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Syst."],"published-print":{"date-parts":[[2021,3,31]]},"abstract":"<jats:p>Annotating activities of daily living (ADL) is vital for developing machine learning models for activity recognition. In addition, it is critical for self-reporting purposes such as in assisted living where the users are asked to log their ADLs. However, data annotation becomes extremely challenging in real-world data collection scenarios, where the users have to provide annotations and labels on their own. Methods such as self-reports that rely on users\u2019 memory and compliance are prone to human errors and become burdensome since they increase users\u2019 cognitive load. In this article, we propose a light yet effective context-aware change point detection algorithm that is implemented and run on a smartwatch for facilitating data annotation for high-level ADLs. The proposed system detects the moments of transition from one to another activity and prompts the users to annotate their data. We leverage freely available Bluetooth low energy (BLE) information broadcasted by various devices to detect changes in environmental context. This contextual information is combined with a motion-based change point detection algorithm, which utilizes data from wearable motion sensors, to reduce the false positives and enhance the system's accuracy. Through real-world experiments, we show that the proposed system improves the quality and quantity of labels collected from users by reducing human errors while eliminating users\u2019 cognitive load and facilitating the data annotation process.<\/jats:p>","DOI":"10.1145\/3431503","type":"journal-article","created":{"date-parts":[[2021,1,12]],"date-time":"2021-01-12T06:34:09Z","timestamp":1610433249000},"page":"1-20","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Facilitating Human Activity Data Annotation via Context-Aware Change Detection on Smartwatches"],"prefix":"10.1145","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1387-1174","authenticated-orcid":false,"given":"Ali","family":"Akbari","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, Texas A8M University, College Station, Texas, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathan","family":"Martinez","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Texas A8M University, College Station, Texas, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roozbeh","family":"Jafari","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Computer Science and Engineering, and Electrical and Computer Engineering, Texas A8 University, College Station, Texas, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2021,1,11]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.archger.2012.02.006"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12199-008-0072-7"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2018.2841905"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1117\/12.2325577"},{"key":"e_1_2_1_5_1","volume-title":"Proceedings of the 2016 19th International Conference on Information Fusion (Fusion). 371--378","author":"Davis K.","year":"2016"},{"key":"e_1_2_1_6_1","volume-title":"Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers. 1596--1605","author":"Akbari A."},{"key":"e_1_2_1_7_1","volume-title":"Proceedings of the 18th International Conference on Information Processing in Sensor Networks. 85--96","author":"Akbari A."},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.3390\/s16010115"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1080\/17453670610045786"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2850347"},{"key":"e_1_2_1_11_1","volume-title":"Proceedings of the International Conference on Internet of Things Design and Implementation. 255--260","author":"Solis R."},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2019.2963816"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2019.2937116"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2016.2640959"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/sam.10124"},{"key":"e_1_2_1_16_1","volume-title":"Proceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence. 116--123","author":"Patterson T."},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2016.2562599"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/INSS.2010.5573462"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2858933"},{"key":"e_1_2_1_20_1","volume-title":"Proceedings of the European Symposium on Artificial Neural Networks (ESANN\u201916)","author":"Diethe T."},{"key":"e_1_2_1_21_1","volume-title":"Proceedings of the Conference on Learning Theory","author":"Sabato S.","year":"2016"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2020.2966151"},{"key":"e_1_2_1_23_1","volume-title":"Proceedings of the 2017 IEEE International Conference on Pervasive Computing and Communications (PerCom\u201917)","author":"Sztyler T."},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.3390\/s140915861"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/1689239.1689243"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2010.2045764"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-016-0987-z"},{"key":"e_1_2_1_28_1","doi-asserted-by":"crossref","unstructured":"D. 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