Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Journal of Intelligent Systems

Editor-in-Chief: Fleyeh, Hasan

CiteScore 2018: 1.03

SCImago Journal Rank (SJR) 2018: 0.188
Source Normalized Impact per Paper (SNIP) 2018: 0.533

See all formats and pricing
More options …
Volume 25, Issue 1


Ambient Assisted Living Technologies for Aging Well: A Scoping Review

Stephanie Blackman
  • Dalhousie Family Medicine, 5909 Veterans Memorial Lane, Abbie J. Lane Building, Halifax, NS, Canada B3H 2E2
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Claudine Matlo / Charisse Bobrovitskiy / Ashley Waldoch
  • Gerontology Research Centre, Simon Fraser University Vancouver, 2800-515 West Hastings Street, Vancouver, BC, Canada V6B 5K3
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Mei Lan Fang
  • Gerontology Research Centre, Simon Fraser University Vancouver, 2800-515 West Hastings Street, Vancouver, BC, Canada V6B 5K3
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Piper Jackson / Alex Mihailidis
  • Rehabilitation Sciences, University of Toronto, 160-500 University Avenue, Toronto, ON, Canada M5G 1V7
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Louise Nygård
  • Karolinska Institutet, Division of Occupational Therapy, Department of Neurobiology, Care Sciences and Society (NVS), H1, Fack 23200 141 83 Huddinge, Sweden
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Arlene Astell / Andrew Sixsmith
  • Gerontology Research Centre, Simon Fraser University Vancouver, 2800-515 West Hastings Street, Vancouver, BC, Canada V6B 5K3
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2015-03-14 | DOI: https://doi.org/10.1515/jisys-2014-0136


Ambient assisted living (AAL) technology is of considerable interest in supporting the independence and quality of life of older adults. As such, it is a core focus of the emerging field of gerontechnology, which considers how technological innovation can aid health and well-being in older age. For this scoping review, a comprehensive search of databases and key journals was conducted from January to April of 2013 in order to identify AAL technologies that have the potential to help deal with some of the challenges associated with aging. In particular, we focused on technologies that could potentially be used by people living with some degree of cognitive impairment, ranging from normal cognitive aging to mild cognitive impairment up to earlier stages of dementia. Options currently available and those still under development were both included in our search. Fifty-nine technologies were identified and are outlined here, along with a discussion of history of AAL from a gerontological perspective and related theoretical considerations.

Keywords: Ambient assisted living; gerontechnology; intelligent systems; mild cognitive impairment

2010 Mathematics Subject Classification:: 91C99

1 Introduction

Ambient assisted living (AAL) technologies have emerged within recent decades as providing innovative approaches to the challenges of an aging population. AAL technology has the potential to enable people to live and age well in the following ways: supporting individuals to maintain and continue their current activities; facilitating and enabling continued participation and engagement in activities at home and in the community; and improving the cost-effectiveness and quality of health and social services [1]. The term “ambient assisted living” is widely used within gerontechnological research and development despite the fact that no universal definition of AAL has been adopted [18]. However, AAL generally refers to the use of information and communication technologies (ICT), stand-alone assistive devices, and smart home technologies in a person’s daily living and working environment to enable individuals to stay active longer, remain socially connected, and live independently into old age [42]. AAL provides supportive home environments by integrating sensors, actuators, smart interfaces, and artificial intelligence [58]. AAL is rooted in the following: traditional assistive technologies for people with disabilities; universal design approaches to accessibility, usability, and acceptability of interactive technologies; and the emerging ambient intelligence (AI) computing paradigm, which provides intelligent, unobtrusive, and ubiquitous assistance [50].

AAL technology has the ability to anticipate and respond to the changing needs of older adults; however, the potential of AAL technology is for it to be adaptive to the heterogeneous nature of old age. To date, AAL research has narrowly focused on the potential of such technologies for older adults who are healthy, frail, or suffering from dementia. Past research has largely neglected the possibilities of AAL technology to enhance the lives of those with mild cognitive impairment (MCI). MCI is defined as a noticeable decline in cognitive abilities (such as memory, decision making, problem solving, and comprehension) that does not prevent daily activities. It is experienced by a significant portion of the older population, affecting up to one-fifth of people over the age of 65 years [48]. Effective support for independent living and aging in place is particularly critical for people with MCI as, if successful, it is possible for them to maintain a high quality of life; conversely, failure can result in suffering and/or the high costs associated with dedicated care. AAL is the most attractive option for providing such support, as effective pharmacological options do not currently exist [49]. However, MCI refers to multiple conditions that differ in presentation and are poorly understood, complicating attempts to provide solutions. This scoping review was designed with the intent of identifying only technology specifically related to MCI, but the technologies identified are more widely useful in addressing challenges related to aging, and for people with other cognitive impairments, such as normal cognitive aging and for earlier stages of dementia. Thus, we present our findings as such: AAL technologies developed as support for challenges in daily life experienced by older adults living with cognitive impairments (centered on MCI), as well as AAL technology that may be more generally useful to that user group.

