A Multi-Disciplinary Approach to Ambient Assisted Living

2011 ◽  
pp. 76-93 ◽  
Author(s):  
Martina Ziefle ◽  
Carsten Röcker ◽  
Wiktoria Wilkowska ◽  
Kai Kasugai ◽  
Lars Klack ◽  
...  
Keyword(s):  
Technology Acceptance ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Medical Engineering ◽  
Interdisciplinary Approach ◽  
Healthcare Systems ◽  
Living Environment ◽  
Smart Healthcare ◽  
Interdisciplinary Research Project ◽  
Independent Life

This chapter illustrates the different disciplinary design challenges of smart healthcare systems and presents an interdisciplinary approach toward the development of an integrative Ambient Assisted Living environment. Within the last years a variety of new healthcare concepts for supporting and assisting users in technology-enhanced environments emerged. While such smart healthcare systems can help to minimize hospital stays and in so doing enable patients an independent life in a domestic environment, the complexity of such systems raises fundamental questions of behavior, communication and technology acceptance. The first part of the chapter describes the research challenges encountered in the fields of medical engineering, computer science, psychology, communication science, and architecture as well as their consequences for the design, use and acceptance of smart healthcare systems. The second part of the chapter shows how these disciplinary challenges were addressed within the eHealth project, an interdisciplinary research project at RWTH Aachen University.

scholarly journals They don't care about us! Care personnel's perspectives on Ambient Assisted Living technology usage: a scenario-based quantitative study (Preprint)

2018 ◽  
Author(s):  
Julia Offermann-van Heek ◽  
Martina Ziefle
Keyword(s):  
Technology Acceptance ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Assistive Technologies ◽  
Care Staff ◽  
Technology Usage ◽  
Disabled People ◽  
Data Types ◽  
Online Questionnaire ◽  
Professional Care

BACKGROUND Demographic change represents enormous burdens for the care sectors resulting in high proportions of (older) people in need of care and a lack of care staff. Ambient Assisted Living (AAL) technologies have the potential to support the bottlenecks in care supply, but are not yet in widespread use in professional care contexts. OBJECTIVE The study aims for investigating professional caregivers' AAL technology acceptance, their perception of specific technologies, data handling, perceived benefits, and barriers. In particular, the study focuses on perspectives on AAL technologies differing between care professionals working in diverse care contexts in order to examine to what extent the care context influences the acceptance of assistive technologies. METHODS An scenario-based online questionnaire (n = 170) was carried out focusing on professional care givers in medical, geriatric, and care of disabled people. The participants were asked for their perceptions concerning specific technologies, specific types of gathered data, potential benefits, and barriers of AAL technology usage. RESULTS The care context significantly impacted the evaluations of AAL technologies (F(14,220) = 2.514; P = .002). Professional caregivers of disabled people had a significantly more critical attitude towards AAL technologies than medical and geriatric caregivers: indicated by a) being the only caregiver group with rejecting evaluations of AAL technology acceptance (F(2,118) = 4.570; P = .01) and specific technologies (F(2,118) = 11.727; P = .000) applied for gathering data and b) by the comparatively lowest agreements referring to the evaluations of data types (F(2,118) = 4.073; P = .02) which are allowed to be gathered. CONCLUSIONS AAL technology acceptance is seen critical out of technology implementation reasons, especially in the care of people with disabilities. AAL technologies in care contexts have to be tailored to care professional's needs and concerns ("care about us"). The results contribute to a broader understanding of professional caregivers needs referring to specific data and technology configurations and encloses major differences concerning diverse care contexts. Integrating these findings into user group-tailored technology concepts and communication strategies will support a sustainable adoption of AAL systems in professional care contexts.

