Sensor-based activity recognition in the context of ambient assisted living systems: A review

[1]  Thanos G. Stavropoulos,et al.  Utilizing ambient and wearable sensors to monitor sleep and stress for people with BPSD in nursing homes , 2018, J. Ambient Intell. Humaniz. Comput..

[2]  Juan Carlos Augusto,et al.  Learning about preferences and common behaviours of the user in an intelligent environment , 2009, BMI Book.

[3]  Antonio Fernández-Caballero,et al.  Emotion Detection and Regulation from Personal Assistant Robot in Smart Environment , 2018, Personal Assistants.

[4]  Diane J Cook,et al.  Assessing the Quality of Activities in a Smart Environment , 2009, Methods of Information in Medicine.

[5]  Diane J. Cook,et al.  Simple and Complex Activity Recognition through Smart Phones , 2012, 2012 Eighth International Conference on Intelligent Environments.

[6]  Jian Lu,et al.  epSICAR: An Emerging Patterns based approach to sequential, interleaved and Concurrent Activity Recognition , 2009, 2009 IEEE International Conference on Pervasive Computing and Communications.

[7]  Jiannong Cao,et al.  Challenges and Opportunities in Designing Smart Spaces , 2018, Internet of Everything.

[8]  Bruno Ando,et al.  Smart Multisensor Strategies for Indoor Localization , 2018 .

[9]  David S. Rosenblum,et al.  From action to activity: Sensor-based activity recognition , 2016, Neurocomputing.

[10]  Chris D. Nugent,et al.  Ontology-based activity recognition in intelligent pervasive environments , 2009, Int. J. Web Inf. Syst..

[11]  Francisco Falcone,et al.  Implementation and Operational Analysis of an Interactive Intensive Care Unit within a Smart Health Context , 2018, Sensors.

[12]  Verena Fuchsberger,et al.  Ambient assisted living: elderly people's needs and how to face them , 2008, SAME '08.

[13]  Alex Mihailidis,et al.  A Survey on Ambient-Assisted Living Tools for Older Adults , 2013, IEEE Journal of Biomedical and Health Informatics.

[14]  Emiliano Sisinni,et al.  Remote and non-invasive monitoring of elderly in a smart city context , 2018, 2018 IEEE Sensors Applications Symposium (SAS).

[15]  Tayeb Lemlouma,et al.  Adaptive monitoring system for e-health smart homes , 2018, Pervasive Mob. Comput..

[16]  Chris D. Nugent,et al.  From Activity Recognition to Intention Recognition for Assisted Living Within Smart Homes , 2017, IEEE Transactions on Human-Machine Systems.

[17]  Cosmin-Septimiu Nechifor,et al.  Web platform architecture for ambient assisted living , 2018, J. Ambient Intell. Smart Environ..

[18]  Kuan-Rong Lee,et al.  A flexible sequence alignment approach on pattern mining and matching for human activity recognition , 2010, Expert Syst. Appl..

[19]  Guang-Zhong Yang,et al.  The use of pervasive sensing for behaviour profiling - a survey , 2009, Pervasive Mob. Comput..

[20]  Percy Nohama,et al.  Notification Oriented Paradigm Applied to Ambient Assisted Living Tool , 2018, IEEE Latin America Transactions.

[21]  Zahir Tari,et al.  A context-aware approach for long-term behavioural change detection and abnormality prediction in ambient assisted living , 2015, Pattern Recognit..

[22]  Ramón F. Brena,et al.  An Improved Three-Stage Classifier for Activity Recognition , 2018, Int. J. Pattern Recognit. Artif. Intell..

[23]  Ahmad Lotfi,et al.  Behavioural pattern identification and prediction in intelligent environments , 2013, Appl. Soft Comput..

[24]  Ibrahim Sadek,et al.  Nonintrusive Remote Monitoring of Sleep in Home-Based Situation , 2018, Journal of Medical Systems.

[25]  Markus Vincze,et al.  User Experience Results of Setting Free a Service Robot for Older Adults at Home , 2018 .

[26]  Muttukrishnan Rajarajan,et al.  Feature selection and data balancing for activity recognition in smart homes , 2015, 2015 IEEE International Conference on Communications (ICC).

[27]  Kim-Kwang Raymond Choo,et al.  Blockchain: A Panacea for Healthcare Cloud-Based Data Security and Privacy? , 2018, IEEE Cloud Computing.

