The Dance of Mind and Body: Unlocking Clues from Gait Analysis

Published on October 4, 2022

Imagine a dance, where the mind and body move together in perfect harmony. Just like a skilled dancer, our cognitive and motor abilities must synchronize seamlessly for us to navigate the world around us. Researchers have conducted a study on middle-aged and aging individuals with normal cognition and mild cognitive impairment (MCI) to understand how their motor and cognitive interactions affect their gait. MCI is a stage between cognitive normality and dementia, with a heightened risk of developing Alzheimer’s disease. By analyzing gait patterns during dual-task activities, such as walking while performing calculations, scientists were able to identify significant differences in cadence between the MCI group and the normal elderly group. This suggests that dual tasks based on cognitive-motor gait analysis can play a role in early identification of MCI. The findings contribute to improving the clinical diagnosis of MCI, opening doors for interventions at this crucial stage to potentially delay the onset of Alzheimer’s disease. Curious to learn more? Explore the full article!

BackgroundMild cognitive impairment (MCI) is considered a transitional stage between cognitive normality and dementia among the elderly, and its associated risk of developing Alzheimer’s disease (AD) is 10–15 times higher than that of the general population. MCI is an important threshold for the prevention and control of AD, and intervention in the MCI stage may be the most effective strategy to delay the occurrence of AD.Materials and methodsIn this study, 68 subjects who met the inclusion criteria were divided into an MCI group (38 subjects) and normal elderly (NE) group (30 subjects). Both groups underwent clinical function assessments (cognitive function, walking function, and activities of daily living) and dual-task three-dimensional gait analysis (walking motor task and walking calculation task). Spatial-temporal parameters were obtained and reduced by principal component analysis, and the key biomechanical indexes were selected. The dual-task cost (DTC) was calculated for intra-group (task factor) and inter-group (group factor) comparisons.ResultsThe results of the principal component analysis showed that the cadence parameter had the highest weight in all three walking tasks. In addition, there were significant differences in the cadence both walking motor task (WMT) vs. walking task (WT) and walking calculation task (WCT) vs. WT in the MCI group. The cadence in the NE group only showed a significant difference between WMT and WT. The only differences between the MCI group and NE group was DTC cadence in WCT, and no differences were found for cadence in any of the three walking tasks.ConclusionThe results show that dual tasks based on cognitive-motor gait analysis of DTCcadence in MCI have potential value for application in early identification and provide theoretical support to improve the clinical diagnosis of MCI.

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