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Rebecca Amariglio

dblp:235/2122 · also Rebecca E. Amariglio · DBLP profile ↗
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3ranked-venue papers
0as first author
2since 2021 · last 2022
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Immersive interaction · 81% Health and well-being technologies · 19%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Health and well-being technologies › rehabilitation
cognitive rehabilitation
0.212022
The cupboard task: An immersive virtual reality-based system for everyday memory assessment · Int. J. Hum. Comput. Stud. 2022
Immersive interaction › virtual reality
immersive virtual reality
0.212022
The cupboard task: An immersive virtual reality-based system for everyday memory assessment · Int. J. Hum. Comput. Stud. 2022

Methods — techniques the papers use, named apart from their topics

reliability analysis · 0.6correlation analysis · 0.6comparative study · 0.6ANOVA · 0.6
YearPublicationVenuePosition
2022 The cupboard task: An immersive virtual reality-based system for everyday memory assessment
abstract
Virtual Reality (VR) has the capacity to be used in cognitive rehabilitation interventions for diagnostic and training purposes. This technology allows the development of proposals that traditionally have been only implemented using physical elements that imply greater resources and a lesser degree of automation. This work presents an immersive virtual reality (IVR) application (the Cupboard task) for the evaluation of memory in a more ecological way and based on an activity of daily living (ADL). To appraise its construct validity, we have carried out a comparative study with a traditional method of memory assessment (method of loci). To check for any association between performance and age, performance with years of education, and reaction time with age, the Pearson's correlation was used. One-way ANOVA was used to check for differences in performance by gender. We also performed a reliability analysis with a two way mixed effects model where people effects are random and measures effects are fixed. Therefore, intra-class correlation coefficient with absolute agreement was reckoned to assess the consistency or concordance of the measures made by both the method of loci and the cupboard IVR task. Both tasks were evaluated on a sample of 22 healthy participants who voluntarily took part in the experiment. The results obtained showed a high degree of concordance between both memory performance measures, which assumes good clinical relevance. In addition, other age-related effects were found, common to memory assessment tasks. This work showed that it is possible to use an IVR application to successfully assess everyday memory. We have also demonstrated the potential of IVR to develop valid tests that assess memory functions reliably and efficiently and within ecologically valid contexts. The results obtained open the door to its use in clinical settings for cognitive training (and promoting cognitive health) of patients with mild cognitive impairment (MCI), severe cognitive impairment (SCI) such as Alzheimer or Dementia, etc., with full guarantees of application, although it must first be validated through a randomized control trial (RCT). The degree of usability of the Cupboard task was very high according to the test carried out by the participants.
José Varela 0002, Jorge Buele, Rebecca Amariglio, Iván García-Magariño, Guillermo Palacios Navarro 0001
Int. J. Hum. Comput. Stud.3
2021 Comparison of Machine Learning Algorithms for Earlier Detection of Cognitive Decline from Clinical Notes in the Electronic Health Records
John Laurentiev, Jie Yang 0039, Ying-Chih Lo, Rebecca Amariglio, Gad A. Marshall, Li Zhou 0007
AMIA5
2020 Investigating Clinical Documentation of Subjective Cognitive Decline in the Electronic Health Records
Rebecca Amariglio, Li Zhou 0007
AMIA2