, Du J Z, Shangguan L F, Han J, Wang X. UbiEar: Bringing location-independent sound awareness to the hard-of-hearing people with smartphones. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2017, 1(2): Article No. 17. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3090082" target="_blank">10.1145/3090082</a>. </div> </td> </tr> <tr class="document-box" id="b150"> <td valign="top" class="td1"> [150] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Nishimura Y, Imai N, Yoshihara K. A proposal on direction estimation between devices using acoustic waves. In <i>Proc</i>. <i>the 8th International Conference on Mobile and Ubiquitous Systems: Computing</i>, <i>Networking</i>, <i>and Services</i>, Dec. 2011, pp.25–36. DOI: <a href="https://doi.org/10.1007/978-3-642-30973-1_3">10.1007/978-3-642-30973-1_3</a>. </div> </td> </tr> <tr class="document-box" id="b151"> <td valign="top" class="td1"> [151] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zhang Z B, Chu D, Chen X M, Moscibroda T. SwordFight: Enabling a new class of phone-to-phone action games on commodity phones. In <i>Proc</i>. <i>the 10th International Conference on Mobile Systems</i>, <i>Applications</i>, <i>and Services</i>, Jun. 2012, pp.1–14. DOI: <a href="https://doi.org/10.1145/2307636.2307638">10.1145/2307636.2307638</a>. </div> </td> </tr> <tr class="document-box" id="b152"> <td valign="top" class="td1"> [152] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Liu H B, Gan Y, Yang J, Sidhom S, Wang Y, Chen Y Y, Ye F. Push the limit of WiFi based localization for smartphones. In <i>Proc</i>. <i>the 18th Annual International Conference on Mobile Computing and Networking</i>, Aug. 2012, pp.305–316. DOI: <a href="https://doi.org/10.1145/2348543.2348581">10.1145/2348543.2348581</a>. </div> </td> </tr> <tr class="document-box" id="b153"> <td valign="top" class="td1"> [153] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Nandakumar R, Chintalapudi K K, Padmanabhan V N. Centaur: Locating devices in an office environment. In <i>Proc</i>. <i>the 18th Annual International Conference on Mobile Computing and Networking</i>, Aug. 2012, pp.281–292. DOI: <a href="https://doi.org/10.1145/2348543.2348579">10.1145/2348543.2348579</a>. </div> </td> </tr> <tr class="document-box" id="b154"> <td valign="top" class="td1"> [154] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Tarzia S P, Dinda P A, Dick R P, Memik G. Indoor localization without infrastructure using the acoustic background spectrum. In <i>Proc</i>. <i>the 9th International Conference on Mobile Systems</i>, <i>Applications</i>, <i>and Services</i>, Jun. 2011, pp.155–168. DOI: <a href="https://doi.org/10.1145/1999995.2000011">10.1145/1999995.2000011</a>. </div> </td> </tr> <tr class="document-box" id="b155"> <td valign="top" class="td1"> [155] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Tung Y C, Shin K G. EchoTag: Accurate infrastructure-free indoor location tagging with smartphones. In <i>Proc</i>. <i>the 21st Annual International Conference on Mobile Computing and Networking</i>, Sept. 2015, pp.525–536. DOI: <a href="https://doi.org/10.1145/2789168.2790102">10.1145/2789168.2790102</a>. </div> </td> </tr> <tr class="document-box" id="b156"> <td valign="top" class="td1"> [156] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Huang W C, Xiong Y, Li X Y, Lin H, Mao X F, Yang P L, Liu Y H. Shake and walk: Acoustic direction finding and fine-grained indoor localization using smartphones. In <i>Proc</i>. <i>the 2014 IEEE Conference on Computer Communications</i>, Apr. 27–May 2, 2014, pp.370–378. DOI: <a href="https://doi.org/10.1109/INFOCOM.2014.6847959">10.1109/INFOCOM.2014.6847959</a>. </div> </td> </tr> <tr class="document-box" id="b157"> <td valign="top" class="td1"> [157] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zhu T, Ma Q, Zhang S F, Liu Y H. Context-free attacks using keyboard acoustic emanations. In <i>Proc</i>. <i>the 2014 ACM SIGSAC Conference on Computer and Communications Security</i>, Nov. 2014, pp.453–464. DOI: <a href="https://doi.org/10.1145/2660267.2660296">10.1145/2660267.2660296</a>. </div> </td> </tr> <tr class="document-box" id="b158"> <td