Cognitive impairments, in general, are known to affect an individual’s ability to observe, encode, accumulate, regain, and utilize information. Various pathways can lead to cognitive impairment [17]. For example, there are neurodegenerative conditions that can influence cognitive decline, which include Alzheimer’s disease, Pick’s disease, Parkinson’s disease, Lewy body disease, Huntington’s disease, progressive supranuclear palsy, and cerebellar degeneration. Additionally, vascular disorders such as strokes and cerebral embolic disease can also lead to deficits to cognitive processes [17]. Individuals that live with some form of cognitive impairment can experience a range of symptomatic challenges associated with memory loss, deficiencies in verbal communication, functional impairment, as well as other varying deficits of attention, judgment, and insight [17, 40, 47]. There are also behavioral issues such as depression, agitation, or psychosis linked to cognitive impairment, which can further influence well-being and overall quality of life [41]. Symptoms of cognitive impairment can affect an individual’s personal safety and sense of security, independence, and confidence, which influence other areas of life such as the ability to engage and participate in social activities as well as the ability to live freely. To enable independent living and help improve quality of life for persons living with a cognitive impairment, various technological interventions have emerged in recent decades to support persons with cognitive impairment, including “low-tech” environmental adaptations [21, 29], technologies for health management [8, 16, 64], as well as to assist with mobility issues and managing wandering behaviors [46]. More specifically, there are possibilities derived from AAL technology that can enhance the lives of those that live with a cognitive impairment.

To contribute to a wider understanding of developments in AAL that satisfy such purposes, this literature review will concentrate on the following: conceptualizing the term “ambient assisted living,” outlining the evolution of AAL technology, exploring the theoretical discourses pertaining to technology and aging, and identifying emerging themes and possible solutions within AAL technology in relation to the needs of older adults with MCI and related cognitive impairments. First, we provide some background regarding the development of AAL technology. Then, we present our review method, which is followed by a summary of our findings: the AAL technologies identified in our search. We provide some discussion on theoretical issues relevant to the topic, and finally present our conclusions drawn from the review.

2 Background: The Evolution of AAL Technology

Assistive technology is an umbrella term referring to specialized technology used by people to adapt how specific tasks are performed. Assistive technology includes low-tech devices, such as eyeglasses or walkers, as well as high-tech devices, such as hardware, software, and peripherals that assist people with disabilities in accessing computers or other information technologies [15]. AAL is the result of a progression from individual devices assisting with one task or activity of daily living (ADL) to ambient systems in which the assistance or support completely encompasses the living area and the person. The addition of the adjective “ambient” reflects this development, as these technologies no longer simply assist the user; they are all encompassing.

According to References [23] and [57], there are three generations of technology designed for supporting the independent living of older adults, which we describe here. A summary of these three generations is shown in Figure 1. These technologies are referred to as “telecare” based on a UK model; however, this model also provides insight as to the evolution of AAL technologies outside of the United Kingdom.

Three Generations of Ambient Assisted Living (AAL).
Figure 1:

Three Generations of Ambient Assisted Living (AAL).

2.1 First-Generation Technologies

The first generation of AAL technologies consisted of community, social, and personal response systems. It involves the older adult wearing an alarm, which usually takes the form of a pendant or alarm button. The older adult presses the button or pendant in order to raise the alarm in the case of an emergency situation, such as a fall [57]. Once alerted, a staff person at a 24-h call center contacts the older person and determines whether or not informal caregivers or emergency services are needed [54]. A well-known example of this first-generation technology is LifeCall (recently renamed LifeAlert), whose memorable “Help, I’ve fallen and I can’t get up!” commercial from 1992 brought public awareness to these devices.

Past research indicates that these first-generation alarms have several benefits related to the security and safety of community-dwelling older adults. These benefits include reduced stress levels among older adults, families, and caregivers; reduced hospital admissions; earlier hospital discharge; and delayed entry into long-term care facilities [54]. While beneficial in certain situations, research demonstrates specific weaknesses associated with this technology. If the person is incapacitated either physically or mentally or is not wearing the device, he or she may not have the capacity to trigger the alarm. For example, an older person may take off the alarm when he/she goes to bed and forget to put it back on when needing to use the bathroom in the middle of the night. As the risk of falling is significant in this scenario, the alarms may prove useless in high-risk situations.

2.2 Second-Generation Technologies

These generations of technologies are characterized by their integration of electronic components, which helped address the limitations of the first generation. These technologies do not simply respond; they also detect potential emergencies, such as a fall or environmental hazards, by using sensors [54]. Within the home, seniors are monitored using sensors, which call for assistance without relying on the user to trigger the alarm [54]. For example, if there is a gas leak within the home leaving the older adult incapacitated, unaware, and/or unable to seek help, the sensor monitoring system automatically raises the alarm and contacts the appropriate authorities [55].

These second-generation sensor systems may prove to be beneficial for older adults with MCI as these individuals demonstrate difficulties using household appliances. Often, these older adults forget to turn off appliances, such as the stove or iron, after completing a task. Second-generation technologies may sense that the stove has remained on for too long and alert the individual before it becomes dangerous. Despite the potential benefits, a weakness associated with this generation is the fact that some users feel it is intrusive. These technologies are emerging on the market and being used by older adults within the home.

2.3 Third-Generation Technologies

The most recent wave of AAL technology has emerged along with the advancement of ICT. At this stage, technology not only detects and reports problems; it prevents problems using the concept of AAL. AAL systems that “render their service in a sensitive and responsive way and are unobtrusively integrated into our daily environment are referred to as being ambient intelligent” [37]. An example includes home monitoring systems that utilize non-intrusive methods, which negate the need of manual activation for alarms while reducing reliance upon active supervision. These systems integrate computing systems and assistive devices into everyday living contexts in order to not only monitor the home environment but also to monitor the older person. Environmental and wearable sensors monitor vital signs as well as changes in mobility and activity patterns. These may be indicative of changes in health status.

