Smart Homes and Assisted Living for Ageing Population: From Sensors to Services

A special issue of Technologies (ISSN 2227-7080). This special issue belongs to the section "Assistive Technologies".

Deadline for manuscript submissions: closed (31 January 2019) | Viewed by 12515

Special Issue Editors

Department of Health Sciences, Health Sciences Centre (HSC), Lund University, Baravägen 3, 222 41 Lund, Sweden
Interests: epidemiology; health economics; ambient assisted living
Department of Information Engineering, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
Interests: communication systems and technologies for ambient-assisted living
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Special Issue Information

Dear Colleagues,

The use of Information and Communication Technology to develop new applications, product, services, and systems addressing the needs of an ageing population, has led to the development of so-called Smart Homes (SH) and Ambient Assisted Living (AAL)-enabled environments. These concepts encompass a range of different domains, from technology, including sensors, communications, and data platforms, to human-system interaction, including applications and user interfaces, to service provision, including management of health conditions and improvement in overall wellbeing and quality of life. With the increasing prevalence of technology, Ambient Assisted Living solutions aim to offer support not only in the home environment, however, but also in the community, and in the workplace.

This Special Issue welcomes submissions on recent findings and comprehensive reviews in the research, design, development, and evaluation through experimental activities of Ambient Assisted Living solutions and Smart Homes, and aimed at improving the health and quality of life of an ageing population. To reflect the multi-disciplinary nature of the target domain, this Special Issue solicits participation from different research areas, ranging from sensors and sensor networks, smart environments, wearable and pervasive computing, to data analytics, applications and service design, health sciences and experimental validation. We invite the submission of original and unpublished work addressing, though not limited to, the following research topics:

  • Sensors, sensor infrastructures, and sensing technologies for Smart Homes and Ambient Assisted Living
  • Internet of Things for Ambient Assisted Living
  • Mobile sensing and monitoring for Ambient Assisted Living
  • Activity recognition for monitoring and wellbeing promotion
  • Behavioral analysis and anomaly detection
  • Homecare monitoring systems
  • Healthy lifestyle promotion
  • Intelligent monitoring and user assistance in everyday settings
  • Security in AAL and SH systems
  • Experimental validation of applications and services for Ambient Assisted Living
  • Living Labs and shared datasets

Dr. Susanna Spinsante
Dr. Carlos Chiatti
Prof. Dr. Chris Nugent
Assoc. Prof. Ennio Gambi
Guest Editors

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Keywords

  • Sensors for smart homes and AAL
  • Activity and behavioral recognition for AAL
  • Living Labs in AAL
  • IoT for AAL

Published Papers (2 papers)

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Research

18 pages, 3964 KiB  
Article
Advanced Solutions Aimed at the Monitoring of Falls and Human Activities for the Elderly Population
by Bruno Andò, Salvatore Baglio, Salvatore Castorina, Ruben Crispino and Vincenzo Marletta
Technologies 2019, 7(3), 59; https://doi.org/10.3390/technologies7030059 - 20 Aug 2019
Cited by 3 | Viewed by 4984
Abstract
Ageing is a global phenomenon which is pushing the scientific community forward the development of innovative solutions in the context of Active and Assisted Living (AAL). Among functionality to be implemented, a major role is covered by falls and human activities monitoring. In [...] Read more.
Ageing is a global phenomenon which is pushing the scientific community forward the development of innovative solutions in the context of Active and Assisted Living (AAL). Among functionality to be implemented, a major role is covered by falls and human activities monitoring. In this paper, main technological solutions to cope with the aforementioned needs are briefly introduced. A specific focus is given on solutions for Falls recognition and classification. A case of study is presented, where a classification methodology based on an event-driven correlation paradigm and an advanced threshold-based classifier is addressed. The receiver operating characteristic (ROC) theory is used to properly define thresholds’ values while, in order to properly assess performances of the classification methodology proposed, dedicated metrics are suggested, such as sensitivity and specificity. The solution proposed shows an average Sensitivity of 0.97 and an average Specificity of 0.99. Full article
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20 pages, 1692 KiB  
Article
An Acoustic-Based Smart Home System for People Suffering from Dementia
by Eleni Boumpa, Anargyros Gkogkidis, Ioanna Charalampou, Argyro Ntaliani, Athanasios Kakarountas and Vasileios Kokkinos
Technologies 2019, 7(1), 29; https://doi.org/10.3390/technologies7010029 - 12 Mar 2019
Cited by 10 | Viewed by 6947
Abstract
Aging-in-place can reduce the progress of dementia syndrome and improve the quality of life of the sufferers and their families. Taking into consideration the fact that numerous neurological research results suggest the use of sound as a stimulus for empowering the memory of [...] Read more.
Aging-in-place can reduce the progress of dementia syndrome and improve the quality of life of the sufferers and their families. Taking into consideration the fact that numerous neurological research results suggest the use of sound as a stimulus for empowering the memory of the sufferer, an innovative information home support system for people suffering from dementia is proposed. The innovation of the proposed system is found in its application, that is to integrate a home system for assisting with person recognition via a sound-based memory aid service. Furthermore, the system addresses the needs of people suffering from dementia to recognize their familiars and have better interaction and collaboration, without the need for training. The system offers a ubiquitous recognition system, using smart devices like smart-phones or smart-wristbands. When a familiar person is detected in the house, then a sound is reproduced on the smart speakers, in order to stimulate the sufferer’s memory. The system identified all users and reproduced the appropriate sound in 100% of the cases. To the best of the authors’ knowledge, this is the first system of its kind for assisting person recognition via sound ever reported in the literature. Full article
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