valign="top" class="td1"> [158] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Liu J, Wang Y, Kar G, Chen Y Y, Yang J, Gruteser M. Snooping keystrokes with mm-level audio ranging on a single phone. In <i>Proc</i>. <i>the 21st Annual International Conference on Mobile Computing and Networking</i>, Sept. 2015, pp.142–154. DOI: <a href="https://doi.org/10.1145/2789168.2790122">10.1145/2789168.2790122</a>. </div> </td> </tr> <tr class="document-box" id="b159"> <td valign="top" class="td1"> [159] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Liu X Y, Zhou Z, Diao W R, Li Z, Zhang K H. When good becomes evil: Keystroke inference with smartwatch. In <i>Proc</i>. <i>the 22nd ACM SIGSAC Conference on Computer and Communications Security</i>, Oct. 2015, pp.1273–1285. DOI: <a href="https://doi.org/10.1145/2810103.2813668">10.1145/2810103.2813668</a>. </div> </td> </tr> <tr class="document-box" id="b160"> <td valign="top" class="td1"> [160] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Fang Y Y, Zhao Z W, Wang Z, Min G Y, Cao Y, Huang H J, Yin H. Eavesdrop with PoKeMon: Position free keystroke monitoring using acoustic data. <i>Future Generation Computer Systems</i>, 2018, 87: 704–711. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1016/j.future.2017.10.039" target="_blank">10.1016/j.future.2017.10.039</a>. </div> </td> </tr> <tr class="document-box" id="b161"> <td valign="top" class="td1"> [161] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wu Z Z, Evans N, Kinnunen T, Yamagishi J, Alegre F, Li H Z. Spoofing and countermeasures for speaker verification: A survey. <i>Speech Communication</i>, 2015, 66: 130–153. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1016/j.specom.2014.10.005" target="_blank">10.1016/j.specom.2014.10.005</a>. </div> </td> </tr> <tr class="document-box" id="b162"> <td valign="top" class="td1"> [162] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wu Z Z, Gao S, Cling E S, Li H Z. A study on replay attack and anti-spoofing for text-dependent speaker verification. In <i>Proc</i>. <i>the 2014 Signal and Information Processing Association Annual Summit and Conference (APSIPA)</i>, Dec. 2014. DOI: <a href="https://doi.org/10.1109/APSIPA.2014.7041636">10.1109/APSIPA.2014.7041636</a>. </div> </td> </tr> <tr class="document-box" id="b163"> <td valign="top" class="td1"> [163] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wu Z Z, Li H Z. Voice conversion and spoofing attack on speaker verification systems. In <i>Proc</i>. <i>the 2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference</i>, Oct. 29–Nov. 1, 2013. DOI: <a href="https://doi.org/10.1109/APSIPA.2013.6694344">10.1109/APSIPA.2013.6694344</a>. </div> </td> </tr> <tr class="document-box" id="b164"> <td valign="top" class="td1"> [164] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Carlini N, Mishra P, Vaidya T, Zhang Y K, Sherr M, Shields C, Wagner D, Zhou W C. Hidden voice commands. In <i>Proc</i>. <i>the 25th USENIX Security Symposium (USENIX Security 16)</i>, Aug. 2016, pp.513–530. </div> </td> </tr> <tr class="document-box" id="b165"> <td valign="top" class="td1"> [165] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Carlini N, Wagner D. Audio adversarial examples: Targeted attacks on speech-to-text. In <i>Proc</i>. <i>the 2018 IEEE Security and Privacy Workshops (SPW)</i>, May 2018. DOI: <a href="https://doi.org/10.1109/SPW.2018.00009">10.1109/SPW.2018.00009</a>. </div> </td> </tr> <tr class="document-box" id="b166"> <td valign="top" class="td1"> [166] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Kasmi C, Esteves J L. IEMI threats for information security: Remote command injection on modern smartphones. <i>IEEE Trans. Electromagnetic Compatibility</i>, 2015, 57(6): 1752–1755. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TEMC.2015.2463089" target="_blank">10.1109/TEMC.2015.2463089</a>. </div> </td> </tr> <tr class="document-box" id="b167"> <td valign="top" class="td1"> [167] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wei L Q, Long Y H, Wei H R, Li Y J. New acoustic features for synthetic and replay spoofing attack detection. <i>Symmetry</i>, 2022, 14(2): Article No. 274. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.3390/sym14020274" target="_blank">10.3390/sym14020274</a>. </div> </td> </tr> <tr class="document-box" id="b168"> <td valign="top" class="td1"> [168] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zhou B, Lohokare J, Gao R P, Ye F. EchoPrint: Two-factor authentication using acoustics and vision on smartphones. In <i>Proc</i>. <i>the 24th Annual International Conference on Mobile Computing and Networking</i>, Oct. 2018, pp.321–336. DOI: <a href="https://doi.org/10.1145/3241539.3241575">10.1145/3241539.3241575</a>. </div> </td> </tr> <tr class="document-box" id="b169"> <td valign="top" class="td1"> [169] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Zou Y P, Zhao M, Zhou Z M, Lin J W, Li M, Wu K S. BiLock: User authentication via dental occlusion biometrics. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2018, 2(3): Article No. 152. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3264962" target="_blank">10.1145/3264962</a>. </div> </td> </tr> <tr class="document-box" id="b170"> <td valign="top" class="td1"> [170] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Xu W, Yu Z W, Wang Z, Guo B, Han Q. AcousticID: Gait-based human identification using acoustic signal. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2019, 3(3): Article No. 115. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3351273" target="_blank">10.1145/3351273</a>. </div> </td> </tr> <tr class="document-box" id="b171"> <td valign="top" class="td1"> [171] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Ding F, Wang D, Zhang Q, Zhao R. ASSV: Handwritten signature verification using acoustic signals. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2019, 3(3): Article No. 80. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3351238" target="_blank">10.1145/3351238</a>. </div> </td> </tr> <tr class="document-box" id="b172"> <td valign="top" class="td1"> [172] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Shrestha P, Shrestha B, Saxena N. Home alone: The insider threat of unattended wearables and a defense using audio proximity. In <i>Proc</i>. <i>the</i> <i>2018 IEEE Conference on Communications and Network Security (CNS)</i>, May 30–Jun 1, 2018. DOI: <a href="https://doi.org/10.1109/CNS.2018.8433216">10.1109/CNS.2018.8433216</a>. </div> </td> </tr> <tr class="document-box" id="b173"> <td valign="top" class="td1"> [173] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Shrestha P, Saxena N. Listening watch: Wearable two-factor authentication using speech signals resilient to near-far attacks. In <i>Proc</i>. <i>the 11th ACM Conference on Security & Privacy in Wireless and Mobile Networks</i>, Jun. 2018, pp.99–110. DOI: <a href="https://doi.org/10.1145/3212480.3212501">10.1145/3212480.3212501</a>. </div> </td> </tr> <tr class="document-box" id="b174"> <td valign="top" class="td1"> [174] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Feng H, Fawaz K, Shin K G. Continuous authentication for voice assistants. In <i>Proc</i>. <i>the 23rd Annual International Conference on Mobile Computing and Networking</i>, Oct. 2017, pp.343–355. DOI: <a href="https://doi.org/10.1145/3117811.3117823">10.1145/3117811.3117823</a>. </div> </td> </tr> <tr class="document-box" id="b175"> <td valign="top" class="td1"> [175] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Chen S, Ren K, Piao S X, Wang C, Wang Q, Weng J, Su L, Mohaisen A. You can hear but you cannot steal: Defending against voice impersonation attacks on smartphones. In <i>Proc</i>. <i>the 37th IEEE International Conference on Distributed Computing Systems (ICDCS)</i>, Jun. 2017, pp.183–195. DOI: <a href="https://doi.org/10.1109/ICDCS.2017.133">10.1109/ICDCS.2017.133</a>. </div> </td> </tr> <tr class="document-box" id="b176"> <td valign="top" class="td1"> [176] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang Q, Lin X, Zhou M, Chen Y J, Wang C, Li Q, Luo X Y. VoicePop: A pop noise based anti-spoofing system for voice authentication on smartphones. In <i>Proc</i>. <i>the 2019 IEEE Conference on Computer Communications</i>, Apr. 29–May 2, 2019, pp.2062–2070. DOI: <a href="https://doi.org/10.1109/INFOCOM.2019.8737422">10.1109/INFOCOM.2019.8737422</a>. </div> </td> </tr> <tr class="document-box" id="b177"> <td valign="top" class="td1"> [177] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Yan C, Ji X Y, Wang K, Jiang Q H, Jin Z Z, Xu W Y. A survey on voice assistant security: Attacks and countermeasures. <i>ACM Computing Surveys</i>, 2022, 55(4): Article No. 84. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3527153" target="_blank">10.1145/3527153</a>. </div> </td> </tr> <tr class="document-box" id="b178"> <td valign="top" class="td1"> [178] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang F, Zhou S P, Panev S, Han J S, Huang D. Person-in-WiFi: Fine-grained person perception using WiFi. In <i>Proc</i>. <i>the 2019 IEEE/CVF International Conference on Computer Vision</i>, Oct. 27–Nov. 2, 2019, pp.5451–5460. DOI: <a href="https://doi.org/10.1109/ICCV.2019.00555">10.1109/ICCV.2019.00555</a>. </div> </td> </tr> <tr class="document-box" id="b179"> <td valign="top" class="td1"> [179] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Li C N, Liu Z, Yao Y G, Cao Z C, Zhang M, Liu Y H. Wi-Fi see it all: Generative adversarial network-augmented versatile Wi-Fi imaging. In <i>Proc</i>. <i>the 18th Conference on Embedded Networked Sensor Systems</i>, Nov. 2020, pp.436–448. DOI: <a href="https://doi.org/10.1145/3384419.3430725">10.1145/3384419.3430725</a>. </div> </td> </tr> <tr class="document-box" id="b180"> <td valign="top" class="td1"> [180] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Yang Q, Wu H X, Huang Q Y, Zhang J, Chen H, Li W C, Tao X F, Zhang Q. Side-lobe can know more: Towards simultaneous communication and sensing for mmWave. <i>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</i>, 2023, 6(4): Article No. 191. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1145/3569498" target="_blank">10.1145/3569498</a>. </div> </td> </tr> <tr class="document-box" id="b181"> <td valign="top" class="td1"> [181] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Huang Q Y, Luo Z Q, Zhang J, Wang W, Zhang Q. LoRadar: Enabling concurrent radar sensing and LoRa communication. <i>IEEE Trans. Mobile Computing</i>, 2022, 21(6): 2045–2057. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/TMC.2020.3035797" target="_blank">10.1109/TMC.2020.3035797</a>. </div> </td> </tr> <tr class="document-box" id="b182"> <td valign="top" class="td1"> [182] </td> <td class="td2"> <div class="reference-en" style="margin:0px;padding:0px;"> Wang J, Varshney N, Gentile C, Blandino S, Chuang J, Golmie N. Integrated sensing and communication: Enabling techniques, applications, tools and data sets, standardization, and future directions. <i>IEEE Internet of Things Journal</i>, 2022, 9(23): 23416–23440. DOI: <a class="mainColor ref-doi" href="http://dx.doi.org/10.1109/JIOT.2022.3190845" target="_blank">10.1109/JIOT.2022.3190845</a>. </div> </td> </tr> </tbody> </table>
[1] Warunika Ranaweera, Parmit Chilana, Daniel Cohen-Or, Hao Zhang. ExquiMo:一种用于协作3D模型设计的精致僵尸（Exquisite Corpse）工具[J]. , 2017, 32(6): 1138-1149.
[2] Jing Wu, Paul L. Rosin, Xianfang Sun, Ralph R. Martin. 基于交互式禁忌搜索的从阴影恢复形状算法[J]. , 2016, 31(3): 450-462.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] 周笛;. A Recovery Technique for Distributed Communicating Process Systems[J]. , 1986, 1(2): 34 -43 .
[2] 李未;. A Structural Operational Semantics for an Edison Like Language(2)[J]. , 1986, 1(2): 42 -53 .
[3] 李万学;. Almost Optimal Dynamic 2-3 Trees[J]. , 1986, 1(2): 60 -71 .
[4] 刘明业; 洪恩宇;. Some Covering Problems and Their Solutions in Automatic Logic Synthesis Systems[J]. , 1986, 1(2): 83 -92 .
[5] C.Y.Chung; 华宣仁;. A Chinese Information Processing System[J]. , 1986, 1(2): 15 -24 .
[6] 孙钟秀; 商陆军;. DMODULA:A Distributed Programming Language[J]. , 1986, 1(2): 25 -31 .
[7] 陈世华;. On the Structure of (Weak) Inverses of an (Weakly) Invertible Finite Automaton[J]. , 1986, 1(3): 92 -100 .
[8] 高庆狮; 张祥; 杨树范; 陈树清;. Vector Computer 757[J]. , 1986, 1(3): 1 -14 .
[9] 金兰; 杨元元;. A Modified Version of Chordal Ring[J]. , 1986, 1(3): 15 -32 .
[10] 潘启敬;. A Routing Algorithm with Candidate Shortest Path[J]. , 1986, 1(3): 33 -52 .
版权所有 © 《计算机科学技术学报》编辑部
本系统由北京玛格泰克科技发展有限公司设计开发 技术支持：support@magtech.com.cn
总访问量：