ArticleCureus2025
Using AI-Based Gait Analysis to Establish a 5-Meter Walk Time Cutoff for Discriminating Alzheimer's Disease.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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1 citing paper in PubMed.
- Evaluating guideline adherence in LLM studies using LLMs.Japanese journal of radiology · 2026Article
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7 authors.
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Abstract
Introduction A decline in gait function has been reported to occur early in Alzheimer's disease (AD), a major cause of dementia, suggesting that gait analysis may be a useful tool for dementia screening. However, a simple and practical analysis method or clear cutoff values have yet to be established. This study aimed to analyze gait function using the AI-powered smartphone application "Toruto," identify gait indicators characteristic of elderly patients with AD, and propose effective cutoff values for dementia discrimination. Methods A total of 147 participants were included in the study: 86 healthy elderly individuals and 61 elderly patients with AD (102 female patients and 45 male patients). Exclusion criteria included the use of a cane, the presence of pain during walking, or the need for walking assistance. Gait function at a normal walking speed was analyzed by the AI of "Toruto" to assess speed, rhythm, and left-right asymmetry. An unpaired t-test was used to compare the two groups, and cutoff values for dementia discrimination were calculated using receiver operating characteristic (ROC) curve analysis. The significance level was set at p < 0.05. Results The AD group showed a significant decline in gait speed (12.12 versus 3.98 sec/5 m), rhythm (10.92 versus 6.51), and left-right asymmetry (6.34 versus 2.15) compared with the healthy control group (p < 0.05). ROC curve analysis revealed that using a gait speed cutoff value of 5.85 sec/5 m yielded a sensitivity of 96.7% and a specificity of 96.5%. A rhythm cutoff of 7.06 (sensitivity: 80.3%, specificity: 65.1%) and a left-right asymmetry cutoff of 2.25 (sensitivity: 75.4%, specificity: 67.4%) were also effective discriminative indicators. Conclusion Gait analysis using the AI-powered smartphone application "Toruto" is effective for distinguishing Alzheimer's disease. This study demonstrated that cutoff values, such as 5.85 seconds for a 5-meter walk, serve as practical screening indicators for dementia. As an objective biomarker reflecting cognitive decline, gait function is expected to be useful for the early detection of Alzheimer's disease in both community and clinical settings.
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