ArticleJournal of neuroengineering and rehabilitation2019
Mobility assessment in people with Alzheimer disease using smartphone sensors.
Article in Journal of neuroengineering and rehabilitation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.
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Who cites it
28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 42 citations in OpenAlex.
- A Systematic Review of the Effects of Capsaicin on Alzheimer's Disease.International journal of molecular sciences · 2023Pooled it
- An update on mobile applications collecting data among subjects with or at risk of Alzheimer's disease.Frontiers in aging neuroscience · 2023Pooled it
- Effect of virtual running with exercise on functionality in pre-frail and frail elderly people: randomized clinical trial.Aging clinical and experimental research · 2023Trial
- Why Frailty Should Be Assessed in Older Adults Affected by Leprosy and How the Use of Smartphones Could Enhance This Health Monitoring.JMIR aging · 2026Article
- Wearable Electronic Devices for Alzheimer's Disease Care: A Systematic Review of Applications, Benefits, and Challenges.Health science reports · 2026Review
- Non-invasive brain stimulation on functional capacity in prefrail older adults: a protocol for a randomised clinical trial.Frontiers in aging neuroscience · 2026Article
- Curve walking gait analysis using depth camera and machine learning for detecting cognitive impairment.Frontiers in neurology · 2026Article
- The association between mobility and a cognitive measure of attention and processing speed in middle-aged adults: a cross-sectional study.Scientific reports · 2025Article
- Synthesis and Neurobehavioral Evaluation of a Potent Multitargeted Inhibitor for the Treatment of Alzheimer's Disease.Molecular neurobiology · 2025Article
- Article
- Electrochemical Analysis of Amyloid Plaques and ApoE4 with Chitosan-Coated Gold Nanostars for Alzheimer's Detection.Biosensors · 2024Article
- Validity of an android device for assessing mobility in people with chronic stroke and hemiparesis: a cross-sectional study.Journal of neuroengineering and rehabilitation · 2024Article
- Shifting From Active to Passive Monitoring of Alzheimer Disease: The State of the Research.Journal of the American Heart Association · 2024Review
- Smartphone-based activity tracking for spine patients: Current technology and future opportunities.World neurosurgery: X · 2024Review
- Smartphone-Based Sit-to-Stand Analysis for Mobility Assessment in Middle Age.Innovation in aging · 2024Article
- ADHD detection based on human action recognition.Neuroscience applied · 2024Article
- The Reliability and Accuracy of a Fall Risk Assessment Procedure Using Mobile Smartphone Sensors Compared with a Physiological Profile Assessment.Sensors (Basel, Switzerland) · 2023Article
- Revolutionizing the Early Detection of Alzheimer's Disease through Non-Invasive Biomarkers: The Role of Artificial Intelligence and Deep Learning.Sensors (Basel, Switzerland) · 2023Review
- Classification of Parkinson's disease stages with a two-stage deep neural network.Frontiers in aging neuroscience · 2023Article
- Machine learning detects altered spatial navigation features in outdoor behaviour of Alzheimer's disease patients.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUnderstanding the functional status of people with Alzheimer Disease (AD), both in a single (ST) and cognitive dual task (DT) activities is essential for identifying signs of early-stage neurodegeneration. This study aims to compare the performance quality of several tasks using sensors embedded in an Android device, among people at different stages of Alzheimer and people without dementia. The secondary aim is to analyze the effect of cognitive task performance on mobility tasks.
methodsThis is a cross-sectional study including 22 participants in the control group (CG), 18 in the group with mild AD and 22 in the group with moderate AD. They performed two mobility tests, under ST and DT conditions, which were registered using an Android device. Postural control was measured by medial-lateral and anterior-posterior displacements of the COM (MLDisp and APDisp, respectively) and gait, with the vertical and medial-lateral range of the COM (Vrange and MLrange). Further, the sit-to-stand (PStand) and turning and sit power (PTurnSit), the total time required to complete the test and the reaction time were measured.
resultsThere were no differences between the two AD stages either for ST or DT in any of the variables (p > 0.05). Nevertheless, people at both stages showed significantly lower values of PStand and PTurnSit and larger Total time and Reaction time compared to CG (p < 0.05). Further, Vrange is also lower in CDR1G than in CG (p < 0.05). The DT had a significant deleterious effect on MLDisp in all groups (p < 0.05) and on APDisp only in moderate AD for DT.
conclusionsOur findings indicate that AD patients present impairments in some key functional abilities, such as gait, turning and sitting, sit to stand, and reaction time, both in mild and moderate AD. Nevertheless, an exclusively cognitive task only influences the postural control in people with AD.
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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.