A Systematic Literature Review on Devices and Systems for Ambient Assisted Living: Solutions and Trends from Different User Perspectives

Cedillo, Priscila; Sánchez, Cristina; Campos, Karina; Bermeo, Alexandra

doi:10.1109/icedeg.2018.8372367

Cited by 39 publications

(25 citation statements)

References 43 publications

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“…Obtained results are correlated with other systematic reviews such as [84], focused on trends and user perspectives in devices for ambient assisted living. They analysed 48 studies in the field and concluded that the majority of technologies are mainly focused on gathering, processing, storing and transmitting the data obtained in order to monitor the health and wellbeing of the dependant users.…”

Section: Discussionmentioning

confidence: 52%

“…On the other hand, as [85] affirms, most care and assistance developments found in the reviewed papers are usually too techno-centric (a trend also reported in [84,86]), so care services are too fragmented and provided by different unrelated stakeholders. In fact, it can be observed from our results that the other main ecosystem architecture type considered in the literature consists in ecosystems that share a common infrastructure, such as cloud [21,46,61] or mobile [49,73], where this common technology is shared among all actors and it provides tools for the development of new applications while at the same time maintaining independence on the contributions.…”

Section: Discussionmentioning

confidence: 79%

“…The actual structure of such a service also depends on the interaction between the provider and the user, and may ultimately (and dynamically) vary according to the flow of that interaction.” For that reason these services may involve atomic software and technological services along with human intervention. In this respect, most reviewed papers provide a wide range of combined services in order to achieve the main ecosystem goal, a trend that has been already reported in other literature reviews related to technologies for care and assistance provision [4,84,86].…”

Section: Discussionmentioning

confidence: 82%

“…In terms of the employed technologies, we observe a wide range of technologies which have been considered in the selected studies (see Section 4.12), and almost all papers cite the combination of one or more technology to be supported (e.g., [10,53,57,73]). This is expected as services provided in ecosystem environments usually involve many different stakeholders and objectives by definition; this is related to other surveys that explore the tools employed for assistance provision [84,86].…”

Section: Discussionmentioning

confidence: 99%

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Technological Ecosystems in Care and Assistance: A Systematic Literature Review

Marcos-Pablos

García-Peñalvo

2019

Sensors

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Applying the concepts of technological ecosystems to the care and assistance domain is an emerging field that has gained interest during the last years, as they allow to describe the complex relationships between actors in a technologically boosted care domain. In that context, this paper presents a systematic review and mapping of the literature to identify, analyse and classify the published research carried out to provide care and assistance services under a technological ecosystems’ perspective. Thirty-seven papers were identified in the literature as relevant and analysed in detail (between 2003–2018). The main findings show that it is indeed an emerging field, as few of the found ecosystem proposals have been developed in the real world nor have they been tested with real users. In addition, a lot of research to date reports the proposal of platform-centric architectures developed over existing platforms not specifically developed for care and services provision. Employed sensor technologies for providing services have very diverse natures depending on the intended services to be provided. However, many of these technologies do not take into account medical standards. The degree of the ecosystems’ openness to adding new devices greatly depends on the approach followed, such as the type of middleware considered. Thus, there is still much work to be done in order to equate other more established ecosystems such as business or software ecosystems.

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Section: Discussionmentioning

confidence: 52%

Section: Discussionmentioning

confidence: 79%

Section: Discussionmentioning

confidence: 82%

Section: Discussionmentioning

confidence: 99%

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Technological Ecosystems in Care and Assistance: A Systematic Literature Review

Marcos-Pablos

García-Peñalvo

2019

Sensors

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“…Sound in general, and speech in particular, constitutes a natural and intuitive way for the development of human-machine interfaces in emerging IoT scenarios [1]. This is one of the reasons why networks of wireless computing devices incorporating microphones (and sometimes loudspeakers), also known as wireless acoustic sensor networks (WASNs), are increasingly attracting the interest of the IoT community [2][3][4][5]. In this context, WASNs may be easily integrated into existing living or industrial environments with well-known advantages [6].…”

Section: Introductionmentioning

confidence: 99%

Practical Considerations for Acoustic Source Localization in the IoT Era: Platforms, Energy Efficiency, and Performance

Belloch

Badía

Igual

et al. 2019

IEEE Internet Things J.

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The rapid development of the Internet of Things (IoT) has posed important changes in the way emerging acoustic signal processing applications are conceived. While traditional acoustic processing applications have been developed taking into account high-throughput computing platforms equipped with expensive multichannel audio interfaces, the IoT paradigm is demanding the use of more flexible and energy-efficient systems. In this context, algorithms for source localization and ranging in wireless acoustic sensor networks can be considered an enabling technology for many IoT-based environments including security, industrial and health-care applications. This paper is aimed at evaluating important aspects dealing with the practical deployment of IoT systems for acoustic source localization. Recent Systems-On-Chip (SoC) composed of low-power multicore processors, combined with a small graphics accelerator (or GPU), yield a notable increment of the computational capacity needed in intensive signal processing algorithms while partially retaining the appealing low power consumption of embedded systems. Different algorithms and implementations over several state-of-the-art platforms are discussed, analyzing important aspects such as the trade-offs between performance, energy efficiency and exploitation of parallelism by taking into account real-time constraints.

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