Actuators, which are mechanical devices that are used for controlling a mechanism or system, provide the older person with assistance, while smart interfaces provide information, support, and encouragement. Presently, this third generation is in development; however, intelligent systems and remote services are being increasingly adopted in this domain to improve quality of life, support self-independence, and reduce costs [37]. A potential benefit of this technology is the reduction of stigma associated with monitoring and assistance devices by embedding the technology invisibly within everyday objects. People with MCI may already feel self-conscious about their changing cognitive ability and not want the added embarrassment of obvious assistive devices. This additional embarrassment may result in older adults refusing to use the technologies; therefore, the unobtrusive nature of AAL technologies may remove this stigma or embarrassment and thus increase usage.

3 Method

Scoping reviews have been used to systematically assess the breadth of a body of literature in a specific research area [14]. By means of working through the scoping review process, we were able to systematically review and categorize a substantial volume of peer-reviewed literature. This review focusing specifically on academic literature addresses the following research questions: what is AAL, and how might AAL technology assist older adults with mild cognitive impairment?

Through sequential steps, the scoping review process maps and synthesizes key underlying concepts in a particular field to identify disparities in existing knowledge [7]. To guide the process, a six-step framework was adopted from Arksey and O’Malley’s scoping review method [7]. Their six-step process included identifying a research question(s); identifying relevant studies; selecting studies to be included; charting data; collating, summarizing, and reporting results; and consulting with colleagues and experts [7]. Twenty electronic sources (including databases and key journals listed in Table 1) were selected and searched to capture relevant peer-reviewed publications related to AAL technology and MCI across a range of disciplines (e.g., gerontology, health care, social sciences, medicine, nursing, policy, and psychology).

Table 1:

Complete List of Electronic Sources Searched for the Scoping Review.

A comprehensive search of databases and key journals was conducted between January and April 2013 to identify English-language peer-reviewed publications published between 2000 and 2013. An initial environmental scan alerted the researchers to various parameters (such as keywords) within the literature that guided subsequent searches. Search terms and phrases included “ambient assisted living”; “ambient assisted living technology”; “technology and aging”; “technology, aging, and MCI”; “telecare”; “aging, technology, and theory”; “aging, technology, and discourse”; “technology and aging in place”; “technology for communication”; “technology for safety and mobility”; “wandering”; “technology for finances”; “technology for health management”; “medication management”; “technology for leisure”; “technologies for aging in place”; and “technology for IADLs”. These were entered into the databases and searched in the “title” and “abstract” fields. As sources were gathered, the reference list of each included article (particularly review articles) was cross-referenced for additional resources that pertained to the research question. In addition, expert informants were contacted to ensure the comprehensive inclusion of relevant material.

Articles were included for review if they met the following inclusion criteria: (i) published after 1990; (ii) conceptualized the term AAL; (iii) concerned primarily with older adults 50 years and older (older adults are usually considered those 65 years and older, but for the purpose of this study, 50 years and older were included because people may experience symptoms of MCI before the age of 65 years); (iv) could be retrieved free of charge online or through university library services; and (v) were written in English.

To guide data extraction and analysis, a data-charting form was created with specific codes to capture relevant details of selected papers. The data-charting form was tested by two team members to ensure consistency. During this process, the researchers made notes on which categories captured information relevant to the study and identified any additional categories needed. Following the data-charting process, the research team agreed on a final set of 80 studies, 16 of which were reviews. As there was substantial heterogeneity among included studies, the majority of the data were synthesized descriptively excluding reviews. Review articles included for the final subset were used to supplement current understandings of AAL and hand searched for additional sources. Articles were excluded if they were published before 1990 and did not discuss AAL in relation to adults aged 50 years and over. A quality assessment was not conducted, as it is not a required element of a scoping review [7, 14]. Figure 2 provides the breakdown of search results according to the different phases of the scoping review search strategy. From the final group of 64 articles produced by the search, we identified 59 technologies of interest; these are listed in Section 4.

Scoping Review Search Strategy.
Figure 2:

Scoping Review Search Strategy.

4 Results

AAL technologies have been identified as “information and communication technology-based products, services, and systems to provide older and vulnerable people with a secure environment, improve their quality of life, and reduce the costs of health and social care” [18]. These systems integrate modern technologies into the homes and lives of older adults, offering intelligent, unobtrusive, and ubiquitous supports [50]. The rapid growth of AAL research in the past few years is partly a result of a push from the Ambient Assisted Living Joint Programme, which funds a number of research projects aimed at developing new and innovative AAL devices across European countries [6]. The potential for AAL products to enhance quality of life among older adults is an interesting new prospect within the field of gerontechnology and should be further investigated.

Past research has largely neglected the possibilities of AAL technology to enhance the quality of life of those that live with a cognitive impairment. As specified, some of the primary symptomatic challenges for individuals living with a form of cognitive impairment include minor to moderate deficits in memory, attention, judgment, insight, verbal communication, and functionality, which can negatively influence a person’s safety and sense of security, personal autonomy, confidence, and the overall ability to live freely and independently while actively engaging in social activities. There are various AAL technologies (denoted in Tables 39) that can help alleviate some of these pressures. To address issues of safety and security, there is a range of health-monitoring and emergency-alert devices through the use of television and telephone platforms to facilitate risk assessments, monitor vital signs, allow easy access to health information, and connect individuals with emergency services as well as their care providers. Social support, activity monitoring, and communication devices through the use of robotic companions and virtual platforms can enable cognitive stimulation, facilitate personal health management, and provide information and entertainment for individuals experiencing cognitive impairment. It is important to note that despite not having cure for cognitive impairment, there are technological solutions that can help improve the quality of life for those that live with this condition. AAL integrates modern technologies into the homes and lives of older adults, offering intelligent, unobtrusive, and ubiquitous supports that help improve functional capabilities in daily activities. These supports can also improve safety by detecting and preventing common but risky situations experienced by people with cognitive impairment, such as appliances being left turned on, and wandering [10]. AAL technology can provide individuals experiencing cognitive impairment with a renewed sense of safety and security, help them maintain independent living, and improve their overall well-being and quality of life.

