Ontology-based Dementia Care Support System

Jeon, Hwawoo; Park, Sung-Kee; Choi, JongSuk; Lim, Yoonseob

doi:10.1109/embc.2018.8512965

Cited by 7 publications

(3 citation statements)

References 12 publications

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“…Ontology-based models combine data from multiple sources [97]. Researchers designed and successfully tested an ontology-based prototype knowledge system that can collect data from an RGB camera, 3D depth camera, and microphones [98].…”

Section: Resultsmentioning

confidence: 99%

Innovative Assisted Living Tools, Remote Monitoring Technologies, Artificial Intelligence-Driven Solutions, and Robotic Systems for Aging Societies: Systematic Review

Sapci

2019

JMIR Aging

119

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BackgroundThe increase in life expectancy and recent advancements in technology and medical science have changed the way we deliver health services to the aging societies. Evidence suggests that home telemonitoring can significantly decrease the number of readmissions, and continuous monitoring of older adults’ daily activities and health-related issues might prevent medical emergencies.ObjectiveThe primary objective of this review was to identify advances in assistive technology devices for seniors and aging-in-place technology and to determine the level of evidence for research on remote patient monitoring, smart homes, telecare, and artificially intelligent monitoring systems.MethodsA literature review was conducted using Cumulative Index to Nursing and Allied Health Literature Plus, MEDLINE, EMBASE, Institute of Electrical and Electronics Engineers Xplore, ProQuest Central, Scopus, and Science Direct. Publications related to older people’s care, independent living, and novel assistive technologies were included in the study.ResultsA total of 91 publications met the inclusion criteria. In total, four themes emerged from the data: technology acceptance and readiness, novel patient monitoring and smart home technologies, intelligent algorithm and software engineering, and robotics technologies. The results revealed that most studies had poor reference standards without an explicit critical appraisal.ConclusionsThe use of ubiquitous in-home monitoring and smart technologies for aged people’s care will increase their independence and the health care services available to them as well as improve frail elderly people’s health care outcomes. This review identified four different themes that require different conceptual approaches to solution development. Although the engineering teams were focused on prototype and algorithm development, the medical science teams were concentrated on outcome research. We also identified the need to develop custom technology solutions for different aging societies. The convergence of medicine and informatics could lead to the development of new interdisciplinary research models and new assistive products for the care of older adults.

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Section: Resultsmentioning

confidence: 99%

Innovative Assisted Living Tools, Remote Monitoring Technologies, Artificial Intelligence-Driven Solutions, and Robotic Systems for Aging Societies: Systematic Review

Sapci

2019

JMIR Aging

119

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“…In addition, the ontology will form the base for the development of the intelligent systems that can provide real‐time support for health care professionals in care delivery. Together with other ontologies that have been developed and applied in dementia care, 79‐81 DRANPTO has opened the opportunity to realize all these possibilities, and thus has made an important contribution to the research community in the agitation management domain and will help improve the quality of life for people living with dementia.…”

Section: Discussionmentioning

confidence: 99%

Developing an ontology for representing the domain knowledge specific to non‐pharmacological treatment for agitation in dementia

Zhang

Chang

et al. 2020

A&D Transl Res & Clin Interv

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Introduction A large volume of clinical care data has been generated for managing agitation in dementia. However, the valuable information in these data has not been used effectively to generate insights for improving the quality of care. Application of artificial intelligence technologies offers us enormous opportunities to reuse these data. For health data science to achieve this, this study focuses on using ontology to coding clinical knowledge for non‐pharmacological treatment of agitation in a machine‐readable format. Methods The resultant ontology—Dementia‐Related Agitation Non‐Pharmacological Treatment Ontology (DRANPTO)—was developed using a method adopted from the NeOn methodology. Results DRANPTO consisted of 569 concepts and 48 object properties. It meets the standards for biomedical ontology. Discussion DRANPTO is the first comprehensive semantic representation of non‐pharmacological management for agitation in dementia in the long‐term care setting. As a knowledge base, it will play a vital role to facilitate the development of intelligent systems for managing agitation in dementia.

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“…Dementia is the staggering sicknesses that lack broad consideration from relatives and guardians. Since the side effects of dementia could be very mind-boggling and may change ramblingly, family and guardian experience the ill effects of gloom and high mental worry from patient consideration [1]. In older adults, the symptom of dementia is decreased mobility and increased risk of falls [2].…”

Section: Introductionmentioning

confidence: 99%

Early Dementia Diagnosis Based on DNN Based Correlational Analysis and Fisher Criterion Based LDA using Morphological Brain Multiplexes

Kumar,

Dutta

2019

IJEAT

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The expanding recurrence of dementia happening is a disturbing patterning that has incited dire research intending to avert the improvement of the sickness. Diagnosing dementia in its beginning periods is an urgent advance in averting the improvement of the ailment into exacerbated side effects. Early mild cognitive impairment (EMCI) is the early symptom of dementia. This can be analyzed using mapping mind associations utilizing Magnetic Resonance Imaging (MRI). In the approach, for improving the correlational block, we presented an enhanced classifier also, for improving the performance of discriminative block, an optimized LDA is to be proposed. For correlational analysis, Deep Neural Network (DNN) is presented in this work. Besides, for discriminative analysis, a novel and efficient feature selection method is presented. Fisher criterion is used to select the most discriminatory and appropriate features to ensure consistent feature selection and classifier learning goals and to improve the classifier's performance. In the Mat lab framework this proposed method is implemented. The performance of this proposed approach is evaluated concerning Accuracy, Sensitivity, and Specificity

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Ontology-based Dementia Care Support System

Cited by 7 publications

References 12 publications

Innovative Assisted Living Tools, Remote Monitoring Technologies, Artificial Intelligence-Driven Solutions, and Robotic Systems for Aging Societies: Systematic Review

Innovative Assisted Living Tools, Remote Monitoring Technologies, Artificial Intelligence-Driven Solutions, and Robotic Systems for Aging Societies: Systematic Review

Developing an ontology for representing the domain knowledge specific to non‐pharmacological treatment for agitation in dementia

Early Dementia Diagnosis Based on DNN Based Correlational Analysis and Fisher Criterion Based LDA using Morphological Brain Multiplexes

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