[28]  Kuei-Chung Chang,et al.  Implementing intelligent behavior tracking technique for elderly home care services , 2015, 2015 IEEE International Conference on Consumer Electronics - Taiwan.

[29]  Tin-Chih Toly Chen Advanced ambient intelligence system informatics , 2018, J. Ambient Intell. Humaniz. Comput..

[30]  S. Mukhopadhyay,et al.  Activity and Anomaly Detection in Smart Home: A Survey , 2016 .

[31]  Antonio F. Gómez-Skarmeta,et al.  An internet of things–based personal device for diabetes therapy management in ambient assisted living (AAL) , 2011, Personal and Ubiquitous Computing.

[32]  Muttukrishnan Rajarajan,et al.  Anomalies Detection in Smart-Home Activities , 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

[33]  Paolo Sernani,et al.  Exploring the ambient assisted living domain: a systematic review , 2017, J. Ambient Intell. Humaniz. Comput..

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

[35]  Chris D. Nugent,et al.  A Knowledge-Driven Approach to Activity Recognition in Smart Homes , 2012, IEEE Transactions on Knowledge and Data Engineering.

[36]  Amedeo Cesta,et al.  User needs and preferences on AAL systems that support older adults and their carers , 2018, J. Ambient Intell. Smart Environ..

[37]  Mahasweta Sarkar,et al.  Smart Connectivity for Internet of Things (IoT) Applications , 2018 .

[38]  Francesco Piazza,et al.  Human Fall Detection by Using an Innovative Floor Acoustic Sensor , 2018, Multidisciplinary Approaches to Neural Computing.

[39]  Chien-Chen Chen,et al.  RFID-based human behavior modeling and anomaly detection for elderly care , 2010 .

[40]  Adina Magda Florea,et al.  AN END-USER PERSPECTIVE ON THE CAMI AMBIENT AND ASSISTED LIVING PROJECT , 2018 .

[41]  Stefano Chessa,et al.  Sensor data fusion for activity monitoring in the PERSONA ambient assisted living project , 2013, J. Ambient Intell. Humaniz. Comput..

[42]  Svetha Venkatesh,et al.  Recognition of emergent human behaviour in a smart home: A data mining approach , 2007, Pervasive Mob. Comput..

[43]  Matthieu Geist,et al.  Human Activity Recognition Using Recurrent Neural Networks , 2017, CD-MAKE.

[44]  Kashif Nisar,et al.  A Smart Home Model Using Android Application , 2018 .

[45]  G. West,et al.  Duration Abnormality Detection in Sequences of Human Activity , 2004 .

[46]  Sally I. McClean,et al.  Probabilistic Learning From Incomplete Data for Recognition of Activities of Daily Living in Smart Homes , 2012, IEEE Transactions on Information Technology in Biomedicine.

[47]  Paolo Barsocchi,et al.  Monitoring elderly behavior via indoor position-based stigmergy , 2015, Pervasive Mob. Comput..

[48]  Karen Zita Haigh,et al.  Learning Models of Human Behaviour with Sequential Patterns , 2002 .

[49]  Daniel Roggen,et al.  Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition , 2016, Sensors.

[50]  C. R. Kothari,et al.  Research Methodology: Methods and Techniques , 2009 .

[51]  Diane J. Cook,et al.  Keeping the Resident in the Loop: Adapting the Smart Home to the User , 2009, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[52]  Juan Carlos Augusto,et al.  Using argumentation to manage users' preferences , 2018, Future Gener. Comput. Syst..

[53]  Ahmad Lotfi,et al.  Smart homes for the elderly dementia sufferers: identification and prediction of abnormal behaviour , 2012, J. Ambient Intell. Humaniz. Comput..

[54]  Kent Larson,et al.  Activity Recognition in the Home Using Simple and Ubiquitous Sensors , 2004, Pervasive.

[55]  Andreas Savvides,et al.  The BehaviorScope framework for enabling ambient assisted living , 2010, Personal and Ubiquitous Computing.

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

[57]  Heiner Stuckenschmidt,et al.  Recognizing interleaved and concurrent activities: A statistical-relational approach , 2011, 2011 IEEE International Conference on Pervasive Computing and Communications (PerCom).

[58]  Hubert Kenfack Ngankam,et al.  The cornerstones of smart home research for healthcare , 2018 .

