{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T13:40:06Z","timestamp":1758721206400,"version":"3.44.0"},"reference-count":73,"publisher":"Association for Computing Machinery (ACM)","issue":"5","funder":[{"name":"JSPS KAKENHI","award":["JP25KJ1297"],"award-info":[{"award-number":["JP25KJ1297"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Sen. Netw."],"published-print":{"date-parts":[[2025,9,30]]},"abstract":"<jats:p>\n            Vital sign detection, based on Channel State Information (CSI) from commercial off-the-shelf (COTS) WiFi devices, has become a popular research area. Previous works in this field mainly focus on respiration, while heartbeat sensing has not been well studied yet, because its signal is very weak and overwhelmed by hardware noises and the respiration signal. Different from existing research that exploits directional antenna, the proposed WiCG (\n            <jats:underline>Wi<\/jats:underline>\n            Fi\n            <jats:underline>C<\/jats:underline>\n            ardio\n            <jats:underline>G<\/jats:underline>\n            ram) system uses common antennas, and not only accurately senses heartbeat rate but also provides the heartbeat signal for further analysis in complex real-life home scenes. Specifically, we first propose an effective denoising solution for Wi-Fi CSI by exploiting its spatial structure, which exhibits strong correlation among the In-phase\/Quadrature components. Leveraging this characteristic with Principal Component Analysis (PCA) achieves effective reduction of ambient noise in both the amplitude and phase of the CSI. Then, we introduce a heartbeat enhancement scheme that utilizes the periodicity of the heartbeat signal. By applying Singular Spectrum Analysis (SSA), the complex effects of residual noise and respiratory interference are effectively mitigated. Extensive experiments have proven that WiCG can effectively sense the heartbeat rate. In a real deployment environment, the average detection error can be reduced to 0.28 bpm, close to current commercial heartbeat sensors.\n          <\/jats:p>\n          <jats:p\/>","DOI":"10.1145\/3748330","type":"journal-article","created":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T15:45:52Z","timestamp":1752162352000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["WiCG: Heartbeat Sensing Using COTS WiFi Devices with Common Antenna"],"prefix":"10.1145","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7159-9140","authenticated-orcid":false,"given":"Youwei","family":"Zhang","sequence":"first","affiliation":[{"name":"The University of Electro-Communications","place":["Chofu, Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0537-4522","authenticated-orcid":false,"given":"Zhi","family":"Liu","sequence":"additional","affiliation":[{"name":"The University of Electro-Communications","place":["Chofu, Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6853-5878","authenticated-orcid":false,"given":"Celimuge","family":"Wu","sequence":"additional","affiliation":[{"name":"The University of Electro-Communications","place":["Chofu, Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4974-6116","authenticated-orcid":false,"given":"Jie","family":"Li","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University","place":["Shanghai, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5784-8411","authenticated-orcid":false,"given":"Suhua","family":"Tang","sequence":"additional","affiliation":[{"name":"The University of Electro-Communications","place":["Chofu, Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,9,24]]},"reference":[{"unstructured":"2019. Ploar H10. Retrieved July 24 2024 from https:\/\/www.polar.com\/en\/sensors\/h10-heart-rate-sensor","key":"e_1_3_2_2_2"},{"unstructured":"2019. Polar H10 Heart Rate Sensor System. Retrieved July 24 2024 from https:\/\/www.polar.com\/sites\/default\/files\/static\/science\/white-papers\/polar-h10-heart-rate-sensor-white-paper.pdf","key":"e_1_3_2_3_2"},{"unstructured":"2019. Polar Sensor Logger. Retrieved July 24 2024 from https:\/\/play.google.com\/store\/apps\/details?id=com.j_ware.polarsensorlogger&pcampaignid=web_share","key":"e_1_3_2_4_2"},{"key":"e_1_3_2_5_2","first-page":"1472","volume-title":"Proceedings of the 2015 IEEE Conference on Computer Communications","author":"Abdelnasser Heba","year":"2015","unstructured":"Heba Abdelnasser, Moustafa Youssef, and Khaled A. Harras. 