Instrumenting the eHome and Preparing Elderly Pilots

2015 ◽  
pp. 335-361 ◽  
Author(s):  
Panagiotis E. Antoniou ◽  
Evdokimos Konstantinidis ◽  
Antonis S. Billis ◽  
Giorgos Bamparopoulos ◽  
Marianna S. Tsatali ◽  
...  
Keyword(s):  
Assisted Living ◽  
Healthcare Costs ◽  
Healthy Lifestyle ◽  
Low Cost ◽  
Ambient Assisted Living ◽  
Daily Activities ◽  
World Population ◽  
Methodological Framework ◽  
Current Trends ◽  
First World

In this chapter the lessons learnt from the build-up and integration of the USEFIL are demonstrated. First an introduction to Ambient Assisted Living (AAL) platforms, the infrastructure for eHomes of any purpose eHome is presented, in the context of their emergence as a viable way for managing healthcare costs in an aging first world population. Then technical and sustainability issues that are present after several years of maturation are touched upon. The USEFIL project's aim at an AAL platform that utilizes low cost “off-the-shelf” technologies in order to develop immediately applicable services, to assist elderly people in maintaining an independent, healthy lifestyle and program of daily activities is then briefly discussed. Afterwards, the methodological framework as well as principal results of the preparation and running of the pre-piloting phase of that platform are presented. Closing, current trends are explored in conjunction with future directions as triggered by this project in the context of cognitive impaired elderly support.

Combining Artificial Intelligence and NetMedicine for Ambient Assisted Living

2020 ◽  
pp. 1652-1666
Author(s):  
Paolo Sernani ◽  
Andrea Claudi ◽  
Aldo Franco Dragoni
Keyword(s):  
Artificial Intelligence ◽  
Assisted Living ◽  
Local Governments ◽  
Intelligent System ◽  
Ambient Assisted Living ◽  
World Population ◽  
Distributed Sensor ◽  
Distributed Sensor Network ◽  
Multi Agent ◽  
Analyse Data

World population is shifting towards older ages: according to recent estimates there will be 1.5 billion people over 65 years old in 2050. Local governments, international institutions, care organizations and industry are fostering the research community to find solutions to face the unprecedented challenges raised by population ageing. A combination of Artificial Intelligence and NetMedicine could be ideal to face these challenges: they provide the means to develop an intelligent system and simultaneously to distribute it over a network, allowing the communication over the internet, if needed. Hence, the authors present a Multi-Agent Architecture for Ambient Assisted Living (AAL): it is the model for a system to manage a distributed sensor network composed by ambient and biometric sensors. The system should analyse data and pro-actively decide to trigger alarms if anomalies are detected. The authors tested the architecture implementing a prototypical Multi-Agent System (MAS), based on Belief-Desire-Intention (BDI) paradigm: the Virtual Carer.

Combining Artificial Intelligence and NetMedicine for Ambient Assisted Living

2015 ◽  
Vol 6 (4) ◽  
pp. 62-76 ◽  
Author(s):  
Paolo Sernani ◽  
Andrea Claudi ◽  
Aldo Franco Dragoni
Keyword(s):  
Artificial Intelligence ◽  
Assisted Living ◽  
Local Governments ◽  
Intelligent System ◽  
Ambient Assisted Living ◽  
World Population ◽  
Distributed Sensor ◽  
Distributed Sensor Network ◽  
Multi Agent ◽  
Analyse Data

World population is shifting towards older ages: according to recent estimates there will be 1.5 billion people over 65 years old in 2050. Local governments, international institutions, care organizations and industry are fostering the research community to find solutions to face the unprecedented challenges raised by population ageing. A combination of Artificial Intelligence and NetMedicine could be ideal to face these challenges: they provide the means to develop an intelligent system and simultaneously to distribute it over a network, allowing the communication over the internet, if needed. Hence, the authors present a Multi-Agent Architecture for Ambient Assisted Living (AAL): it is the model for a system to manage a distributed sensor network composed by ambient and biometric sensors. The system should analyse data and pro-actively decide to trigger alarms if anomalies are detected. The authors tested the architecture implementing a prototypical Multi-Agent System (MAS), based on Belief-Desire-Intention (BDI) paradigm: the Virtual Carer.

scholarly journals A Low Cost Wireless Acoustic Sensor for Ambient Assisted Living Systems

2017 ◽  
Vol 7 (9) ◽  
pp. 877 ◽  
Author(s):  
Miguel Quintana-Suárez ◽  
David Sánchez-Rodríguez ◽  
Itziar Alonso-González ◽  
Jesús Alonso-Hernández
Keyword(s):  
Assisted Living ◽  
Low Cost ◽  
Ambient Assisted Living ◽  
Living Systems ◽  
Acoustic Sensor

scholarly journals User Identity Protection in Automatic Emotion Recognition through Disguised Speech

AI ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 636-649
Author(s):  
Fasih Haider ◽  
Pierre Albert ◽  
Saturnino Luz
Keyword(s):  
Machine Learning ◽  
Transfer Learning ◽  
Assisted Living ◽  
Speech Signal ◽  
Low Cost ◽  
Ambient Assisted Living ◽  
Recognition Task ◽  
Affect Recognition ◽  
Acoustic Features ◽  
Machine Learning Classification

