Embedding-based real-time change point detection with application to activity segmentation in smart home time series data

[1]  Aitor Almeida,et al.  A Scalable Hybrid Activity Recognition Approach for Intelligent Environments , 2018, IEEE Access.

[2]  Diane J. Cook,et al.  A survey of methods for time series change point detection , 2017, Knowledge and Information Systems.

[3]  Aitor Almeida,et al.  Cross-environment activity recognition using word embeddings for sensor and activity representation , 2020, Neurocomputing.

[4]  Diane J. Cook,et al.  COM: A method for mining and monitoring human activity patterns in home-based health monitoring systems , 2013, ACM Trans. Intell. Syst. Technol..

[5]  Aitor Almeida,et al.  Predicting Human Behaviour with Recurrent Neural Networks , 2018 .

[6]  Liming Chen,et al.  A semantics-based approach to sensor data segmentation in real-time Activity Recognition , 2019, Future Gener. Comput. Syst..

[7]  Diane J. Cook,et al.  Enhancing activity recognition using CPD-based activity segmentation , 2019, Pervasive Mob. Comput..

[8]  Siwei Feng,et al.  Few-Shot Learning-Based Human Activity Recognition , 2019, Expert Syst. Appl..

[9]  S Szewcyzk,et al.  Annotating smart environment sensor data for activity learning. , 2009, Technology and health care : official journal of the European Society for Engineering and Medicine.

[10]  Zhenyu Kong,et al.  High-dimensional process monitoring and change point detection using embedding distributions in reproducing kernel Hilbert space , 2014 .

[11]  Geoffrey Zweig,et al.  Linguistic Regularities in Continuous Space Word Representations , 2013, NAACL.

[12]  M. Shah,et al.  Object tracking: A survey , 2006, CSUR.

[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]  Gwenn Englebienne,et al.  Accurate activity recognition in a home setting , 2008, UbiComp.

[15]  Luis González Abril,et al.  Discrete techniques applied to low-energy mobile human activity recognition. A new approach , 2014, Expert Syst. Appl..

[16]  Rémi Ronfard,et al.  A survey of vision-based methods for action representation, segmentation and recognition , 2011, Comput. Vis. Image Underst..

[17]  Michelangelo Ceci,et al.  ECHAD: Embedding-Based Change Detection From Multivariate Time Series in Smart Grids , 2020, IEEE Access.

[18]  Liming Chen,et al.  Dynamic sensor data segmentation for real-time knowledge-driven activity recognition , 2014, Pervasive Mob. Comput..

[19]  Fadi Al Machot,et al.  A review on applications of activity recognition systems with regard to performance and evaluation , 2016, Int. J. Distributed Sens. Networks.

[20]  Chris D. Nugent,et al.  Evaluation of Prompted Annotation of Activity Data Recorded from a Smart Phone , 2014, Sensors.

[21]  Liming Chen,et al.  Semantic segmentation of real-time sensor data stream for complex activity recognition , 2017, Personal and Ubiquitous Computing.

[22]  Diane J. Cook,et al.  Automated Detection of Activity Transitions for Prompting , 2015, IEEE Transactions on Human-Machine Systems.

[23]  Alexandros André Chaaraoui,et al.  A review on vision techniques applied to Human Behaviour Analysis for Ambient-Assisted Living , 2012, Expert Syst. Appl..

[24]  Young-Koo Lee,et al.  Comprehensive Context Recognizer Based on Multimodal Sensors in a Smartphone , 2012, Sensors.

[25]  Diane J. Cook,et al.  Activity Discovery and Activity Recognition: A New Partnership , 2013, IEEE Transactions on Cybernetics.

[26]  Changseok Bae,et al.  Unsupervised learning for human activity recognition using smartphone sensors , 2014, Expert Syst. Appl..

[27]  Diego López-de-Ipiña,et al.  Exploring the computational cost of machine learning at the edge for human-centric Internet of Things , 2020, Future Gener. Comput. Syst..

[28]  Diane J. Cook,et al.  Using Smart Homes to Detect and Analyze Health Events , 2016, Computer.

[29]  Jamie Bennett,et al.  Healthcare in the Smart Home: A Study of Past, Present and Future , 2017 .

[30]  Hongnian Yu,et al.  Elderly activities recognition and classification for applications in assisted living , 2013, Expert Syst. Appl..

[31]  Aitor Almeida,et al.  PADL: A Modeling and Deployment Language for Advanced Analytical Services † , 2020, Sensors.

[32]  Nigel Collier,et al.  Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation , 2012, Neural Networks.