2015. Wigest: A ubiquitous wifi-based gesture recognition system. In Proceedings of the 2015 IEEE Conference on Computer Communications. IEEE, 1472\u20131480."},{"doi-asserted-by":"publisher","key":"e_1_3_2_6_2","DOI":"10.1145\/2702123.2702200"},{"issue":"6","key":"e_1_3_2_7_2","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1016\/j.numecd.2017.04.004","article-title":"Resting heart rate and the risk of cardiovascular disease, total cancer, and all-cause mortality\u2013a systematic review and dose\u2013response meta-analysis of prospective studies","volume":"27","author":"Aune Dagfinn","year":"2017","unstructured":"Dagfinn Aune, Abhijit Sen, Br\u00edain \u00f3\u2019Hartaigh, Imre Janszky, P\u00e5l R. Romundstad, Serena Tonstad, and Lars J. Vatten. 2017. Resting heart rate and the risk of cardiovascular disease, total cancer, and all-cause mortality\u2013a systematic review and dose\u2013response meta-analysis of prospective studies. Nutrition, Metabolism and Cardiovascular Diseases 27, 6 (2017), 504\u2013517.","journal-title":"Nutrition, Metabolism and Cardiovascular Diseases"},{"issue":"4","key":"e_1_3_2_8_2","doi-asserted-by":"crossref","first-page":"436","DOI":"10.5958\/2394-2126.2016.00099.2","article-title":"Relation between respiratory rate and heart rate\u2013a comparative study","volume":"3","author":"Bahmed Farah","year":"2016","unstructured":"Farah Bahmed, Farisa Khatoon, B. Ram Reddy, and Farah Bahmed. 2016. Relation between respiratory rate and heart rate\u2013a comparative study. Indian Journal of Clinical Anatomy and Physiology 3, 4 (2016), 436\u2013439.","journal-title":"Indian Journal of Clinical Anatomy and Physiology"},{"issue":"2","key":"e_1_3_2_9_2","article-title":"Nocturnal heart rate variability in obstructive sleep apnoea: A cross-sectional analysis of the sleep heart health study","volume":"12","author":"Bradicich Matteo","year":"2020","unstructured":"Matteo Bradicich, Noriane A. Sievi, Fabian A. Grewe, Alessio Gasperetti, Malcolm Kohler, and Esther I. Schwarz. 2020. Nocturnal heart rate variability in obstructive sleep apnoea: A cross-sectional analysis of the sleep heart health study. Journal of Thoracic Disease 12, Suppl 2 (2020), S129\u2013S138. Retrieved from https:\/\/jtd.amegroups.org\/article\/view\/44697","journal-title":"Journal of Thoracic Disease"},{"doi-asserted-by":"publisher","key":"e_1_3_2_10_2","DOI":"10.1109\/TBME.2017.2699422"},{"key":"e_1_3_2_11_2","first-page":"349","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Chen Weixuan","year":"2018","unstructured":"Weixuan Chen and Daniel McDuff. 2018. Deepphys: Video-based physiological measurement using convolutional attention networks. In Proceedings of the European Conference on Computer Vision. 349\u2013365."},{"doi-asserted-by":"publisher","key":"e_1_3_2_12_2","DOI":"10.1145\/3447993.3483251"},{"doi-asserted-by":"publisher","key":"e_1_3_2_13_2","DOI":"10.1016\/j.jjcc.2013.02.018"},{"key":"e_1_3_2_14_2","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.physbeh.2016.03.006","article-title":"Measures of sleep and cardiac functioning during sleep using a multi-sensory commercially-available wristband in adolescents","volume":"158","author":"Zambotti Massimiliano de","year":"2016","unstructured":"Massimiliano de Zambotti, Fiona C. Baker, Adrian R. Willoughby, Job G. Godino, David Wing, Kevin Patrick, and Ian M. Colrain. 2016. Measures of sleep and cardiac functioning during sleep using a multi-sensory commercially-available wristband in adolescents. Physiology and Behavior 158 (2016), 143\u2013149.","journal-title":"Physiology and Behavior"},{"key":"e_1_3_2_15_2","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1109\/RWS45077.2020.9050134","volume-title":"Proceedings of the 2020 IEEE Radio and Wireless Symposium","author":"Dong Shuqin","year":"2020","unstructured":"Shuqin Dong, Yi Zhang, Chao Ma, Qinyi Lv, Changzhi Li, and Lixin Ran. 2020. Cardiogram detection with a millimeter-wave radar sensor. In Proceedings of the 2020 IEEE Radio and Wireless Symposium. IEEE, 127\u2013129."