ArticleJournal of Alzheimer's disease : JAD2021
Combining Multimodal Behavioral Data of Gait, Speech, and Drawing for Classification of Alzheimer's Disease and Mild Cognitive Impairment.
Article in Journal of Alzheimer's disease : JAD, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 3 of them syntheses that pooled it.
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Who cites it
29 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Diagnostic utility of speech-based biomarkers in mild cognitive impairment: a systematic review and meta-analysis.Age and ageing · 2025Pooled it
- Neural Mechanisms of Motor Dysfunction in Mild Cognitive Impairment and Alzheimer's Disease: A Systematic Review.Journal of Alzheimer's disease reports · 2022Pooled it
- Speech changes in old age: Methodological considerations for speech-based discrimination of healthy ageing and Alzheimer's disease.International journal of language & communication disordersPooled it
- Recovery strategies during trip-like support surface perturbations while walking in older adults with mild cognitive impairment.GeroScience · 2026Article
- Article
- WATCH-SS: Developing a Trustworthy and Explainable Modular Framework for Detecting Cognitive Impairment from Spontaneous Speech.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2026Article
- SpeechCARE: dynamic multimodal modeling for cognitive screening in diverse linguistic and speech task contexts.NPJ digital medicine · 2025Article
- WATCH-SS: Developing a Trustworthy and Explainable Modular Framework for Detecting Cognitive Impairment from Spontaneous Speech.medRxiv : the preprint server for health sciences · 2025Article
- Dual-task walking for early detection of Alzheimer's disease: comparative analysis of tasks using whole-body gait variables.BMC geriatrics · 2025Article
- Optimizing mobile cognitive assessment reduces administration time while maintaining screening accuracy in older adults.Scientific reports · 2025Article
- Utility of synthetic musculoskeletal gaits for generalizable healthcare applications.Nature communications · 2025Article
- Alzheimer's disease digital biomarkers multidimensional landscape and AI model scoping review.NPJ digital medicine · 2025Article
- Artificial Intelligence in the Diagnosis of Neurological Diseases Using Biomechanical and Gait Analysis Data: A Scopus-Based Bibliometric Analysis.Neurology international · 2025Review
- Effectiveness of digital screening tools in detecting cognitive impairment among community-dwelling elderly in Northern China: A large cohort study.The journal of prevention of Alzheimer's disease · 2025Article
- Association between nutritional status and gait performance in Alzheimer's disease.CNS neuroscience & therapeutics · 2024Article
- Shifting From Active to Passive Monitoring of Alzheimer Disease: The State of the Research.Journal of the American Heart Association · 2024Review
- An effective screening model for subjective cognitive decline in community-dwelling older adults based on gait analysis and eye tracking.Frontiers in aging neuroscience · 2024Article
- Distinct eye movement patterns to complex scenes in Alzheimer's disease and Lewy body disease.Frontiers in neuroscience · 2024Article
- Classification of Mild Cognitive Impairment and Alzheimer's Disease Using Manual Motor Measures.Neuro-degenerative diseases · 2024Article
- Multimodal learning of clinically accessible tests to aid diagnosis of neurodegenerative disorders: a scoping review.Health information science and systems · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGait, speech, and drawing behaviors have been shown to be sensitive to the diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, previous studies focused on only analyzing individual behavioral modalities, although these studies suggested that each of these modalities may capture different profiles of cognitive impairments associated with AD.
objectiveWe aimed to investigate if combining behavioral data of gait, speech, and drawing can improve classification performance compared with the use of individual modality and if each of these behavioral data can be associated with different cognitive and clinical measures for the diagnosis of AD and MCI.
methodsBehavioral data of gait, speech, and drawing were acquired from 118 AD, MCI, and cognitively normal (CN) participants.
resultsCombining all three behavioral modalities achieved 93.0% accuracy for classifying AD, MCI, and CN, and only 81.9% when using the best individual behavioral modality. Each of these behavioral modalities was statistically significantly associated with different cognitive and clinical measures for diagnosing AD and MCI.
conclusionOur findings indicate that these behaviors provide different and complementary information about cognitive impairments such that classification of AD and MCI is superior to using either in isolation.
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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.