ArticleSensors (Basel, Switzerland)2020
Internet of Things and Machine Learning for Healthy Ageing: Identifying the Early Signs of Dementia.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Technology-Enhanced Health Care in Smart Homes: Scoping Review of Sensor Technologies, Clinical Applications, Integration Challenges, and Future Directions.JMIR medical informatics · 2026Article
- Smart home Internet of Things-based behavioural analysis for early detection of cognitive decline: toward Saudi future vision.mHealth · 2026Article
- Digital Neuropsychology beyond Computerized Cognitive Assessment: Applications of Novel Digital Technologies.Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists · 2024Review
- The promise of digital healthcare technologies.Frontiers in public health · 2023Review
- In-Home Monitoring Technology for Aging in Place: Scoping Review.Interactive journal of medical research · 2022Article
- Addressing Mild Cognitive Impairment and Boosting Wellness for the Elderly through Personalized Remote Monitoring.Healthcare (Basel, Switzerland) · 2022Article
- Are Smart Homes Adequate for Older Adults with Dementia?Sensors (Basel, Switzerland) · 2022Review
- Analysis of Relationship between Natural Standing Behavior of Elderly People and a Class of Standing Aids in a Living Space.Sensors (Basel, Switzerland) · 2022Article
- Discrimination of the Cognitive Function of Community Subjects Using the Arterial Pulse Spectrum and Machine-Learning Analysis.Sensors (Basel, Switzerland) · 2022Article
- A Versatile and Ubiquitous IoT-Based Smart Metabolic and Immune Monitoring System.Computational intelligence and neuroscience · 2022Article
- Use of the Clock Drawing Test and the Rey-Osterrieth Complex Figure Test-copy with convolutional neural networks to predict cognitive impairment.Alzheimer's research & therapy · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identifying the symptoms of the early stages of dementia is a difficult task, particularly for older adults living in residential care. Internet of Things (IoT) and smart environments can assist with the early detection of dementia, by nonintrusive monitoring of the daily activities of the older adults. In this work, we focus on the daily life activities of adults in a smart home setting to discover their potential cognitive anomalies using a public dataset. After analysing the dataset, extracting the features, and selecting distinctive features based on dynamic ranking, a classification model is built. We compare and contrast several machine learning approaches for developing a reliable and efficient model to identify the cognitive status of monitored adults. Using our predictive model and our approach of distinctive feature selection, we have achieved 90.74% accuracy in detecting the onset of dementia.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.