Forecasting Trends in an Ambient Assisted Living Environment Using Deep Learning

2021 ◽  
Author(s):  
Guillaume Gingras ◽  
Mehdi Adda ◽  
Abdenour Bouzouane ◽  
Hussein Ibrahim ◽  
Clemence Dallaire
Keyword(s):  
Deep Learning ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Living Environment

The Smart Condo Project

2011 ◽  
pp. 289-314 ◽  
Author(s):  
Nicholas M. Boers ◽  
David Chodos ◽  
Pawel Gburzynski ◽  
Lisa Guirguis ◽  
Jianzhao Huang ◽  
...  
Keyword(s):  
Sensor Network ◽  
Assisted Living ◽  
Universal Design ◽  
Ambient Assisted Living ◽  
Lessons Learned ◽  
Wireless Sensor ◽  
High Quality ◽  
Quality Healthcare ◽  
Living Space ◽  
Smart Healthcare

Most would agree that older adults want affordable, high-quality healthcare that enables them to live independently longer and in their own homes. To this end, ambient assisted living environments have been developed that are able to non-intrusively monitor the health of people at-home and to provide them with improved care. The authors have designed an environment, the Smart Condo, to support seniors and rehabilitating patients. They have embedded a wireless sensor network into a model living space, which incorporates universal design principles. Information from the sensor network is archived in a server, which supports a range of views via APIs. One such view is a virtual world, which is realistic and intuitive, while remaining non-intrusive. This chapter examines computing technologies for smart healthcare-related environments and the needs of elderly patients. It discusses the Smart Condo architecture, reviews key research challenges, and presents the lessons learned through the project.

A pattern analysis and visualisation system for sleep monitoring in ambient assisted living environment

2012 ◽  
Vol 1 (4) ◽  
pp. 320 ◽  
Author(s):  
Huiru Zheng ◽  
Haiying Wang ◽  
Hoda Nikamalfard ◽  
Maurice Mulvenna ◽  
Paul McCullagh ◽  
...  
Keyword(s):  
Assisted Living ◽  
Pattern Analysis ◽  
Ambient Assisted Living ◽  
Living Environment ◽  
Sleep Monitoring

scholarly journals Behavioral Biometrics in Assisted Living: A Methodology for Emotion Recognition

2016 ◽  
Vol 6 (4) ◽  
pp. 1035-1044
Author(s):  
S. Xefteris ◽  
N. Doulamis ◽  
V. Andronikou ◽  
T. Varvarigou ◽  
G. Cambourakis
Keyword(s):  
Risk Assessment ◽  
Neurodegenerative Diseases ◽  
Facial Expressions ◽  
Assisted Living ◽  
Service Oriented Architecture ◽  
Ambient Assisted Living ◽  
Living Environment ◽  
Emotional Status ◽  
Behavioral Biometrics ◽  
Dementia Patients

Behavioral biometrics aim at providing algorithms for the automatic recognition of individual behavioral traits, stemming from a person’s actions, attitude, expressions and conduct. In the field of ambient assisted living, behavioral biometrics find an important niche. Individuals suffering from the early stages of neurodegenerative diseases (MCI, Alzheimer’s, dementia) need supervision in their daily activities. In this context, an unobtrusive system to monitor subjects and alert formal and informal carers providing information on both physical and emotional status is of great importance and positively affects multiple stakeholders. The primary aim of this paper is to describe a methodology for recognizing the emotional status of a subject using facial expressions and to identify its uses, in conjunction with pre-existing risk-assessment methodologies, for its integration into the context of a smart monitoring system for subjects suffering from neurodegenerative diseases. Paul Ekman’s research provided the background on the universality of facial expressions as indicators of underlying emotions. The methodology then makes use of computational geometry, image processing and graph theory algorithms for the detection of regions of interest and then a neural network is used for the final classification. Findings are coupled with previous published work for risk assessment and alert generation in the context of an ambient assisted living environment based on Service oriented architecture principles, aimed at remote web-based estimation of the cognitive and physical status of MCI and dementia patients.

Sign in / Sign up

Export Citation Format

Share Document