{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,22]],"date-time":"2025-07-22T11:18:42Z","timestamp":1753183122240,"version":"3.41.0"},"reference-count":39,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2023,1,14]],"date-time":"2023-01-14T00:00:00Z","timestamp":1673654400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62072040"],"award-info":[{"award-number":["62072040"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Sen. Netw."],"published-print":{"date-parts":[[2023,2,28]]},"abstract":"<jats:p>Sound-related respiratory symptoms are commonly observed in our daily lives. They are closely related to illnesses, infections, or allergies but ignored by the majority. Existing detection methods either depend on specific devices, which are inconvenient to wear, or are sensitive to noises and only work for indoor environment. Considering the lack of monitoring method for in-car environment, where there is high risk of spreading infectious diseases, we propose a smartphone-based system, named SymListener, to detect respiratory symptoms in driving environment. By continuously recording acoustic data through a built-in microphone, SymListener can detect the sounds of cough, sneeze, and sniffle. We design a modified ABSE-based method to remove the strong and changeable driving noises while saving energy of the smartphone. An LSTM network is adopted to classify the three types of symptoms according to the carefully designed acoustic features. We implement SymListener on different Android devices and evaluate its performance in real driving environment. The evaluation results show that SymListener can reliably detect target respiratory symptoms with an average accuracy of 92.19% and an average precision of 90.91%.<\/jats:p>","DOI":"10.1145\/3517014","type":"journal-article","created":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T11:34:20Z","timestamp":1657884860000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["SymListener: Detecting Respiratory Symptoms via Acoustic Sensing in Driving Environments"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8306-2252","authenticated-orcid":false,"given":"Yue","family":"Wu","sequence":"first","affiliation":[{"name":"Tsinghua University, Shuangqing Rd, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2348-4488","authenticated-orcid":false,"given":"Fan","family":"Li","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology, Zhongguancun South Rd, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2467-4240","authenticated-orcid":false,"given":"Yadong","family":"Xie","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology, Zhongguancun South Rd, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3511-0288","authenticated-orcid":false,"given":"Yu","family":"Wang","sequence":"additional","affiliation":[{"name":"Temple University, Philadelphia, Pennsylvania, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4048-2684","authenticated-orcid":false,"given":"Zheng","family":"Yang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Shuangqing Rd, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2023,1,14]]},"reference":[{"key":"e_1_3_1_2_2","first-page":"49","volume-title":"International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT\u201919)","author":"Akhil S. Sairam","year":"2019","unstructured":"S. Sairam Akhil, N. Arun Vignesh, Sudharsan Jayabalan, E. Karthikeyan, Ayyem Pillai V., Ch. Usha Kumari, and Asisa Kumar Panigrahy. 2019. A novel approach for detection of the symptomatic patterns in the acoustic biological signal using truncation multiplier. In International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT\u201919). IEEE, 49\u201353."},{"key":"e_1_3_1_3_2","first-page":"3666","volume-title":"International Conference of the IEEE Engineering in Medicine and Biology (EMBC\u201910)","author":"Azarbarzin Ali","year":"2010","unstructured":"Ali Azarbarzin and Zahra Moussavi. 