Ubiquitous healthcare: a systematic mapping study

Saleemi, Maria; Anjum, Maria; Rehman, Mariam

doi:10.1007/s12652-020-02513-x

Cited by 11 publications

(3 citation statements)

References 115 publications

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“…This tool can therefore be applied in a great variety of disciplines. One example from the healthcare area is a study by Saleemi et al (2020) which uses systematic mapping to thoroughly analyze the available evidence on ubiquitous medical attention, in order to understand and evaluate the progress made in the field and identify the challenges that hinder further progress. Another example is a study by Drissi et al (2020) which aims to provide a general description and structured comprehension of the literature on connected mental health (CMH).…”

Section: Systematic Mapping Studymentioning

confidence: 99%

Electric Vehicles and the Use of Demand Projection Models: A Systematic Mapping of Studies

et al. 2023

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In today’s world, electric vehicles have become a real solution to the problem of pollution caused by petrol and diesel-powered vehicles. However, incorporating them successfully into the global vehicle park poses new challenges. Some of these challenges have to do with meeting the electricity demand, providing the physical installations for charging, and the size and capacity of the electric grid required to deliver the necessary supply. Solving these new problems requires determining or projecting the electrical and/or physical requirements involved, but there is no single model or methodology to do this, nor any single document which summarizes the existing information. To address this situation, this work presents the result of a systematic mapping study that seeks to provide organized information about the (mathematical) models for the demand arising from electric vehicles, as well as to answer a series of questions posed for this research. The results obtained show that there is a wide variety of models used to determine demand requirements –of either physical or electrical elements– in which mathematical modelling and operations research tools are normally used. Other results indicate that demand models are mainly focused on the electrical requirements rather than on physical ones, and that, in most cases, the type of vehicle for which the demand is studied is not mentioned.

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Section: Systematic Mapping Studymentioning

confidence: 99%

Electric Vehicles and the Use of Demand Projection Models: A Systematic Mapping of Studies

et al. 2023

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“…In turn, this interest would result in improved competency development and a stronger engagement with their learning of the course content linked to the problem situation. Furthermore, by encouraging students to carry out learning experiences within daily-life scenarios, we familiarised them with the concept of "ubiquitous healthcare" (i.e., the use of computing and communication devices to deliver healthcare services for patients and healthcare professionals, anytime and anywhere [61]) through "ubiquitous learning" [62,63]. Despite its hands-on nature, the problem situation above represents a simplified and contrived learning experience since students are only expected to reproduce a previously performed analysis on data collected by someone else.…”

Section: Learning Experience Definition and Structurementioning

confidence: 99%

Experiential Learning in Biomedical Engineering Education Using Wearable Devices: A Case Study in a Biomedical Signals and Systems Analysis Course

et al. 2022

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Biomedical engineering (BME) is one of the fastest-growing engineering fields worldwide. BME professionals are extensively employed in the health technology and healthcare industries. Hence, their education must prepare them to face the challenge of a rapidly evolving technological environment. Biomedical signals and systems analysis is essential to BME undergraduate education. Unfortunately, students often underestimate the importance of their courses as they do not perceive these courses’ practical applications in their future professional practice. In this study, we propose using blended learning spaces to develop new learning experiences in the context of a biomedical signals and systems analysis course to enhance students’ motivation and interest and the relevance of the materials learned. We created a learning experience based on wearable devices and cloud-based collaborative development environments such that the students turned daily-life scenarios into experiential learning spaces. Overall, our results suggest a positive impact on the students’ perceptions of their learning experience concerning relevance, motivation, and interest. Namely, the evidence shows a reduction in the variability of such perceptions. However, further research must confirm this potential impact. This confirmation is required given the monetary and time investment this pedagogical approach would require if it were to be implemented at a larger scale.

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“…A systematic mapping review is a type of review that allows the contextualization of systematic literature reviews within a broad literature and the identification of gaps in scientific literature. It is a review that seeks to identify not only the results of the works but also the existing links between the works carried out [20][21][22]. Therefore, the aim of this paper is to offer a systematic mapping review in order to (1) obtain a precise definition of AH to clarify the concept and use of AH and that it is not misused and (2) list the potential areas of application of AH.…”

Section: Introductionmentioning

confidence: 99%

Augmented Humanity: A Systematic Mapping Review

Guerrero

Silva

Fernández-Caballero

et al. 2022

Sensors

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Augmented humanity (AH) is a term that has been mentioned in several research papers. However, these papers differ in their definitions of AH. The number of publications dealing with the topic of AH is represented by a growing number of publications that increase over time, being high impact factor scientific contributions. However, this terminology is used without being formally defined. The aim of this paper is to carry out a systematic mapping review of the different existing definitions of AH and its possible application areas. Publications from 2009 to 2020 were searched in Scopus, IEEE and ACM databases, using search terms “augmented human”, ”human augmentation” and “human 2.0”. Of the 16,914 initially obtained publications, a final number of 133 was finally selected. The mapping results show a growing focus on works based on AH, with computer vision being the index term with the highest number of published articles. Other index terms are wearable computing, augmented reality, human–robot interaction, smart devices and mixed reality. In the different domains where AH is present, there are works in computer science, engineering, robotics, automation and control systems and telecommunications. This review demonstrates that it is necessary to formalize the definition of AH and also the areas of work with greater openness to the use of such concept. This is why the following definition is proposed: “Augmented humanity is a human–computer integration technology that proposes to improve capacity and productivity by changing or increasing the normal ranges of human function through the restoration or extension of human physical, intellectual and social capabilities.”

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Ubiquitous healthcare: a systematic mapping study

Cited by 11 publications

References 115 publications

Electric Vehicles and the Use of Demand Projection Models: A Systematic Mapping of Studies

Electric Vehicles and the Use of Demand Projection Models: A Systematic Mapping of Studies

Experiential Learning in Biomedical Engineering Education Using Wearable Devices: A Case Study in a Biomedical Signals and Systems Analysis Course

Augmented Humanity: A Systematic Mapping Review

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