Given the novelty of this area, much of the information on the latest AAL technologies has yet to be published by peer-reviewed sources. Thus, a preliminary summary of available devices and novel projects will help gain perspective on the trends in this field. Table 2 encapsulates the way in which we have classified the technology encountered in our review. While this is a preliminary classification scheme, it helps show the common types and intended uses of AAL for the user group we are interested in.

Table 2:

Legend: Technology Types Classified in This Review.

Table 3 summarizes AAL devices currently or soon to be on the market. These systems offer supports for physical health and safety. Physical health promotion devices include monitoring systems that track vitals and/or provide a connection to health systems such as health-care providers, services, and information. Ambient safety technologies often include monitoring and alert devices that connect to emergency services. A common trend in available AAL devices is the provision of adaptations to the home environment that are mostly immobile and passive technologies, especially among safety technologies. These systems can be useful for many older adults experiencing advanced health problems but may not necessarily be appropriate for the needs of individuals with MCI, as they may require active prompts and reminders to use the system as well as more advanced features that minimize the number of interactions that are required between the technology and user.

Table 3:

AAL Devices Currently or Soon to Become Available on the Market.

In addition to devices currently or soon to be available, other trends were found regarding current and recent AAL projects. These research and technology developments are summarized in Tables 49. AAL technology projects recognize the potential this technology has to provide more than physiological support systems. Some devices are attempting to bolster mental health, offering outlets for cognitive stimulation, communication, and companionship [6, 20, 52]. A number of projects are working toward the standardization of AAL technology by creating recommendations and guidelines for universality, standardization, coordination, and regulation of these technologies [25–27]. Others are focusing on improving user interfaces, which will allow for enhanced accessibility and usability among the older adult population [6, 32, 33]. Trends in standardization and user interface development emphasize that connected and accessible systems can offer more cohesive and meaningful services to older adults. The development of devices that facilitate independence with instrumental activities of daily living (IADL) is also on the rise. These include systems to assist with banking, cooking, navigation/travel, nutrition, and shopping [6, 43, 52]. From the trends in current and recent AAL research, one can see a more holistic selection of devices for the support of physiological, psychological, and behavioral systems.

Table 4:

Current and Recent Developments in AAL Technology: Physical Health.

Table 5:

Current and Recent Developments in AAL Technology: Mental Health.

Table 6:

Current and Recent Developments in AAL Technology: Enhanced User Interfaces.

IATSL’s COACH (Cognitive Orthosis for Assisting with aCtivites in the Home). This system supports proper handwashing technique. AI analysis of video data determines which tips are given, and whether verbal or video cues are more appropriate [33].
Figure 3:

IATSL’s COACH (Cognitive Orthosis for Assisting with aCtivites in the Home).

This system supports proper handwashing technique. AI analysis of video data determines which tips are given, and whether verbal or video cues are more appropriate [33].

Table 7:

Current and Recent Developments in AAL Technology: Support of Daily Tasks.

Table 8:

Current and Recent Developments in AAL Technology: Safety.

Table 9:

Current and Recent Developments in AAL Technology: Standardization of AAL Systems.

5 Discussion: Theoretical Discourses Concerning Aging and Technology

Gerontological research has been notably characterized as “data rich and theory poor” [11]. Similarly, gerontechnology, the study of aging and technology, has not been adequately informed by theory [41]. While first- and second-generation AAL technologies are already established within the marketplace, most third-generation technologies are still in the research and development phase and may benefit from discussing theoretical discourses. The majority of the technologies summarized in this review lack explicit discussion and consideration of theoretical underpinnings of the AAL devices. This issue is reflected in some of the work being done to standardize AAL systems. For example, the AALIANCE project, which created a roadmap of priorities in AAL research and development, did not expressly indicate a recommendation for theoretically driven AAL research [25].

In an analysis of the discourses around technology and health care, Greenhalgh et al. [30] found that “different stakeholders hold different assumptions, values, and world views, talk past each other, and compete for recognition and resources.” While Greenhalgh et al.’s analysis identified four overlapping discourses (modernist, humanist, political economy, and change management), this will consider the intersection of the dominant bio-medical and neo-liberal discourses and the alternative active aging discourse.

The bio-medical discourse prevails within the academic literature addressing technology and aging [30]. This discourse emphasizes the impairments of older adults and medicalizes aging as a disease [30]. In the review of AAL systems, a number of the devices focused solely on addressing physiological needs. An overemphasis on the bio-medical perspective risks the legitimation of existing power relations, such as the doctor–patient relationship, the role of pharmaceuticals in the treatment of disease, and the emphasis on acute rather than preventative health care. Neo-liberal discourse on health and aging esteems the idea of economic systems as rational and self-regulatory systems based on the relationship between supply and demand.

