Technology-Facilitated Detection of Mild Cognitive Impairment: A Review

Zhao, Wenbing; Pillai, Jagan A.; Leverenz, James B.; Luo, Xiong

doi:10.1109/eit.2018.8500151

Cited by 9 publications

(2 citation statements)

References 47 publications

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“…Moreover, the scope of IoT innovations and research includes a variety of data gathering technologies, each of which has a number of advantages and disadvantages. It is very important to assess what aspects of AD/dementia patients' care each technology can target [25]. Technologies such as radio frequency identification (RFID), near field communication (NFC), cameras, and sensors have been employed in various studies to support these patients and have alleviated their problems to some extent [26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

“…Some other reviews have examined only one specific dimension of AD/dementia such as physical activity monitoring [7,37]. Other studies have investigated the possibility of disease diagnosis using this technology [25,[37][38][39]. Some other works have only examined AD/ dementia patients' wandering symptom using IoT [40,41] or only those patients staying at home or nursing homes [39,42,43].…”

Section: Introductionmentioning

confidence: 99%

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Applications and Outcomes of Internet of Things for Patients with Alzheimer’s Disease/Dementia: A Scoping Review

Sheikhtaheri

Sabermahani

2022

BioMed Research International

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Objectives. We aimed to identify and classify the Internet of Things (IoT) technologies used for Alzheimer’s disease (AD)/dementia as well as the healthcare aspects addressed by these technologies and the outcomes of the IoT interventions. Methodology. We searched PubMed/MEDLINE, IEEE Explore, Web of Science, OVID, Scopus, Embase, Cochrane, and Google Scholar. In total, 13,005 papers were reviewed, 36 of which were finally selected. All the reviews were independently carried out by two researchers. In the case of any disagreement, the problem was resolved by holding a meeting and exchanging views. Due to the diversity of the reviewed studies, narrative analysis was performed. Results. Among the technologies used for the patients including radio frequency identification (RFID), near field communication (NFC), ZigBee, Bluetooth, global positioning system (GPS), sensors, and cameras, the sensors were employed in 36 studies, most of which were switch and vital sign monitoring sensors. The most common aspects of AD/dementia care monitored using these technologies were activities of daily living (ADLs) in 27 studies, followed by sleep patterns and disease diagnosis in 19 and 14 studies, respectively. Sleeping, medication, vital signs, agitation, memory, social interaction, apathy, movement, tracking, and fall were other aspects monitored by IoT. Then, their outcomes were reported. Conclusion. Using IoT for AD/dementia provides many opportunities for considering various aspects of this disease. Moreover, the ability to use various technologies for gathering patient-related data provides a comprehensive application for almost all aspects of the patients’ care with high accuracy.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Applications and Outcomes of Internet of Things for Patients with Alzheimer’s Disease/Dementia: A Scoping Review

Sheikhtaheri

Sabermahani

2022

BioMed Research International

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Indoor Localization and Human Activity Tracking with Multiple Kinect Sensors

Yang

Hans

Zhao

et al. 2019

Smart Assisted Living

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Artificial Intelligence for Cognitive Health Assessment: State-of-the-Art, Open Challenges and Future Directions

et al. 2023

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The subjectivity and inaccuracy of in-clinic Cognitive Health Assessments (CHA) have led many researchers to explore ways to automate the process to make it more objective and to facilitate the needs of the healthcare industry. Artificial Intelligence (AI) and machine learning (ML) have emerged as the most promising approaches to automate the CHA process. In this paper, we explore the background of CHA and delve into the extensive research recently undertaken in this domain to provide a comprehensive survey of the state-of-the-art. In particular, a careful selection of significant works published in the literature is reviewed to elaborate a range of enabling technologies and AI/ML techniques used for CHA, including conventional supervised and unsupervised machine learning, deep learning, reinforcement learning, natural language processing, and image processing techniques. Furthermore, we provide an overview of various means of data acquisition and the benchmark datasets. Finally, we discuss open issues and challenges in using AI and ML for CHA along with some possible solutions. In summary, this paper presents CHA tools, lists various data acquisition methods for CHA, provides technological advancements, presents the usage of AI for CHA, and open issues, challenges in the CHA domain. We hope this first-of-its-kind survey paper will significantly contribute to identifying research gaps in the complex and rapidly evolving interdisciplinary mental health field.

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Technology-Facilitated Detection of Mild Cognitive Impairment: A Review

Cited by 9 publications

References 47 publications

Applications and Outcomes of Internet of Things for Patients with Alzheimer’s Disease/Dementia: A Scoping Review

Applications and Outcomes of Internet of Things for Patients with Alzheimer’s Disease/Dementia: A Scoping Review

Indoor Localization and Human Activity Tracking with Multiple Kinect Sensors

Artificial Intelligence for Cognitive Health Assessment: State-of-the-Art, Open Challenges and Future Directions

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