2010. Unsupervised classification of respiratory sound signal into snore\/no-snore classes. In International Conference of the IEEE Engineering in Medicine and Biology (EMBC\u201910). IEEE, 3666\u20133669."},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1186\/1745-9974-2-8"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1186\/1745-9974-8-12"},{"key":"e_1_3_1_6_2","first-page":"1","volume-title":"EAI International Conference on Pervasive Computing Technologies for Healthcare - Demos and Posters (PervasiveHealth\u201919)","author":"Chatterjee Soujanya","year":"2019","unstructured":"Soujanya Chatterjee, Md Mahbubur Rahman, Ebrahim Nemanti, and Jilong Kuang. 2019. WheezeD: Respiration phase based wheeze detection using acoustic data from pulmonary patients under attack. In EAI International Conference on Pervasive Computing Technologies for Healthcare - Demos and Posters (PervasiveHealth\u201919). EAI, 1\u20134."},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/jbhi.2013.2239303"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10439-009-9830-y"},{"key":"e_1_3_1_9_2","first-page":"1","volume-title":"ACM Conference on Embedded Network Sensor Systems (SenSys\u201913)","author":"Hao Tian","year":"2013","unstructured":"Tian Hao, Guoliang Xing, and Gang Zhou. 2013. iSleep: Unobtrusive sleep quality monitoring using smartphones. In ACM Conference on Embedded Network Sensor Systems (SenSys\u201913). ACM, 1\u201314."},{"key":"e_1_3_1_10_2","unstructured":"Healthgrades. 2020. Respiratory Symptoms. Retrieved from https:\/\/www.healthgrades.com\/right-care\/lungs-breathing-and-respiration\/respiratory-symptoms."},{"key":"e_1_3_1_11_2","unstructured":"Healthline. 2020. What causes sniffling and how to stop. Retrieved from https:\/\/www.healthline.com\/health\/sniffles."},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1006\/pulp.1996.0034"},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1152\/japplphysiol.00273.2006"},{"key":"e_1_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.21037\/jtd.2016.11.02"},{"key":"e_1_3_1_15_2","first-page":"375","volume-title":"International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp\u201911)","author":"Larson Eric","year":"2011","unstructured":"Eric Larson, Tien Jui Lee, Sean Liu, Margaret Rosenfeld, and Shwetak Patel. 2011. Accurate and privacy preserving cough sensing using a low-cost microphone. In International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp\u201911). ACM, New York, NY, 375\u2013384."},{"key":"e_1_3_1_16_2","first-page":"1095","volume-title":"International Conference on Computer Communication and Networks (ICCCN\u201918)","author":"Li Hanshang","year":"2018","unstructured":"Hanshang Li, Ting Li, Fan Li, Yue Wu, and Yu Wang. 2018. Cumulative participant selection with switch costs in large-scale mobile crowd sensing. In International Conference on Computer Communication and Networks (ICCCN\u201918). IEEE, 1095\u20132055."},{"key":"e_1_3_1_17_2","first-page":"36","volume-title":"International Conference on Life System Modeling and Simulation (LSMS\u201907)","author":"Li Xin","year":"2007","unstructured":"Xin Li, Huaping Liu, Yu Zheng, and Bolin Xu. 2007. Robust speech endpoint detection based on improved adaptive band-partitioning spectral entropy. In International Conference on Life System Modeling and Simulation (LSMS\u201907). Springer, 36\u201345."},{"key":"e_1_3_1_18_2","first-page":"1123","volume-title":"IEEE Conference on Computer Communications (INFOCOM\u201920)","author":"Liu Chi Harold","year":"2020","unstructured":"Chi Harold Liu, Zipeng Dai, Haoming Yang, and Jian Tang. 2020. Multi-task-oriented vehicular crowdsensing: A deep learning approach. In IEEE Conference on Computer Communications (INFOCOM\u201920). IEEE, 1123\u20131132."