Discussions concerning the aging population exemplify how the neo-liberal and bio-medical discourses not only intersect but also support one another. Older adults are often presented as being non-productive members of society who use an excess of resources, thus creating a burden on the productive members of society. AAL technologies are viewed as solutions to the problems associated with the aging population. In particular, technologies are supposed to reduce the use of scarce health-care and social resources and admissions to hospitals and nursing homes. While this is perhaps an oversimplification of the complex processes underlying the development of AAL solutions, it sadly resonates with the experiences of many gerontologists working in this field (including some of the current authors). Typically, the “needs” of older people are equated with deficits, losses, illnesses, and dependencies, and solutions are often seen as straightforward fixes to these. The solutions often fail to understand the context within which these “needs” are experienced (e.g., availability of support vs. isolation), the preferences of the person (e.g., feelings of stigmatization vs. feelings of mastery), and the impact on everyday life (e.g., changes in power relationships between person and caregiver). Moreover, the problematization of the old age experience provides a particular lens that excludes the many positive aspects of aging the agency of the individual, which, although compromised, should not be ignored. Ethically, when AAL technologies are developed without questioning the bio-medical agenda, they may unintentionally uphold assumptions and expectations that equate older adults with their medical conditions.

An alternative discourse that has emerged within gerontological research is the World Health Organization’s social model of health and active aging. In contrast to the bio-medical and neo-liberal perspectives, which see aging as a problem to be overcome or reconciled, this perspective can be applied to understand the more social components of technology development inherent in designing technologies to enhance well-being within the older population [56]. The active aging discourse focuses on the following: maintaining activity, health, and social participation; discussing the rights of older adults as active participants within society; and recognizing the processes of marginalization that often objectify, stigmatize, exclude, and impoverish older adults [63]. Some AAL projects adopt an approach that more closely aligns with this perspective. For example, the PALANTE project seeks to incorporate patient empowerment into the ICTs designed to manage their health [24]. According to this discourse, AAL technologies should focus on the abilities, rights, and desires of older adults in addition to issues pertaining to safety, security, the avoidance of harm, the reduction of risk, and the management of chronic diseases.

6 Conclusions

Gerontechnology has emerged as a consequence of the convergence of global population aging with the rapid acceleration of technological development. It resides at the crossroads of advancing technology and advancing age. This interdisciplinary field of scientific research perceives technology as a means to improve the life of aging people and to facilitate their participation as active citizens of the community [13]. Within gerontechnology, AAL is a relatively new approach to how technological solutions can meet the demands and needs of aging adults [4]. By increasing autonomy, self-confidence, and mobility: increasing or maintaining health and functional capacity, and promoting active lifestyles, AAL technologies are expected to reduce the risk of disability and institutionalization, enhance security, prevent social isolation, and maintain support networks, thus enabling older adults to age in place [58]. In order to achieve the objective of aging in place, AAL research and development must involve a collaboration between field experts within the health sciences, rehabilitation, gerontology, and social sciences as well as technical experts within engineering, computing science, and robotics [39, 58]. These collaborations have driven the development of assistive technology from stand-alone devices to more complex environmental systems that ultimately will be able to satisfy the multidimensional (e.g., physical, medical, psychological, and social) needs of a heterogeneous population of older adults living with a variety of challenges including cognitive impairment.

Funding: Institute of Aging (Canada) (Grant/Award Number: 278311), Forte (Sweden) (Grant/Award Number: 2012-1552), Economic and Social Research Council (UK) (Grant/Award Number: ES/K011138/1).


  • [1]

    AAL-WELL, Ambient Assistive Living Technologies for Wellness, Engagement and Long Life, Retrieved July 16, 2014, from http://www.aal-well.org/index.html, 2013.

  • [2]

    Aerotel Medical Systems, GeoSkeeper, Retrieved March 1, 2013, from http://www.aerotel.com/en/products-and-solutions/lifecare-mobile-solutions/geoskeeper.html, 2012.

  • [3]

    Aipermon, Products, Retrieved March 1, 2013, from http://www.aipermon.com/produkte-aipercarenutzung.htm, 2013.

  • [4]

    K. B. Akhlaki, M. V. Hurtado, M. J. Hornos, M. L. Rodríguez, C. Rodríguez-Domínguez, A. B. Pelegrina and M. J. Ortiz, Enabling correct design and formal analysis of Ambient Assisted Living systems, J. Syst. Softw. 85 (2012), 498–510.Google Scholar

  • [5]

    Aladdin, A home care system for the efficient monitoring of elderly people with dementia, Retrieved March 1, 2013, from http://www.aladdin-project.eu/home.aspx.

  • [6]

    Ambient Assisted Living Joint Program, Retrieved March 1, 2013, from www.aal-europe.eu, 2012.

  • [7]

    H. Arksey and L. O’Malley, Scoping studies: towards a methodological framework, Int. J. Soc. Res. Methodol. 8 (2005), 19–32.CrossrefGoogle Scholar

  • [8]

    D. W. Bates and M. D. Gawande, Improving safety with information technology, New Engl. J. Med. 348 (2003), 2426–2534.Google Scholar

  • [9]

    Bedmond, Behaviour pattern based assistant for early detection and management of neurodegenerative diseases, Retrieved March 1, 2013, from http://www.aladdin-project.eu/home.aspx, 2010.

