Smart Assisted Living

1. Front Matter

   Pages i-x

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2. Sensing and Monitoring Technologies

   1. Front Matter

      Pages 1-1

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   2. Pervasive Sensing

      • Yiqiang Chen

      Pages 3-22

   3. Indoor Localization and Human Activity Tracking with Multiple Kinect Sensors

      • Shunkun Yang, Akshat Hans, Wenbing Zhao, Xiong Luo

      Pages 23-42

   4. Unobtrusive Sensing Solution for Post-stroke Rehabilitation

      • Idongesit Ekerete, Chris Nugent, Oonagh M. Giggins, James McLaughlin

      Pages 43-62

   5. Lessons from Hands-Free Data Entry in Flexible Cystoscopy with Glass for Future Smart Assistance

      • Charles Templeman, Francisco Javier Ordoñez Morales, Mathias Ciliberto, Andrew Symes, Daniel Roggen

      Pages 63-87

3. Activity Recognition and Behaviour Analysis

   1. Front Matter

      Pages 89-89

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   2. Human Activity Identification in Smart Daily Environments

      • Hossein Malekmohamadi, Nontawat Pattanjak, Roeland Bom

      Pages 91-118

   3. Object Detection-Based Location and Activity Classification from Egocentric Videos: A Systematic Analysis

      • Georgios Kapidis, Ronald Poppe, Elsbeth van Dam, Lucas P. J. J. Noldus, Remco C. Veltkamp

      Pages 119-145

   4. Improving the Collection and Understanding the Quality of Datasets for the Aim of Human Activity Recognition

      • Angelica Poli, Susanna Spinsante, Chris Nugent, Ian Cleland

      Pages 147-165

   5. Automated General Movement Assessment for Perinatal Stroke Screening in Infants

      • Yan Gao, Yang Long, Yu Guan, Anna Basu, Jessica Baggaley, Thomas Plötz

      Pages 167-187

4. User Needs and Personalisation

   1. Front Matter

      Pages 189-189

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   2. User-Centered Design in Defining and Developing Health and Well-Being ICT Solutions

      • Nikolaos Liappas, José G. Teriús-Padrón, Rebeca I. García-Betances, María Fernanda Cabrera-Umpiérrez, María Teresa Arredondo

      Pages 191-208

   3. Service Robot Behaviour Adaptation Based on User Mood, Towards Better Personalized Support of MCI Patients at Home

      • Dimitrios Giakoumis, Georgia Peleka, Manolis Vasileiadis, Ioannis Kostavelis, Dimitrios Tzovaras

      Pages 209-226

   4. Using Semantic Markup to Boost Context Awareness for Assistive Systems

      • Claudia Steinberger, Judith Michael

      Pages 227-246

5. Open Smart Home and Service Infrastructures

   1. Front Matter

      Pages 247-247

      PDF

   2. Towards Multi-resident Activity Monitoring with Smarter Safer Home Platform

      • Son N. Tran, Qing Zhang

      Pages 249-267

   3. New Environments for the Evaluation of Smart Living Solutions

      • Beatriz Merino Barbancho, Ivana Lombroni, Cecilia Vera-Muñoz, María Teresa Arredondo

      Pages 269-285

   4. A Distributed Spatial Index on Smart Medical System

      • Changqing Ji, Yang Gao, Zumin Wang, Jing Qin

      Pages 287-303

   5. Data Reduction Methods for Life-Logged Datasets

      • William P. Burns, Paul J. McCullagh, Dewar D. Finlay, Cesar Navarro-Paredes, James McLaughlin

      Pages 305-319

Smart Homes (SH) offer a promising approach to assisted living for the ageing population. Yet the main obstacle to the rapid development and deployment of Smart Home (SH) solutions essentially arises from the nature of the SH field, which is multidisciplinary and involves diverse applications and various stakeholders. Accordingly, an alternative to a one-size-fits-all approach is needed in order to advance the state of the art towards an open SH infrastructure.

This book makes a valuable and critical contribution to smart assisted living research through the development of new effective, integrated, and interoperable SH solutions. It focuses on four underlying aspects: (1) Sensing and Monitoring Technologies; (2) Context Interference and Behaviour Analysis; (3) Personalisation and Adaptive Interaction, and (4) Open Smart Home and Service Infrastructures, demonstrating how fundamental theories, models and algorithms can be exploited to solve real-world problems.

This comprehensive and timely book offers a unique and essential reference guide for policymakers, funding bodies, researchers, technology developers and managers, end users, carers, clinicians, healthcare service providers, educators and students, helping them adopt and implement smart assisted living systems.

• Assisted Living Solutions
• Smart Home User Needs and System Requirements
• Sensing and Monitoring
• Sensor Networks
• Context Awareness
• Activity Recognition
• Behavior Analysis
• User-Centered Design and Ethics
• Human-Machine Interaction
• Personalized and Adaptive Interactions
• Open Smart Home Infrastructures and Toolsets
• Virtual Reality
• Wearables
• Security and Privacy

• School of Computer Science & Informatics, De Montfort University, Leicester, UK

  Feng Chen

• Life Supporting Technologies, Universidad Politecnica de Madrid, Madrid, Spain

  Rebeca I. García-Betances, María Fernanda Cabrera-Umpiérrez

• School of Computing, Ulster University, Belfast, UK

  Liming Chen

• School of Computing, Ulster University, Newtownabbey, UK

  Chris Nugent

Dr Feng Chen is a Senior Lecturer at the School of Computer Science and Informatics, De Montfort University.

Dr Rebeca I García-Betances is a Senior Researcher in the Life Supporting Technologies Group at the Technical University of Madrid.

Prof María Fernanda Cabrera-Umpiérrez is an Associate Professor at the Telecommunication School, Technical University of Madrid.

Prof Liming Chen is a Chair Professor of Computer Science at De Montfort University, where he leads the Context, Intelligence and Interaction Research Group (CIIRG).

Prof Chris Nugent is a Professor of Biomedical Engineering and Head of the School of Computing at Ulster University, where he also leads the Pervasive Computing Research Group and is Co-Principal Investigator at the Connected Health Innovation Centre.

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