Facilitating Human Activity Data Annotation via Context-Aware Change Detection on Smartwatches
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[1] Sajal K. Das,et al. HuMAn: Complex Activity Recognition with Multi-Modal Multi-Positional Body Sensing , 2019, IEEE Transactions on Mobile Computing.
[2] Chris D. Nugent,et al. Sensor-Based Change Detection for Timely Solicitation of User Engagement , 2017, IEEE Transactions on Mobile Computing.
[3] Sivan Sabato,et al. Interactive Algorithms: from Pool to Stream , 2016, COLT.
[4] Timo Sztyler,et al. Online personalization of cross-subjects based activity recognition models on wearable devices , 2017, 2017 IEEE International Conference on Pervasive Computing and Communications (PerCom).
[5] O. Svensson,et al. Health-related quality of life and self-reported ability concerning ADL and IADL after hip fracture: A randomized trial , 2006, Acta orthopaedica.
[6] Chris D. Nugent,et al. Evaluation of Prompted Annotation of Activity Data Recorded from a Smart Phone , 2014, Sensors.
[7] Roozbeh Jafari,et al. Hierarchical Signal Segmentation and Classification for Accurate Activity Recognition , 2018, UbiComp/ISWC Adjunct.
[8] Niall Twomey,et al. Active transfer learning for activity recognition , 2016, ESANN.
[9] Xiangliang Zhang,et al. A PCA-Based Change Detection Framework for Multidimensional Data Streams: Change Detection in Multidimensional Data Streams , 2015, KDD.
[10] KawaharaYoshinobu,et al. Sequential change-point detection based on direct density-ratio estimation , 2012 .
[11] Roozbeh Jafari,et al. MotionSynthesis Toolset (MoST): An Open Source Tool and Data Set for Human Motion Data Synthesis and Validation , 2016, IEEE Sensors Journal.
[12] Paul Lukowicz,et al. Collecting complex activity datasets in highly rich networked sensor environments , 2010, 2010 Seventh International Conference on Networked Sensing Systems (INSS).
[13] Samaneh Aminikhanghahi,et al. Real-Time Change Point Detection with Application to Smart Home Time Series Data , 2019, IEEE Transactions on Knowledge and Data Engineering.
[14] Hani Hagras,et al. Autonomous computational intelligence-based behaviour recognition in security and surveillance , 2018, Security + Defence.
[15] Roozbeh Jafari,et al. Transferring Activity Recognition Models for New Wearable Sensors with Deep Generative Domain Adaptation , 2019, 2019 18th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).
[16] Maureen Schmitter-Edgecombe,et al. Context-Aware Delivery of Ecological Momentary Assessment , 2020, IEEE Journal of Biomedical and Health Informatics.
[17] Jun Hu,et al. Activity recognition based on inertial sensors for Ambient Assisted Living , 2016, 2016 19th International Conference on Information Fusion (FUSION).
[18] M. Levandowsky,et al. Distance between Sets , 1971, Nature.
[19] Masashi Sugiyama,et al. Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation , 2009, SDM.
[20] J. Kristensson,et al. Prevalence and predictors of healthcare utilization among older people (60+): focusing on ADL dependency and risk of depression. , 2012, Archives of gerontology and geriatrics.
[21] Mazda A. Marvasti,et al. Cusum techniques for timeslot sequences with applications to network surveillance , 2009, Comput. Stat. Data Anal..
[22] Roozbeh Jafari,et al. A human-centered wearable sensing platform with intelligent automated data annotation capabilities , 2019, IoTDI.
[23] Daniel Roggen,et al. Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition , 2016, Sensors.
[24] Dewen Wang,et al. Changes in activities of daily living (ADL) among elderly Chinese by marital status, living arrangement, and availability of healthcare over a 3-year period , 2009, Environmental health and preventive medicine.
[25] Chris D. Nugent,et al. Online Change Detection for Timely Solicitation of User Interaction , 2014, UCAmI.
[26] Masashi Sugiyama,et al. Sequential change‐point detection based on direct density‐ratio estimation , 2012, Stat. Anal. Data Min..
[27] Ludmila I. Kuncheva,et al. PCA Feature Extraction for Change Detection in Multidimensional Unlabeled Data , 2014, IEEE Transactions on Neural Networks and Learning Systems.
[28] Nigel Collier,et al. Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation , 2012, Neural Networks.
[29] Roozbeh Jafari,et al. Orientation Independent Activity/Gesture Recognition Using Wearable Motion Sensors , 2019, IEEE Internet of Things Journal.
[30] Lin Wang,et al. The University of Sussex-Huawei Locomotion and Transportation Dataset for Multimodal Analytics With Mobile Devices , 2018, IEEE Access.
[31] Francesca Bovolo,et al. Semisupervised One-Class Support Vector Machines for Classification of Remote Sensing Data , 2010, IEEE Transactions on Geoscience and Remote Sensing.
[32] Sanjay Ranka,et al. Statistical change detection for multi-dimensional data , 2007, KDD '07.
[33] Edward R. Sykes,et al. Context-aware mobile apps using iBeacons: towards smarter interactions , 2015, CASCON.
[34] Diane J. Cook,et al. A survey of methods for time series change point detection , 2017, Knowledge and Information Systems.
[35] Roozbeh Jafari,et al. Personalizing Activity Recognition Models Through Quantifying Different Types of Uncertainty Using Wearable Sensors , 2020, IEEE Transactions on Biomedical Engineering.
[36] Roozbeh Jafari,et al. Using Intelligent Personal Annotations to Improve Human Activity Recognition for Movements in Natural Environments , 2020, IEEE Journal of Biomedical and Health Informatics.
[37] Deborah Estrin,et al. Using mobile phones to determine transportation modes , 2010, TOSN.