},{"doi-asserted-by":"publisher","key":"e_1_3_2_16_2","DOI":"10.1109\/TSP.2013.2288675"},{"issue":"19","key":"e_1_3_2_17_2","first-page":"e558\u2013e577","article-title":"Projected costs of informal caregiving for cardiovascular disease: 2015 to 2035: A policy statement from the American heart association","volume":"137","author":"Dunbar Sandra B.","year":"2018","unstructured":"Sandra B. Dunbar, Olga A. Khavjou, Tamilyn Bakas, Gail Hunt, Rebecca A. Kirch, Alyssa R. Leib, R. Sean Morrison, Diana C. Poehler, Veronique L. Roger, and Laurie P. Whitsel. 2018. Projected costs of informal caregiving for cardiovascular disease: 2015 to 2035: A policy statement from the American heart association. Circulation 137, 19 (2018), e558\u2013e577.","journal-title":"Circulation"},{"doi-asserted-by":"publisher","key":"e_1_3_2_18_2","DOI":"10.1093\/sleep\/22.8.1067"},{"doi-asserted-by":"publisher","key":"e_1_3_2_19_2","DOI":"10.1016\/j.jacc.2007.04.079"},{"doi-asserted-by":"publisher","key":"e_1_3_2_20_2","DOI":"10.1145\/3555600"},{"key":"e_1_3_2_21_2","volume-title":"Analysis of Time Series Structure: SSA and Related Techniques","author":"Golyandina Nina","year":"2001","unstructured":"Nina Golyandina, Vladimir Nekrutkin, and Anatoly A. Zhigljavsky. 2001. Analysis of Time Series Structure: SSA and Related Techniques. CRC press."},{"doi-asserted-by":"publisher","key":"e_1_3_2_22_2","DOI":"10.1016\/j.sleep.2013.11.321"},{"issue":"19","key":"e_1_3_2_23_2","doi-asserted-by":"crossref","first-page":"7873","DOI":"10.1175\/JCLI-D-15-0100.1","article-title":"Monte carlo singular spectrum analysis (SSA) revisited: Detecting oscillator clusters in multivariate datasets","volume":"28","author":"Groth Andreas","year":"2015","unstructured":"Andreas Groth and Michael Ghil. 2015. Monte carlo singular spectrum analysis (SSA) revisited: Detecting oscillator clusters in multivariate datasets. Journal of Climate 28, 19 (2015), 7873\u20137893.","journal-title":"Journal of Climate"},{"doi-asserted-by":"publisher","key":"e_1_3_2_24_2","DOI":"10.1145\/3372224.3419982"},{"doi-asserted-by":"publisher","key":"e_1_3_2_25_2","DOI":"10.1145\/1925861.1925870"},{"doi-asserted-by":"publisher","key":"e_1_3_2_26_2","DOI":"10.1145\/3659595"},{"doi-asserted-by":"publisher","key":"e_1_3_2_27_2","DOI":"10.1183\/23120541.00121-2022"},{"doi-asserted-by":"publisher","key":"e_1_3_2_28_2","DOI":"10.5555\/555620"},{"key":"e_1_3_2_29_2","first-page":"3896","volume-title":"Proceedings of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society","author":"Hu Jingjing","year":"2019","unstructured":"Jingjing Hu, Yunze He, Jie Liu, Min He, and Wenjin Wang. 2019. Illumination robust heart-rate extraction from single-wavelength infrared camera using spatial-channel expansion. In Proceedings of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 3896\u20133899."},{"doi-asserted-by":"publisher","key":"e_1_3_2_30_2","DOI":"10.1098\/rspa.1998.0193"},{"doi-asserted-by":"publisher","key":"e_1_3_2_31_2","DOI":"10.1016\/S0893-6080(00)00026-5"},{"issue":"1","key":"e_1_3_2_32_2","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1080\/00365513.2019.1566567","article-title":"Resting heart rate and relation to disease and longevity: Past, present and future","volume":"79","author":"Jensen Magnus T.","year":"2019","unstructured":"Magnus T. Jensen. 