  • [10]

    I. Bierhoff, A. van Berlo, J. Abascal, B. Allen, A. Civit, K. Fellbaum, E. Kemppainen, N. Bitterman, D. Freitas and K. Kristiansson, Smart home environment, in: Towards an Inclusive Future: Impact and Wider Potential of Information and Communication Technologies, P. R. W. Roe, ed., COST, Brussels, 2006.Google Scholar

  • [11]

    J. E. Birren, A contribution to the theory of the psychology of aging: a counterpart of development, in: Emergent Theories of Aging, J. E. Birren and V. L. Bengtson, eds., pp. 153–174, Springer, New York, 1988.Google Scholar

  • [12]

    Bosch Healthcare, Health buddy system, Retrieved March 1, 2013, from http://www.boschtelehealth.com/en/us/products/health_buddy/health_buddy.html, 2013.

  • [13]

    H. Bouma, V. Taipale, J. L. Fozard, D. G. Bouwhuis and J. E. M. H. van Bronswijk, Concepts and significance of gerontechnology: past, present, future (symposium), Gerontechnology 7 (2008), 77.CrossrefGoogle Scholar

  • [14]

    S. E. Brien, D. L. Lorenzetti, S. Lewis, J. Kennedy and W. A. Ghali, Overview of a formal scoping review on health system report cards, Implementation Science 5 (2010), 2.Google Scholar

  • [15]

    D. Bryant and B. R. Bryant, Assistive Technology for People with Disabilities, Allyn and Bacon, Boston, MA, 2003.Google Scholar

  • [16]

    K. C. Buckwalter, B. J. Wakefield, B. Hanna and J. Lehmann, New technology for medication adherence: electronically managed medication dispensing system, J. Gerontol. Nurs. 30 (2004), 5–8.CrossrefGoogle Scholar

  • [17]

    M. D. Buffum, E. Hutt, V. T. Chang, M. H. Craine and A. L. Snow, Cognitive impairment and pain management: review of issues and challenges, J. Rehabil. Res. Dev. 44 (2007), 315–330.CrossrefGoogle Scholar

  • [18]

    F. Cardinaux, D. Bhowmik, C. Abhayaratne and M. S. Hawley, Video based technology for ambient assisted living: a review of the literature, J. Ambient Intell. Smart Environ. 3 (2011), 253–269.Google Scholar

  • [19]

    CCE, Connected care for elderly persons suffering from dementia. Retrieved March 1, 2013, from http://www.cceproject.eu/, 2007.

  • [20]

    CompanionAble, Integrated cognitive assistive and domotic companion robot systems for ability and security, Retrieved March 1, 2013, from companionable.net, 2013.Google Scholar

  • [21]

    K. M. Daniel, C. L. Cason and S. Ferrell, Emerging technologies to enhance safety of older people in their homes, Geriatr. Nurs. 30 (2009), 384–389.Google Scholar

  • [22]

    Dem@Care, Dementia ambient care: multi-sensing monitoring for intelligent remote management and decision support, Retrieved March 1, 2013, from http://www.demcare.eu/, 2011.

  • [23]

    K. Doughty, K. Cameron and P. Garner, Three generations of telecare of the elderly, J. Telemed. Telecare 2 (1996), 71–80.CrossrefGoogle Scholar

  • [24]

    Empirica, PALANTE: patients leading and managing their healthcare through eHealth, Retrieved March 1, 2013, from http://www.empirica.com/themen/telemedizin/projekte_en.php?taken=aarg20.

  • [25]

    The European Ambient Assisted Living Innovation Alliance, Alliance2, Retrieved March 1, 2013, from http://www.aaliance.eu/public/.

  • [26]

    F. Furfari, M. R. Tazari and V. Eisemberg, universAAL: an open platform and reference specification for building AAL systems, ERCIM News 87 (2011), 44–45.Google Scholar

  • [27]

    German Commission for Electrical, Electronic, and Information Technologies, The German AAL Standardization Roadmap, pp. 1–99, VDE Association for Electrical, Electronic, and Information Technologies, Frankfurt, Germany, 2012.Google Scholar

  • [28]

    Giraff, Giraff, Retrieved March 1, 2013, from http://www.giraff.org/vardgivare/, 2013.

  • [29]

    K. Goodacre, C. McCreadie, S. Flanagan and P. Lansley, Enabling older people to stay at home: the costs of substituting and supplementing care with assistive technology, Brit. J. Occup. Ther. 71 (2008), 130–140.Google Scholar

  • [30]

    T. Greenhalgh, R. Proctor, R. Wherton, J. Sugarhood and L. Shaw, The organizing vision for telehealth and telecare: discourse analysis, BMJ Open 2 (2012), e001574.Google Scholar

  • [31]

    Hope, Smart home for elderly people, Retrieved March 1, 2013, from http://www.hope-project.eu/.

  • [32]

    I2HOME, Intuitive interaction for everyone with home appliances based on industry standards, Retrieved March 1, 2013, from http://www.i2home.org/Default.aspx?base.

  • [33]

    IATSL, Intelligent supportive environments for older adults, Retrieved March 1, 2013, from http://www.ot.utoronto.ca/iatsl/projects/intell_env.htm, 2012.

  • [34]

    Independa Inc., Technology enabled independent living solutions. Retrieved March 1, 2013, from http://independa.com/independa-integrated-cloudcare, 2013.

  • [35]

    Jontek Limited, m-Care, Retrieved March 1, 2013, from http://www.jontek.co.uk/Jontek/media/Media/Brochures%20and%20Leaflets/mCareleaflet.pdf, 2013.

  • [36]

    Just Checking Ltd., Just checking: helping people to stay at home, Retrieved March 1, 2013, from http://www.justchecking.co.uk/, 2013.