},{"key":"e_1_3_1_19_2","first-page":"165","volume-title":"International Conference on Mobile Systems, Applications, and Services (MobiSys\u201909)","author":"Lu Hong","year":"2009","unstructured":"Hong Lu, Wei Pan, Nicholas D. Lane, Tanzeem Choudhury, and Andrew T. Campbell. 2009. SoundSense: Scalable sound sensing for people-centric applications on mobile phones. In International Conference on Mobile Systems, Applications, and Services (MobiSys\u201909). ACM, 165\u2013178."},{"key":"e_1_3_1_20_2","unstructured":"Lyft. 2018. Safety policies. Retrieved from https:\/\/help.lyft.com\/hc\/en-us\/articles\/115012923127-Safety-policies#nosmoking."},{"key":"e_1_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2018.2800741"},{"key":"e_1_3_1_22_2","first-page":"45","volume-title":"International Conference on Mobile Systems, Applications, and Services (MobiSys\u201915)","author":"Nandakumar Rajalakshmi","year":"2015","unstructured":"Rajalakshmi Nandakumar, Shyamnath Gollakota, and Nathaniel Watson. 2015. Contactless sleep apnea detection on smartphones. In International Conference on Mobile Systems, Applications, and Services (MobiSys\u201915). ACM, New York, NY, 45\u201357."},{"key":"e_1_3_1_23_2","first-page":"221","volume-title":"EAI International Conference on Body Area Networks (BODYNETS\u201920)","author":"Nemati Ebrahim","year":"2018","unstructured":"Ebrahim Nemati, Md Mahbubur Rahman, Viswam Nathan, and Jilong Kuang. 2018. Private audio-based cough sensing for in-home pulmonary assessment using mobile devices. In EAI International Conference on Body Area Networks (BODYNETS\u201920). EAI, 221\u2013232."},{"key":"e_1_3_1_24_2","unstructured":"USD of Transportation. 2019. Ratings. Retrieved from https:\/\/www.nhtsa.gov\/ratings."},{"key":"e_1_3_1_25_2","first-page":"305","volume-title":"IEEE International Symposium on Circuits and Systems (ISCAS\u201913)","author":"Qi Jun","year":"2013","unstructured":"Jun Qi, Dong Wang, Yi Jiang, and Runsheng Liu. 2013. Auditory features based on Gammatone filters for robust speech recognition. In IEEE International Symposium on Circuits and Systems (ISCAS\u201913). IEEE, 305\u2013308."},{"key":"e_1_3_1_26_2","first-page":"1574","volume-title":"IEEE Conference on Computer Communications (INFOCOM\u201918)","author":"Qian Kun","year":"2018","unstructured":"Kun Qian, Chenshu Wu, Fu Xiao, Yue Zheng, Yi Zhang, Zheng Yang, and Yunhao Liu. 2018. Acousticcardiogram: Monitoring heartbeats using acoustic signals on smart devices. In IEEE Conference on Computer Communications (INFOCOM\u201918). IEEE, 1574\u20131582."},{"key":"e_1_3_1_27_2","first-page":"1","volume-title":"International Conference on Ambient Computing, Applications, Services and Technologies (AMBIENT\u201919)","author":"Rahman Md Juber","year":"2019","unstructured":"Md Juber Rahman, Ebrahim Nemati, Mahbubur Rahman, and Korosh Vatanparvar. 2019. Efficient online cough detection with a minimal feature set using smartphones for automated assessment of pulmonary patients. In International Conference on Ambient Computing, Applications, Services and Technologies (AMBIENT\u201919). IARIA XPS Press, 1\u20137."},{"key":"e_1_3_1_28_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2017.2737621"},{"key":"e_1_3_1_29_2","first-page":"97","volume-title":"International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp\u201915)","author":"Sun Xiao","year":"2015","unstructured":"Xiao Sun, Zongqing Lu, Wenjie Hu, and Guohong Cao. 2015. SymDetector: Detecting sound-related respiratory symptoms using smartphones. In International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp\u201915). ACM, 97\u2013108."},{"key":"e_1_3_1_30_2","first-page":"1","volume-title":"International Workshop on Emerging Mobile Sensing Technologies, Systems, and Applications (MobiSense\u201911)","author":"Sun Zheng","year":"2011","unstructured":"Zheng Sun, Aveek Purohit, Kathleen Yang, Neha Pattan, Dan Siewiorek, Asim Smailagic, Ian Lane, and Pei Zhang. 