2019. Resting heart rate and relation to disease and longevity: Past, present and future. Scandinavian Journal of Clinical and Laboratory Investigation 79, 1-2 (2019), 108\u2013116.","journal-title":"Scandinavian Journal of Clinical and Laboratory Investigation"},{"issue":"2","key":"e_1_3_2_33_2","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1016\/S0008-6363(01)00230-9","article-title":"Resting heart rate as a predictive risk factor for sudden death in middle-aged men","volume":"50","author":"Jouven Xavier","year":"2001","unstructured":"Xavier Jouven, Mahmoud Zureik, Michel Desnos, Claude Gu\u00e9rot, and Pierre Ducimeti\u00e8re. 2001. Resting heart rate as a predictive risk factor for sudden death in middle-aged men. Cardiovascular Research 50, 2 (2001), 373\u2013378.","journal-title":"Cardiovascular Research"},{"issue":"2","key":"e_1_3_2_34_2","first-page":"87","article-title":"Comparison of smart watch based pulse rate variability with heart rate variability","volume":"39","author":"Kim Changjin","year":"2018","unstructured":"Changjin Kim and Jihwan Woo. 2018. Comparison of smart watch based pulse rate variability with heart rate variability. Journal of Biomedical Engineering Research 39, 2 (2018), 87\u201393.","journal-title":"Journal of Biomedical Engineering Research"},{"issue":"10","key":"e_1_3_2_35_2","doi-asserted-by":"crossref","first-page":"1327","DOI":"10.1093\/eurheartj\/ehn123","article-title":"Impact of resting heart rate on outcomes in hypertensive patients with coronary artery disease: Findings from the INternational VErapamil-SR\/trandolapril STudy (INVEST)","volume":"29","author":"Kolloch Rainer","year":"2008","unstructured":"Rainer Kolloch, Udo F Legler, Annette Champion, Rhonda M Cooper-DeHoff, Eileen Handberg, Qian Zhou, and Carl J Pepine. 2008. Impact of resting heart rate on outcomes in hypertensive patients with coronary artery disease: Findings from the INternational VErapamil-SR\/trandolapril STudy (INVEST). European Heart Journal 29, 10 (2008), 1327\u20131334.","journal-title":"European Heart Journal"},{"issue":"2","key":"e_1_3_2_36_2","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1053\/euhj.1999.1741","article-title":"The association of resting heart rate with cardiovascular, cancer and all-cause mortality. Eight year follow-up of 3527 male israeli employees (the CORDIS study)","volume":"21","author":"Kristal-Boneh E.","year":"2000","unstructured":"E. Kristal-Boneh, H. Silber, G. Harari, and P. Froom. 2000. The association of resting heart rate with cardiovascular, cancer and all-cause mortality. Eight year follow-up of 3527 male israeli employees (the CORDIS study). European Heart Journal 21, 2 (2000), 116\u2013124.","journal-title":"European Heart Journal"},{"doi-asserted-by":"publisher","key":"e_1_3_2_37_2","DOI":"10.1145\/3411834"},{"issue":"3","key":"e_1_3_2_38_2","first-page":"1","article-title":"IndoTrack: Device-free indoor human tracking with commodity Wi-Fi","volume":"1","author":"Li Xiang","year":"2017","unstructured":"Xiang Li, Daqing Zhang, Qin Lv, Jie Xiong, Shengjie Li, Yue Zhang, and Hong Mei. 2017. IndoTrack: Device-free indoor human tracking with commodity Wi-Fi. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, 3 (2017), 1\u201322.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"e_1_3_2_39_2","article-title":"A handwriting recognition system with WiFi","author":"Lin Chi","year":"2023","unstructured":"Chi Lin, Asfandeyar Ahmad, Rongsheng Qu, Yi Wang, Lei Wang, Guowei Wu, Qiang Lin, and Qiang Zhang. 2023. A handwriting recognition system with WiFi. IEEE Transactions on Mobile Computing 23, 4 (2023), 3391\u20133409.","journal-title":"IEEE Transactions on Mobile Computing"},{"doi-asserted-by":"publisher","key":"e_1_3_2_40_2","DOI":"10.1145\/3117811.3117839"},{"doi-asserted-by":"publisher","key":"e_1_3_2_41_2","DOI":"10.1145\/2746285.2746303"},{"issue":"1","key":"e_1_3_2_42_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3448092","article-title":"WiPhone: Smartphone-based respiration monitoring using ambient reflected WiFi signals","volume":"5","author":"Liu Jinyi","year":"2021","unstructured":"Jinyi Liu, Youwei Zeng, Tao Gu, Leye Wang, and Daqing Zhang. 2021. WiPhone: Smartphone-based respiration monitoring using ambient reflected WiFi signals. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, 1 (2021), 1\u201319.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"e_1_3_2_43_2","volume-title":"StatPearls [Internet]","author":"Lopez Edgardo Olvera","year":"2023","unstructured":"Edgardo Olvera Lopez, Brian D. Ballard, and Arif Jan. 2023. Cardiovascular disease. In StatPearls [Internet]. StatPearls Publishing."