Smartphone-based gait analysis with rhythmic auditory cueing discriminates cognitive impairment stages in a resource-limited African setting

痴呆 认知 物理医学与康复 步态 认知障碍 医学 听力学 跨步 步态分析 节奏 认知测验 提示语 认知功能衰退 执行功能障碍 心理学 疾病 阿尔茨海默病
作者
Samwel Sylvester Msigwa,Innocent Rwiza Mwombeki,Sadiki Mandari
出处
期刊:Age and Ageing [Oxford University Press]
卷期号:55 (4)
标识
DOI:10.1093/ageing/afag098
摘要

BACKGROUND: Early cognitive impairment detection in sub-Saharan Africa is limited by few specialists, restricted testing and cultural barriers. Conventional dual-task paradigms may be unsuitable for low-literacy populations, whereas rhythmic auditory cueing (RAC) using familiar music may provide a culturally neutral, engaging alternative. This study aimed to validate smartphone-based gait assessment across cognitive stages in adults attending a memory-clinic. METHODS: Sixty adults aged 60-85 years attending a memory clinic were stratified into Subjective Cognitive Decline (SCD, n = 21), Mild Cognitive Impairment (MCI, n = 23) and Dementia (n = 16). Smartphone-based spatiotemporal and kinematic gait parameters were collected under uncued, dual-task (fruits/vegetables naming) and RAC conditions. Between-group differences were examined using MANCOVA or rank-based MANOVA, adjusting for age, sex and body mass index, with Bonferroni-corrected post hoc tests. Correlations with executive function were analysed using false discovery rate-corrected Spearman tests. Receiver operating characteristic analyses determined discriminatory performance. RESULTS: Gait impairment increased with cognitive decline. Dementia participants exhibited slower velocity, shorter stride length, longer double support, reduced hip range and higher stance asymmetry, particularly under RAC. RAC stance asymmetry distinguished SCD from Dementia with high accuracy (AUC = 0.952, sensitivity 93.8%, specificity 90.5%), outperforming dual-task measures. Dual-task base width differentiated SCD from MCI (AUC = 0.772), while music-cued support times distinguished MCI from Dementia (P ≤ .028, η2 ≈ 0.33). Gait parameters correlated strongly with executive function (r ≈ 0.48, P < .001). CONCLUSIONS: Smartphone-based gait assessment, particularly under RAC, provides a sensitive, culturally neutral and scalable method for detecting and classifying cognitive impairment. RAC highlights sensorimotor deficits characteristic of dementia, complementing standard cognitive screening tools in resource-limited settings.
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