[59]  Víctor Zamudio,et al.  A Proposal to Classify Ways of Walking Patterns Using Spiking Neural Networks , 2018, Fuzzy Logic Augmentation of Neural and Optimization Algorithms.

[60]  Svetha Venkatesh,et al.  Explicit State Duration HMM for Abnormality Detection in Sequences of Human Activity , 2004, PRICAI.

[61]  Carlos Iván Chesñevar,et al.  Argumentation-Based Personal Assistants for Ambient Assisted Living , 2018, Personal Assistants.

[62]  Salvatore Gaglio,et al.  Detection of User Activities in Intelligent Environments , 2014, Advances onto the Internet of Things.

[63]  Fabien Cardinaux,et al.  Modelling of Behavioural Patterns for Abnormality Detection in the Context of Lifestyle Reassurance , 2008, CIARP.

[64]  Stefano Ferilli,et al.  A Logic Framework for Incremental Learning of Process Models , 2013, Fundam. Informaticae.

[65]  Paul Cuddihy,et al.  Algorithm to automatically detect abnormally long periods of inactivity in a home , 2007, HealthNet '07.

[66]  Matthai Philipose,et al.  Unsupervised Activity Recognition Using Automatically Mined Common Sense , 2005, AAAI.

[67]  Stefano Ferilli,et al.  Incremental Learning of Daily Routines as Workflows in a Smart Home Environment , 2015, ACM Trans. Interact. Intell. Syst..

[68]  Ig-Jae Kim,et al.  Mobile health monitoring system based on activity recognition using accelerometer , 2010, Simul. Model. Pract. Theory.

[69]  Diane J. Cook,et al.  CRAFFT: an activity prediction model based on Bayesian networks , 2015, J. Ambient Intell. Humaniz. Comput..

[70]  Sivakumar Ramakrishnan,et al.  Ubiquitous and Ambient Intelligence Assisted Learning Environment Infrastructures Development - a review , 2017, Education and Information Technologies.

[71]  Amitava Chatterjee,et al.  Recognition of Human Behavior for Assisted Living Using Dictionary Learning Approach , 2018, IEEE Sensors Journal.

[72]  Diane J. Cook,et al.  Human Activity Recognition and Pattern Discovery , 2010, IEEE Pervasive Computing.

[73]  Markus M. Bugge,et al.  Governing socio-technical change: Orchestrating demand for assisted living in ageing societies , 2018 .

[74]  B. Kröse,et al.  Bayesian Activity Recognition in Residence for Elders , 2007 .

[75]  Diane J. Cook,et al.  Learning frequent behaviours of the users in Intelligent Environments , 2010, J. Ambient Intell. Smart Environ..

[76]  Giovanni Delnevo,et al.  On enhancing accessible smart buildings using IoT , 2018, 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC).

[77]  Hani Hagras,et al.  Towards the detection of temporal behavioural patterns in intelligent environments , 2006 .

[78]  Hani Hagras,et al.  Embedding Computational Intelligence in Pervasive Spaces , 2007, IEEE Pervasive Computing.

[79]  Younghwan Yoo,et al.  User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm , 2015, Sensors.

[80]  Diane J. Cook,et al.  Discovering Temporal Features and Relations of Activity Patterns , 2010, 2010 IEEE International Conference on Data Mining Workshops.

[81]  Henry A. Kautz,et al.  Inferring activities from interactions with objects , 2004, IEEE Pervasive Computing.

[82]  Lawrence B. Holder,et al.  Discovering Activities to Recognize and Track in a Smart Environment , 2011, IEEE Transactions on Knowledge and Data Engineering.

[83]  Hui Li,et al.  A novel one-pass neural network approach for activities recognition in intelligent environments , 2008, 2008 7th World Congress on Intelligent Control and Automation.

[84]  Vikramaditya R. Jakkula,et al.  Anomaly Detection Using Temporal Data Mining in a Smart Home Environment , 2008, Methods of Information in Medicine.

[85]  Hani Hagras,et al.  A fuzzy embedded agent-based approach for realizing ambient intelligence in intelligent inhabited environments , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[86]  Marcela D. Rodríguez,et al.  Activity Inference for Ambient Intelligence Through Handling Artifacts in a Healthcare Environment , 2012, Sensors.

[87]  Hani Hagras,et al.  Detection Of Normal and Novel Behaviours In Ubiquitous Domestic Environments , 2010, Comput. J..

[88]  François Brémond,et al.  An Activity Monitoring System for Real Elderly at Home: Validation Study , 2010, 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance.