  • [37]

    T. Kleinberger, M. Becker, E. Ras, A. Holzinger and P. Muller, Ambient intelligence in assisted living: enable elderly people to handle future interfaces, in: Universal Access in HCI, C. Stephanidis ed., Part II, pp. 103–112, Springer-Verlag, Berlin, 2007.Google Scholar

  • [38]

    Koninklijke Philips Electronics N.V., Telehealth, Retrieved March 1, 2013, from http://telehealth.philips.com/, 2013.

  • [39]

    G. Lesnoff-Carvaglia ed., Gerontechnology: Growing Old in a Technological Society, Charles C. Thomas Publisher, LTD., Springfield, IL, 2007.Google Scholar

  • [40]

    R. G. Logsdon, L. E. Gibbons, S. M. McCurry and L. Teri, Assessing quality of life in older adults with cognitive impairment, Psychosom. Med. 64 (2002), 510–519.Google Scholar

  • [41]

    L. Lorenzen-Huber, M. Boutain, L. Camp, K. Shankar and K. H. Connelly, Privacy, technology, and aging: a proposed framework, Ageing Int. 36 (2011), 232–252.Google Scholar

  • [42]

    A. Muñoz, J. Augusto, A. Villa and J. Botía, Design and evaluation of an ambient assisted living system based on an argumentative multi-agent system, Pers. Ubiquitous Computing 15 (2011), 377–387.Google Scholar

  • [43]

    NDA Programme, NANA: novel assessment of nutrition and ageing, Retrieved March 1, 2013, from http://www.newdynamics.group.shef.ac.uk/nana.html, 2013.

  • [44]

    Northwood Intouch, The equipment, Retrieved March 1, 2013, from http://independa.com/independaintegrated-cloudcare, 2013.

  • [45]

    NSF, EAGER: an in-home health alert system with remote care coordination, Received from http://eldertech.missouri.edu/docs/Skubic, 2007.

  • [46]

    F. Oswald, H. W. Wahl, E. Voss, O. Schilling, T. Freytag, G. Auslander, N. Shoval, J. Heinik and R. Landau, The use of tracking technologies for the analysis of outdoor mobility in the face of dementia: first steps into a project and some illustrative findings from Germany, J. Hous. Elder. 24 (2010), 55–73.Google Scholar

  • [47]

    R. C. Petersen, Mild cognitive impairment as a diagnostic entity, J. Intern. Med. 256 (2004), 183–194.Google Scholar

  • [48]

    R. C. Petersen, Mild cognitive impairment, New Engl. J. Med. 364 (2011), 2227–2234.Google Scholar

  • [49]

    A. Piau, F. Nourhashémi, C. Hein, C. Caillaud and B. Vellas, Progress in the development of new drugs in Alzheimer’s disease, J. Nutr. Health Aging 15 (2011), 45–57.CrossrefGoogle Scholar

  • [50]

    M. Pieper, M. Antona and U. Cortés, Introduction to the special theme: ambient assisted living, Interuniversity Centre for Social Science Theory and Methodology, Retrieved from http://ercim-news.ercim.eu/en87/special/introduction-to-the special-theme-ambient-assisted-living, 2011.

  • [51]

    Rosetta, Homepage Rosetta, Retrieved March 1, 2013, from http://www.aal-rosetta.eu/smartsite.dws?id=135321, 2012.

  • [52]

    Smart Homes, Complete ambient assisted living, Retrieved March 1, 2013, from http://www.smarthomes.nl/Innovatie/Europees-Onderzoek/Caalyx.aspx.

  • [53]

    Simply Home, How it works, Retrieved March 1, 2013, from http://www.simplyhome.com/HowItWorks.html, 2013.

  • [54]

    A. Sixsmith, An evaluation of an intelligent home monitoring system, J. Telemed. Telecare 6 (2000), 63–72.CrossrefGoogle Scholar

  • [55]

    A. Sixsmith, New technologies to support living and quality of life for older people with dementia, Alzheimer’s Care Q. 7 (2006), 194–202.Google Scholar

  • [56]

    A. Sixsmith, Technology and the challenge of aging, in: Technologies for Active Aging, pp. 7–25, Springer, US, 2013.Google Scholar

  • [57]

    A. Sixsmith, G. Gibson, R. D. Orpwood and J. M. Torrington, New technologies to support independent living and quality of life for people with dementia, Alzheimer’s Care Q. 7 (2007), 194–202.Google Scholar

  • [58]

    A. Sixsmith, S. Mueller, F. Lull, M. Klein, I. Bierhoff, S. Deleaney, P. Byrne, S. Sproll, R. Savage and E. Avatangelou, A user-driven approach to developing ambient assisted living systems for older people: the SOPRANO project, in: Intelligent Technologies for Bridging the Grey Digital Divide, J. Soar, R. Swindell and P. Tsang eds., IGI Global, Hershey PA, 2010.Google Scholar

  • [59]

    The Smart Consortium, Self management supported by assistive, rehabilitation and telecare technologies, Retrieved March 1, 2013, from http//thesmartconsortium.org/smart-video/, 2012.

  • [60]

    Telefónica UK Limited – O2, Help at hand, Retrieved March 1, 2013, from http://www.o2.co.uk/health/helpathand, 2013.

  • [61]

    Tunstall, Solutions for dementia, Retrieved March 1, 2013, from http://apac.tunstall.com/solutions/dementia, 2013.

