A design methodology for matching smart health requirements

Bellandi, Valerio; Ceravolo, Paolo; Cristiano, Alessia; Damiani, Ernesto; Sanna, Alberto; Trojaniello, Diana

doi:10.1002/cpe.6062

Cited by 11 publications

(6 citation statements)

References 29 publications

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“…The methodology proposed in [16] addresses a major emerging issue: the specification of a new generation of health platforms capable of monitoring people's quality of life, given that older adults are expected to represent the majority population in the years to come. This methodology supports the entire elicitation and requirements specification process: from the initial phase of gathering clinical, technological and end user requirements, to the choice of the most appropriate solution.…”

Section: Discussionmentioning

confidence: 99%

Specifying Requirements for Modern Software Development: A Test-Oriented Methodology

Esperón¹,

Pérez²,

Berná-Martínez³

et al. 2023

Int. J. Soft. Eng. Knowl. Eng.

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Most modern computer systems operate in distributed environments. To develop and test such applications, services, and systems, it is necessary to consider the physical devices, architectures, communication, security and deployment mechanisms involved. However, the requirements’ specification process still replicates that of traditional applications: details remain implicit and are hidden in the description. As a result, specifications are difficult to identify and, ultimately, tests are designed in the traditional way: they overlook constraints and fail to achieve the desired effects. Our objective is to design a methodology for specifying requirements in both traditional software and applications deployed in distributed environments. We present an iterative and incremental requirements specification methodology. This methodology allows us to describe functional requirements and incorporate non-functional or quality constraints, which is the main contribution of this proposal. To ensure that quality requirements are specified during the design phase, the methodology proposes a series of phases, stages and artefacts that ensure the discovery and consideration of these requirements. In order to find out the strengths and weaknesses of our methodology, we have carried out a comparative study with other similar proposals in the literature. To this end, evaluation criteria were defined by considering standards and good practices in Requirements Engineering. The results of the comparative study show that our methodology constitutes a solid procedure for a detailed requirements specification from the beginning of the software development cycle. This represents an advance over the rest of the proposals studied. Our methodology contributes to the simplification of the design and execution phases of software testing, enabling traceability between the specified requirements and the designed test cases.

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Section: Discussionmentioning

confidence: 99%

Specifying Requirements for Modern Software Development: A Test-Oriented Methodology

Esperón¹,

Pérez²,

Berná-Martínez³

et al. 2023

Int. J. Soft. Eng. Knowl. Eng.

View full text Add to dashboard Cite

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“…However, there have not been enough works for the methodology for deploying smart health technologies (usually in smart homes). Bellandi et al [4] is among the first works that propose a design methodology that matches smart health requirements. They argued that due to the rapidly aging world population, smart health technologies are about to playing an even more important role in caring for the aging population at homes.…”

Section: Methodology For Deploying Smart Health Technologiesmentioning

confidence: 99%

Integrating Voice-Based Machine Learning Technology into Complex Home Environments

Gao¹,

Jabbour²,

Ko³

et al. 2022

Preprint

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To demonstrate the value of machine learning based smart health technologies, researchers have to deploy their solutions into complex real-world environments with real participants. This gives rise to many, oftentimes unexpected, challenges for creating technology in a lab environment that will work when deployed in real home environments. In other words, like more mature disciplines, we need solutions for what can be done at development time to increase success at deployment time. To illustrate an approach and solutions, we use an example of an ongoing project that is a pipeline of voice based machine learning solutions that detects the anger and verbal conflicts of the participants. For anonymity, we call it the XYZ system. XYZ is a smart health technology because by notifying the participants of their anger, it encourages the participants to better manage their emotions. This is important because being able to recognize one's emotions is the first step to better managing one's anger. XYZ was deployed in 6 homes for 4 months each and monitors the emotion of the caregiver of a dementia patient. In this paper we demonstrate some of the necessary steps to be accomplished during the development stage to increase deployment time success, and show where continued work is still necessary. Note

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“…For this reason, an important emerging issue is the definition of a new generation of healthcare platforms capable of monitoring people's quality of life. In the contribution by Bellandi et al, “A design methodology for matching smart health requirements,” the authors propose a new methodology that supports the entire requirements elicitation process starting from the initial phase of gathering the requirements, both clinical, technological, and end‐user, up to the choice of the most suitable solution 6 . Their proposal provides a new iterative model in the smart healthcare research area.…”

Section: Themes Of This Special Issuementioning

confidence: 99%