},{"doi-asserted-by":"publisher","key":"e_1_3_2_44_2","DOI":"10.1016\/S0140-6736(12)61728-0"},{"doi-asserted-by":"publisher","key":"e_1_3_2_45_2","DOI":"10.3390\/s21030751"},{"issue":"2","key":"e_1_3_2_46_2","first-page":"022707","article-title":"HRVCam: Robust camera-based measurement of heart rate variability","volume":"26","author":"Pai Amruta","year":"2021","unstructured":"Amruta Pai, Ashok Veeraraghavan, and Ashutosh Sabharwal. 2021. HRVCam: Robust camera-based measurement of heart rate variability. Journal of Biomedical Optics 26, 2 (2021), 022707\u2013022707.","journal-title":"Journal of Biomedical Optics"},{"doi-asserted-by":"publisher","key":"e_1_3_2_47_2","DOI":"10.1145\/3161183"},{"doi-asserted-by":"publisher","key":"e_1_3_2_48_2","DOI":"10.4322\/2675-9977.cpcr.42591"},{"doi-asserted-by":"publisher","key":"e_1_3_2_49_2","DOI":"10.1109\/INFOCOM.2018.8485978"},{"key":"e_1_3_2_50_2","first-page":"1","volume-title":"Proceedings of the 2019 13th International Conference on Signal Processing and Communication Systems","author":"Raheel Muhammad Salman","year":"2019","unstructured":"Muhammad Salman Raheel, James Coyte, Faisel Tubbal, Raad Raad, Philip Ogunbona, Christopher Patterson, and Dana Perlman. 2019. Breathing and heartrate monitoring system using IR-UWB radar. In Proceedings of the 2019 13th International Conference on Signal Processing and Communication Systems. IEEE, 1\u20135."},{"issue":"7","key":"e_1_3_2_51_2","first-page":"573","article-title":"Association of resting heart rate and hypertension stages on all-cause and cardiovascular mortality among elderly koreans: The kangwha cohort study","volume":"13","author":"Ryu Mikyung","year":"2016","unstructured":"Mikyung Ryu, Gombojav Bayasgalan, Heejin Kimm, Chung Mo Nam, and Heechoul Ohrr. 2016. Association of resting heart rate and hypertension stages on all-cause and cardiovascular mortality among elderly koreans: The kangwha cohort study. Journal of Geriatric Cardiology: JGC 13, 7 (2016), 573.","journal-title":"Journal of Geriatric Cardiology: JGC"},{"issue":"17","key":"e_1_3_2_52_2","doi-asserted-by":"crossref","first-page":"6536","DOI":"10.3390\/s22176536","article-title":"Validity of the polar H10 sensor for heart rate variability analysis during resting state and incremental exercise in recreational men and women","volume":"22","author":"Schaffarczyk Marcelle","year":"2022","unstructured":"Marcelle Schaffarczyk, Bruce Rogers, R\u00fcdiger Reer, and Thomas Gronwald. 2022. Validity of the polar H10 sensor for heart rate variability analysis during resting state and incremental exercise in recreational men and women. Sensors 22, 17 (2022), 6536.","journal-title":"Sensors"},{"doi-asserted-by":"publisher","key":"e_1_3_2_53_2","DOI":"10.1007\/BFb0020217"},{"issue":"1","key":"e_1_3_2_54_2","doi-asserted-by":"crossref","first-page":"5093","DOI":"10.1038\/srep05093","article-title":"Surface chest motion decomposition for cardiovascular monitoring","volume":"4","author":"Shafiq Ghufran","year":"2014","unstructured":"Ghufran Shafiq and Kalyana C. Veluvolu. 2014. Surface chest motion decomposition for cardiovascular monitoring. Scientific Reports 4, 1 (2014), 5093.","journal-title":"Scientific Reports"},{"doi-asserted-by":"publisher","key":"e_1_3_2_55_2","DOI":"10.1145\/2987354.2987360"},{"doi-asserted-by":"publisher","key":"e_1_3_2_56_2","DOI":"10.1016\/j.sleep.2018.09.014"},{"doi-asserted-by":"publisher","key":"e_1_3_2_57_2","DOI":"10.1145\/2971648.2971744"},{"doi-asserted-by":"publisher","key":"e_1_3_2_58_2","DOI":"10.1109\/TMC.2016.2557795"},{"doi-asserted-by":"publisher","key":"e_1_3_2_59_2","DOI":"10.1145\/3581791.3596867"},{"issue":"3","key":"e_1_3_2_60_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3550293","article-title":"Loear: Push the range limit of acoustic sensing for vital sign monitoring","volume":"6","author":"Wang Lei","year":"2022","unstructured":"Lei Wang, Wei Li, Ke Sun, Fusang Zhang, Tao Gu, Chenren Xu, and Daqing Zhang. 