Ambient Assisted Living (AAL) technologies are being developed which could assist elderly people to live healthy and active lives. These technologies have been used to monitor people’s daily exercises, consumption of calories and sleep patterns, and to provide coaching interventions to foster positive behaviour. Speech and audio processing can be used to complement such AAL technologies to inform interventions for healthy ageing by analyzing speech data captured in the user’s home. However, collection of data in home settings presents challenges. One of the most pressing challenges concerns how to manage privacy and data protection. To address this issue, we proposed a low cost system for recording disguised speech signals which can protect user identity by using pitch shifting. The disguised speech so recorded can then be used for training machine learning models for affective behaviour monitoring. Affective behaviour could provide an indicator of the onset of mental health issues such as depression and cognitive impairment, and help develop clinical tools for automatically detecting and monitoring disease progression. In this article, acoustic features extracted from the non-disguised and disguised speech are evaluated in an affect recognition task using six different machine learning classification methods. The results of transfer learning from non-disguised to disguised speech are also demonstrated. We have identified sets of acoustic features which are not affected by the pitch shifting algorithm and also evaluated them in affect recognition. We found that, while the non-disguised speech signal gives the best Unweighted Average Recall (UAR) of 80.01%, the disguised speech signal only causes a slight degradation of performance, reaching 76.29%. The transfer learning from non-disguised to disguised speech results in a reduction of UAR (65.13%). However, feature selection improves the UAR (68.32%). This approach forms part of a large project which includes health and wellbeing monitoring and coaching.

scholarly journals IndoorCare: Low-Cost Elderly Activity Monitoring System through Image Processing

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6051
Author(s):  
Daniel Fuentes ◽  
Luís Correia ◽  
Nuno Costa ◽  
Arsénio Reis ◽  
José Ribeiro ◽  
...  
Keyword(s):  
Low Income ◽  
Assisted Living ◽  
Rural Areas ◽  
Low Cost ◽  
Elderly Care ◽  
Ambient Assisted Living ◽  
The Elderly ◽  
Case Scenario ◽  
Care Services ◽  
Socially Excluded

The Portuguese population is aging at an increasing rate, which introduces new problems, particularly in rural areas, where the population is small and widely spread throughout the territory. These people, mostly elderly, have low income and are often isolated and socially excluded. This work researches and proposes an affordable Ambient Assisted Living (AAL)-based solution to monitor the activities of elderly individuals, inside their homes, in a pervasive and non-intrusive way, while preserving their privacy. The solution uses a set of low-cost IoT sensor devices, computer vision algorithms and reasoning rules, to acquire data and recognize the activities performed by a subject inside a home. A conceptual architecture and a functional prototype were developed, the prototype being successfully tested in an environment similar to a real case scenario. The system and the underlying concept can be used as a building block for remote and distributed elderly care services, in which the elderly live autonomously in their homes, but have the attention of a caregiver when needed.

scholarly journals A Radar-Based Smart Sensor for Unobtrusive Elderly Monitoring in Ambient Assisted Living Applications

2017 ◽  
Author(s):  
Giovanni Diraco ◽  
Alessandro Leone ◽  
Pietro Siciliano
Keyword(s):  
Technology Acceptance ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Vital Signs ◽  
Ultra Wideband ◽  
Daily Activities ◽  
Smart Sensor ◽  
Body Movements ◽  
Ambient Lighting ◽  
Wideband Radar

Continuous in-home monitoring of older adults living alone aims to improve their quality of life and independence, by detecting early signs of illness and functional decline or emergency conditions. To meet requirements for technology acceptance by seniors (unobtrusiveness, non-intrusiveness, privacy-preservation), this study presents and discusses a new smart sensor system for the detection of abnormalities during daily activities, based on ultra-wideband radar providing rich, not privacy-sensitive, information useful for sensing both cardiorespiratory and body movements, regardless of ambient lighting conditions and physical obstructions (through-wall sensing). The radar sensing is a very promising technology, enabling the measurement of vital signs and body movements at a distance, and thus meeting both requirements of unobtrusiveness and accuracy. In particular, impulse-radio ultra-wideband radar has attracted considerable attention in recent years thanks to many properties that make it useful for assisted living purposes. The proposed sensing system, evaluated in meaningful assisted living scenarios by involving 30 participants, exhibited the ability to detect vital signs, to discriminate among dangerous situations and activities of daily living, and to accommodate individual physical characteristics and habits. The reported results show that vital signs can be detected also while carrying out daily activities or after a fall event (post-fall phase), with accuracy varying according to the level of movements, reaching up to 95% and 91% in detecting respiration and heart rates, respectively. Similarly, good results were achieved in fall detection by using the micro-motion signature and unsupervised learning, with sensitivity and specificity greater than 97% and 90%, respectively.

Ambient Assisted Living and Internet of Things

2019 ◽  
pp. 100-115 ◽  
Author(s):  
Gonçalo Marques
Keyword(s):  
Internet Of Things ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Physical Object ◽  
World Population ◽  
Ageing Population ◽  
Communication Devices ◽  
Great Relevance ◽  
The One ◽  
Systems Architectures

The study of systems and architectures for ambient assisted living (AAL) is undoubtedly a topic of great relevance given the ageing of the world population. On the one hand, AAL technologies are designed to meet the needs of the ageing population in order to maintain their independence as long as possible. On the other hand, internet of things (IoT) proposes that various “things,” which include not only communication devices but also every other physical object on the planet, are going to be connected and will be controlled across the internet. The continuous technological advancements turn possible to build smart objects with great capabilities for sensing and connecting turn possible several advancements in AAL and IoT systems architectures. Advances in networking, sensors, and embedded devices have made it possible to monitor and provide assistance to people in their homes. This chapter reviews the state of art on AAL and IoT and their applications for enhanced indoor living environments and occupational health.

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