2011. CoughLoc: Location-aware indoor acoustic sensing for non-intrusive cough detection. In International Workshop on Emerging Mobile Sensing Technologies, Systems, and Applications (MobiSense\u201911). 1\u20137."},{"key":"e_1_3_1_31_2","doi-asserted-by":"crossref","first-page":"1043","DOI":"10.21437\/ICSLP.1994-275","volume-title":"International Conference on Spoken Language Processing (ICSLP\u201994)","author":"Tokuda Keiichi","year":"1994","unstructured":"Keiichi Tokuda, Takao Kobayashi, Takashi Masuko, and Satoshi Imai. 1994. Mel generalized cepstral analysis\u2014Unified approach to speech spectral estimation. In International Conference on Spoken Language Processing (ICSLP\u201994). INTERSPEECH, 1043\u20131046."},{"key":"e_1_3_1_32_2","first-page":"1","volume-title":"IEEE International Conference on Wearable and Implantable Body Sensor Networks (BSN\u201919)","author":"Vatanparvar Korosh","year":"2019","unstructured":"Korosh Vatanparvar, Viswam Nathan, Ebrahim Nemati, Md Mahbubur Rahman, and Jilong Kuang. 2019. A generative model for speech segmentation and obfuscation for remote health monitoring. In IEEE International Conference on Wearable and Implantable Body Sensor Networks (BSN\u201919). IEEE, 1\u20134."},{"key":"e_1_3_1_33_2","doi-asserted-by":"publisher","DOI":"10.1186\/1745-9974-6-3"},{"key":"e_1_3_1_34_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13246-016-0507-1"},{"key":"e_1_3_1_35_2","doi-asserted-by":"publisher","DOI":"10.1145\/3161188"},{"key":"e_1_3_1_36_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSA.2005.851909"},{"key":"e_1_3_1_37_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2903197"},{"key":"e_1_3_1_38_2","first-page":"1","volume-title":"IEEE Conference on Computer Communications (INFOCOM\u201921)","author":"Xie Yadong","year":"2021","unstructured":"Yadong Xie, Fan Li, Yue Wu, and Yu Wang. 2021. HearFit: Fitness monitoring on smart speakers via active acoustic sensing. In IEEE Conference on Computer Communications (INFOCOM\u201921). IEEE, 1\u20131."},{"key":"e_1_3_1_39_2","first-page":"1225","volume-title":"IEEE Conference on Computer Communications (INFOCOM\u201919)","author":"Xie Yadong","year":"2019","unstructured":"Yadong Xie, Fan Li, Yue Wu, Song Yang, and Yu Wang. 2019. \\( D^3 \\) -Guard: Acoustic-based drowsy driving detection using smartphones. In IEEE Conference on Computer Communications (INFOCOM\u201919). IEEE, 1225\u20131233."},{"key":"e_1_3_1_40_2","first-page":"54","volume-title":"International Conference on Mobile Systems, Applications, and Services (MobiSys\u201919)","author":"Xu Xiangyu","year":"2019","unstructured":"Xiangyu Xu, Jiadi Yu, Yingying Chen, Yanmin Zhu, Linghe Kong, and Minglu Li. 2019. BreathListener: Fine-grained breathing monitoring in driving environments utilizing acoustic signals. In International Conference on Mobile Systems, Applications, and Services (MobiSys\u201919). ACM, New York, NY, 54\u201366."}],"container-title":["ACM Transactions on Sensor Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3517014","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3517014","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:08:59Z","timestamp":1750183739000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3517014"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,14]]},"references-count":39,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,2,28]]}},"alternative-id":["10.1145\/3517014"],"URL":"https:\/\/doi.org\/10.1145\/3517014","relation":{},"ISSN":["1550-4859","1550-4867"],"issn-type":[{"type":"print","value":"1550-4859"},{"type":"electronic","value":"1550-4867"}],"subject":[],"published":{"date-parts":[[2023,1,14]]},"assertion":[{"value":"2021-09-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-02-02","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-01-14","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}