2022. Loear: Push the range limit of acoustic sensing for vital sign monitoring. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 6, 3 (2022), 1\u201324.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"doi-asserted-by":"publisher","key":"e_1_3_2_61_2","DOI":"10.1145\/2971648.2971670"},{"key":"e_1_3_2_62_2","first-page":"1230","volume-title":"Proceedings of the 2017 IEEE 37th International Conference on Distributed Computing Systems","author":"Wang Xuyu","year":"2017","unstructured":"Xuyu Wang, Chao Yang, and Shiwen Mao. 2017. PhaseBeat: Exploiting CSI phase data for vital sign monitoring with commodity WiFi devices. In Proceedings of the 2017 IEEE 37th International Conference on Distributed Computing Systems. IEEE, 1230\u20131239."},{"issue":"1","key":"e_1_3_2_63_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3380981","article-title":"FingerDraw: Sub-wavelength level finger motion tracking with WiFi signals","volume":"4","author":"Wu Dan","year":"2020","unstructured":"Dan Wu, Ruiyang Gao, Youwei Zeng, Jinyi Liu, Leye Wang, Tao Gu, and Daqing Zhang. 2020. FingerDraw: Sub-wavelength level finger motion tracking with WiFi signals. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, 1 (2020), 1\u201327.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"e_1_3_2_64_2","first-page":"149","volume-title":"Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems","author":"Xu Chenhan","year":"2022","unstructured":"Chenhan Xu, Tianyu Chen, Huining Li, Alexander Gherardi, Michelle Weng, Zhengxiong Li, and Wenyao Xu. 2022. Hearing heartbeat from voice: Towards next generation voice-user interfaces with cardiac sensing functions. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems. 149\u2013163."},{"doi-asserted-by":"publisher","key":"e_1_3_2_65_2","DOI":"10.1109\/INFOCOM48880.2022.9796912"},{"doi-asserted-by":"publisher","key":"e_1_3_2_66_2","DOI":"10.1145\/3051124"},{"issue":"4","key":"e_1_3_2_67_2","first-page":"1","article-title":"Enabling WiFi sensing on new-generation WiFi cards","volume":"7","author":"Yi Enze","year":"2024","unstructured":"Enze Yi, Fusang Zhang, Jie Xiong, Kai Niu, Zhiyun Yao, and Daqing Zhang. 2024. Enabling WiFi sensing on new-generation WiFi cards. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 7, 4 (2024), 1\u201326.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"doi-asserted-by":"publisher","key":"e_1_3_2_68_2","DOI":"10.1109\/ICCV.2019.00024"},{"key":"e_1_3_2_69_2","first-page":"7004","volume-title":"Proceedings of the 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","author":"Zanetti John M.","year":"2013","unstructured":"John M. Zanetti and Kouhyar Tavakolian. 2013. Seismocardiography: Past, present and future. In Proceedings of the 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 7004\u20137007."},{"doi-asserted-by":"publisher","key":"e_1_3_2_70_2","DOI":"10.1145\/3411816"},{"doi-asserted-by":"publisher","key":"e_1_3_2_71_2","DOI":"10.1145\/3351279"},{"doi-asserted-by":"publisher","key":"e_1_3_2_72_2","DOI":"10.1145\/3432237"},{"doi-asserted-by":"publisher","key":"e_1_3_2_73_2","DOI":"10.1145\/3632958"},{"doi-asserted-by":"publisher","key":"e_1_3_2_74_2","DOI":"10.1145\/3397321"}],"container-title":["ACM Transactions on Sensor Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3748330","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T13:07:26Z","timestamp":1758719246000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3748330"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,24]]},"references-count":73,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,9,30]]}},"alternative-id":["10.1145\/3748330"],"URL":"https:\/\/doi.org\/10.1145\/3748330","relation":{},"ISSN":["1550-4859","1550-4867"],"issn-type":[{"type":"print","value":"1550-4859"},{"type":"electronic","value":"1550-4867"}],"subject":[],"published":{"date-parts":[[2025,9,24]]},"assertion":[{"value":"2024-08-17","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-01","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-09-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}