  • [62]

    Washington State University, WSU CASAS, Retrieved March 1, 2013, from http://ailab.eecs.wsu.edu/casas/.

  • [63]

    World Health Organization, Active ageing: from evidence to action, Paper presented at the Second United Nations World Assembly on Ageing. Retrieved May 12, 2010, from http://www.who.int/hpr/ageing, 2002.

  • [64]

    K. Wulff, G. G. Cummings, P. Marck and O. Yurtseven, Medication administration and patient safety: a mixed-method systematic review, J. Adv. Nurs. 67 (2011), 2080–2095.CrossrefGoogle Scholar

About the article

Corresponding author: Piper Jackson, IRMACS Centre, Simon Fraser University, 8888 University Drive, Burnaby, BC, Canada V5A 1S6, e-mail:

Received: 2014-09-23

Published Online: 2015-03-14

Published in Print: 2016-01-01

Citation Information: Journal of Intelligent Systems, Volume 25, Issue 1, Pages 55–69, ISSN (Online) 2191-026X, ISSN (Print) 0334-1860, DOI: https://doi.org/10.1515/jisys-2014-0136.

Export Citation

©2016 by De Gruyter.Get Permission

Citing Articles

Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.

Rustam Pirmagomedov and Yevgeni Koucheryavy
Internet of Things, 2019, Page 100120
Miguel Ángel Antón, Joaquín Ordieres-Meré, Unai Saralegui, and Shengjing Sun
Sensors, 2019, Volume 19, Number 14, Page 3113
Constantine Stephanidis, Gavriel Salvendy, Margherita Antona, Jessie Y. C. Chen, Jianming Dong, Vincent G. Duffy, Xiaowen Fang, Cali Fidopiastis, Gino Fragomeni, Limin Paul Fu, Yinni Guo, Don Harris, Andri Ioannou, Kyeong-ah (Kate) Jeong, Shin’ichi Konomi, Heidi Krömker, Masaaki Kurosu, James R. Lewis, Aaron Marcus, Gabriele Meiselwitz, Abbas Moallem, Hirohiko Mori, Fiona Fui-Hoon Nah, Stavroula Ntoa, Pei-Luen Patrick Rau, Dylan Schmorrow, Keng Siau, Norbert Streitz, Wentao Wang, Sakae Yamamoto, Panayiotis Zaphiris, and Jia Zhou
International Journal of Human–Computer Interaction, 2019, Volume 35, Number 14, Page 1229
Monique Chabot, Louie Delaware, Sabrena McCarley, Casey Little, Allison Nye, and Emily Anderson
Current Geriatrics Reports, 2019, Volume 8, Number 3, Page 232
Julia Offermann-van Heek and Martina Ziefle
Frontiers in Public Health, 2019, Volume 7
Ioan Susnea, Luminita Dumitriu, Mihai Talmaciu, Emilia Pecheanu, and Dan Munteanu
Sensors, 2019, Volume 19, Number 10, Page 2264
Palacín, Clotet, Martínez, Martínez, and Moreno
Robotics, 2019, Volume 8, Number 2, Page 27
Francisco Gomez-Donoso, Félix Escalona, Francisco Miguel Rivas, Jose Maria Cañas, and Miguel Cazorla
Computational Intelligence and Neuroscience, 2019, Volume 2019, Page 1
Elena Borelli, Giacomo Paolini, Francesco Antoniazzi, Marina Barbiroli, Francesca Benassi, Federico Chesani, Lorenzo Chiari, Massimiliano Fantini, Franco Fuschini, Andrea Galassi, Gian Andrea Giacobone, Silvia Imbesi, Melissa Licciardello, Daniela Loreti, Michele Marchi, Diego Masotti, Paola Mello, Sabato Mellone, Giuseppe Mincolelli, Carla Raffaelli, Luca Roffia, Tullio Salmon Cinotti, Carlo Tacconi, Paola Tamburini, Marco Zoli, and Alessandra Costanzo
Sensors, 2019, Volume 19, Number 5, Page 1258
M. Plöthner, K. Schmidt, L. de Jong, J. Zeidler, and K. Damm
BMC Geriatrics, 2019, Volume 19, Number 1
Elizabeth Downes, Ann Horigan, and Patrick Teixeira
Journal of the American Association of Nurse Practitioners, 2019, Volume 31, Number 3, Page 156
Caroline Byrne, Rem Collier, and Gregory O’Hare
Information, 2018, Volume 9, Number 7, Page 182
Christina Jaschinski and Somaya Ben Allouch
Journal of Ambient Intelligence and Humanized Computing, 2018
Javed Iqbal, Mihai Teodor Lazarescu, Osama Bin Tariq, Arslan Arif, and Luciano Lavagno
IEEE Transactions on Instrumentation and Measurement, 2018, Volume 67, Number 4, Page 789
Sheik Fattah, Nak-Myoung Sung, Il-Yeup Ahn, Minwoo Ryu, and Jaeseok Yun
Sensors, 2017, Volume 17, Number 10, Page 2311
Michael Decker, Nora Weinberger, Bettina-Johanna Krings, and Johannes Hirsch
Journal of Responsible Innovation, 2017, Page 1
Mei Lan Fang, Katherine Coatta, Melissa Badger, Sarah Wu, Margaret Easton, Louise Nygård, Arlene Astell, and Andrew Sixsmith
Journal of Applied Gerontology, 2017, Volume 36, Number 7, Page 808

Comments (0)

Please log in or register to comment.
Log in