[89]  Masamichi Shimosaka,et al.  Anomaly Detection and Life Pattern Estimation for the Elderly Based on Categorization of Accumulated Data , 2011 .

[90]  Roberto Colella,et al.  Modular multimodal user interface for distributed ambient intelligence architectures , 2018, Internet Technol. Lett..

[91]  Heiner Stuckenschmidt,et al.  A probabilistic ontological framework for the recognition of multilevel human activities , 2013, UbiComp.

[92]  David Wetherall,et al.  Recognizing daily activities with RFID-based sensors , 2009, UbiComp.

[93]  Diane J. Cook,et al.  Mining Sensor Streams for Discovering Human Activity Patterns over Time , 2010, 2010 IEEE International Conference on Data Mining.

[94]  Juan Carlos Augusto,et al.  Past, Present and Future of Ambient Intelligence and Smart Environments , 2009, ICAART.

[95]  Martha E. Pollack,et al.  Adaptive cognitive orthotics: combining reinforcement learning and constraint-based temporal reasoning , 2004, ICML.

[96]  Susan Elias,et al.  Assistive Dementia Care System Through Smart Home , 2018 .

[97]  Diane J. Cook,et al.  An Adaptive Sensor Mining Framework for Pervasive Computing Applications , 2008, KDD Workshop on Knowledge Discovery from Sensor Data.

[98]  H. Bonjer,et al.  A Perioperative eHealth Program to Enhance Postoperative Recovery After Abdominal Surgery: Process Evaluation of a Randomized Controlled Trial , 2018, Journal of medical Internet research.

[99]  Paul Müller,et al.  Ambient Intelligence in Assisted Living: Enable Elderly People to Handle Future Interfaces , 2007, HCI.

[100]  Muttukrishnan Rajarajan,et al.  Activity Recognition in Smart Homes Using Clustering Based Classification , 2014, 2014 22nd International Conference on Pattern Recognition.

[101]  Diane J. Cook,et al.  Learning Setting-Generalized Activity Models for Smart Spaces , 2012, IEEE Intelligent Systems.

[102]  Stefan Woltran,et al.  Generalizations of Dung Frameworks and Their Role in Formal Argumentation , 2014, IEEE Intelligent Systems.

[103]  Abdellah Touhafi,et al.  Ambient Assisted living system's models and architectures: A survey of the state of the art , 2020, J. King Saud Univ. Comput. Inf. Sci..

[104]  Vicente Julián,et al.  Designing a goal-oriented smart-home environment , 2016, Information Systems Frontiers.

[105]  Jian Lu,et al.  A Pattern Mining Approach to Sensor-Based Human Activity Recognition , 2011, IEEE Transactions on Knowledge and Data Engineering.

[106]  Mukhtiar Memon,et al.  Ambient Assisted Living Healthcare Frameworks, Platforms, Standards, and Quality Attributes , 2014, Sensors.

[107]  Weihua Sheng,et al.  Motion- and location-based online human daily activity recognition , 2011, Pervasive Mob. Comput..

[108]  Gregory D. Abowd,et al.  The context toolkit: aiding the development of context-enabled applications , 1999, CHI '99.

[109]  Subhas Mukhopadhyay,et al.  Determining Wellness through an Ambient Assisted Living Environment , 2014, IEEE Intelligent Systems.

[110]  Svetha Venkatesh,et al.  Activity recognition and abnormality detection with the switching hidden semi-Markov model , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[111]  Heinrich C. Mayr,et al.  HCM-L: Domain-Specific Modeling for Active and Assisted Living , 2016, Domain-Specific Conceptual Modeling.

[112]  Matjaz Gams,et al.  An Approach to Analysis of Daily Living Dynamics , 2010 .

[113]  Irina Mocanu,et al.  Human Activity Recognition in Smart Environments , 2013, 2013 19th International Conference on Control Systems and Computer Science.

[114]  Bernadette Dorizzi,et al.  A fuzzy logic system for home elderly people monitoring (EMUTEM) , 2009 .

[115]  Cem Ersoy,et al.  Daily life behaviour monitoring for health assessment using machine learning: bridging the gap between domains , 2014, Personal and Ubiquitous Computing.

[116]  Clauirton A. Siebra,et al.  A neural network based application for remote monitoring of human behaviour , 2015, International Conference on Computer Vision and Image Analysis Applications.