AAL open source system for the monitoring and intelligent control of nursing homes

González-Usach, Régel; Collado, Vicente; Esteve, Manuel; Palau, Carlos E.

doi:10.1109/icnsc.2017.8000072

Cited by 11 publications

(11 citation statements)

References 14 publications

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“…We classified 34 publications as studies that employed real-world settings. Multimedia Appendix 3 [ 13 , 18 , 19 , 34 - 58 , 63 , 69 , 82 , 95 , 100 , 310 , 312 ] summarizes the characteristics of these publications. The data used originated from the United States in 12 studies, from Canada in 5 studies, and from Spain in 3 studies.…”

Section: Resultsmentioning

confidence: 99%

“…We identified 6 publications [ 7 , 21 , 64 - 67 ], specifically focusing on the ethical, legal, and social aspects of AI in nursing care. In addition, 7 publications [ 35 , 41 , 57 , 59 , 60 , 68 , 69 ], which were either reviews or studies including real-world settings, addressed selected ELSI aspects when discussing results or limitations of their work. Recurring aspects were consent (of care dependents or nurses), data privacy and safety , acceptance and implications for work processes and workforce , such as lack of human interaction and communication skills or the fear of replacement of nurses by technology and the implications arising from choosing humanoid designs for hardware hosting intelligent technologies [ 41 , 67 ].…”

Section: Resultsmentioning

confidence: 99%

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Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review

et al. 2021

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Background Artificial intelligence (AI) holds the promise of supporting nurses’ clinical decision-making in complex care situations or conducting tasks that are remote from direct patient interaction, such as documentation processes. There has been an increase in the research and development of AI applications for nursing care, but there is a persistent lack of an extensive overview covering the evidence base for promising application scenarios. Objective This study synthesizes literature on application scenarios for AI in nursing care settings as well as highlights adjacent aspects in the ethical, legal, and social discourse surrounding the application of AI in nursing care. Methods Following a rapid review design, PubMed, CINAHL, Association for Computing Machinery Digital Library, Institute of Electrical and Electronics Engineers Xplore, Digital Bibliography & Library Project, and Association for Information Systems Library, as well as the libraries of leading AI conferences, were searched in June 2020. Publications of original quantitative and qualitative research, systematic reviews, discussion papers, and essays on the ethical, legal, and social implications published in English were included. Eligible studies were analyzed on the basis of predetermined selection criteria. Results The titles and abstracts of 7016 publications and 704 full texts were screened, and 292 publications were included. Hospitals were the most prominent study setting, followed by independent living at home; fewer application scenarios were identified for nursing homes or home care. Most studies used machine learning algorithms, whereas expert or hybrid systems were entailed in less than every 10th publication. The application context of focusing on image and signal processing with tracking, monitoring, or the classification of activity and health followed by care coordination and communication, as well as fall detection, was the main purpose of AI applications. Few studies have reported the effects of AI applications on clinical or organizational outcomes, lacking particularly in data gathered outside laboratory conditions. In addition to technological requirements, the reporting and inclusion of certain requirements capture more overarching topics, such as data privacy, safety, and technology acceptance. Ethical, legal, and social implications reflect the discourse on technology use in health care but have mostly not been discussed in meaningful and potentially encompassing detail. Conclusions The results highlight the potential for the application of AI systems in different nursing care settings. Considering the lack of findings on the effectiveness and application of AI systems in real-world scenarios, future research should reflect on a more nursing care–specific perspective toward objectives, outcomes, and benefits. We identify that, crucially, an advancement in technological-societal discourse that surrounds the ethical and legal implications of AI applications in nursing care is a necessary next step. Further, we outline the need for greater participation among all of the stakeholders involved.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review

et al. 2021

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“… Gonzalez-Usach et al (2017) have presented SAFE-ECH - an IoT SOA system to monitor and control AAL residences. The system includes functionalities for the management of multiple residences, accessing globally and locally through an HMI.…”

Section: Data Analysis: Systematic Mapmentioning

confidence: 99%

Ambient intelligence governance review: from service-oriented to self-service

Ponce¹,

Abdulrazak²

2022

PeerJ Computer Science

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The current generation of connected devices and the Internet of Things augment people’s capabilities through ambient intelligence. Ambient Intelligence (AmI) support systems contain applications consuming available services in the environment to serve users. A well-known design of these applications follows a service architecture style and implement artificial intelligence mechanisms to maintain an awareness of the context: The service architecture style enables the distribution of capabilities and facilitates interoperability. Intelligence and context-awareness provide an adaptation of the environment to improve the interaction. Smart objects in distributed deployments and the increasing machine awareness of devices and people context also lead us to architectures, including self-governed policies providing self-service. We have systematically reviewed and analyzed ambient system governance considering service-oriented architecture (SOA) as a reference model. We applied a systematic mapping process obtaining 198 papers for screening (out of 712 obtained after conducting searches in research databases). We then reviewed and categorized 68 papers related to 48 research projects selected by fulfilling ambient intelligence and SOA principles and concepts. This paper presents the result of our analysis, including the existing governance designs, the distribution of adopted characteristics, and the trend to incorporate service in the context-aware process. We also discuss the identified challenges and analyze research directions.

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“…Two 3D cameras cover the whole environment and a user interface allows the interaction with the environment from an interactive graphical interface to select elements of the environment and trigger the actions necessary to achieve the proposed objectives. 6 To support actions over the environment, the system counts on three robots with very different and complementary features: a Cartesian robot hanging on the ceiling (CAPDI), a second double-handed robot for complex manipulation operations (BAXTER) and a single robot arm over the table surface (MICO).…”

Section: Hardwarementioning

confidence: 99%

“…In this context the efforts focus on the implantation of intelligent services to support daily life therapies. In [6], an open code system is presented aimed at generating an intelligent environment able to monitor the patient from diverse sensors, analyze the obtained data and manage the actions to perform in an intelligent manner through a complex events processor.…”

Section: Introductionmentioning

confidence: 99%

Suitable Task Allocation in Intelligent Systems for Assistive Environments

Vinagre

Aranda

Casals

2019

Advances in Intelligent Systems and Computing

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The growing need of technological assistance to provide support to people with special needs demands for systems more and more efficient and with better performances. With this aim, this work tries to advance in a multirobot platform that allows the coordinated control of different agents and other elements in the environment to achieve an autonomous behavior based on the user's needs or will. Therefore, this environment is structured according to the potentiality of each agent and elements of this environment and of the dynamic context, to generate the adequate actuation plans and the coordination of their execution.

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AAL open source system for the monitoring and intelligent control of nursing homes

Cited by 11 publications

References 14 publications

Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review

Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review

Ambient intelligence governance review: from service-oriented to self-service

Suitable Task Allocation in Intelligent Systems for Assistive Environments

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