| Sumario: | Background: While gait analysis is well-documented, turn performance—which is a more complex task and involves multiple brain regions—has been less explored. This study aims to assess the diagnostic potential of turn dynamics as a novel tool for detecting cognitive decline. Methods: We recruited 75 participants, including 26 neurotypical (NT) older adults, 25 with amnestic mild cognitive impairment (aMCI), and 24 with mild Alzheimer's disease (AD). Participants completed a dual-task walk and turn (DTWT) test using a dual Kinect setup while counting backwards by ones. Key measures analyzed included spatial-temporal parameters of gait and turn dynamics. Statistical analyses including analyses of variance and linear regression were performed to identify key features as well as to assess their correlation with cognitive performance. Results: Gait speed and stride time significantly differentiated among groups in DTWT conditions. More notably, turn dynamics, particularly segmental peak speeds and step length, displayed stronger discriminatory power with more significant p -values compared to gait features. Linear regression analysis indicated that turn dynamics had stronger correlations with executive function and working memory, suggesting a more pronounced relationship between cognitive performance and turn features than gait variables. Conclusion: In contrast to straight walk metrics, this study shows that DTWT turn dynamics are more sensitive to detect cognitive impairment. Consequently, incorporating turning movements into gait analysis techniques could enhance diagnostic protocols in clinical settings, offering a valuable tool for monitoring the progression of conditions associated with cognitive aging.
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