Detecting Lower MMSE Scores in Older Adults Using Cross-Trial Features From a Dual-Task With Gait and Arithmetic

The Mini-Mental State Examination (MMSE) is widely used in clinics to screen for low cognitive status. However, it is limited in that it requires examiners to be present; and has fixed questions that constrain its repeated use. Thus, the MMSE cannot be used as a daily assessment to facilitate early...

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Autores principales: Shuqiong Wu, Taku Matsuura, Fumio Okura, Yasushi Makihara, Chengju Zhou, Kota Aoki, Ikuhisa Mitsugami, Yasushi Yagi
Formato: article
Lenguaje:EN
Publicado: IEEE 2021
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MCI
Acceso en línea:https://doaj.org/article/1368ba115414449d8dac4c3797d24c69
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Sumario:The Mini-Mental State Examination (MMSE) is widely used in clinics to screen for low cognitive status. However, it is limited in that it requires examiners to be present; and has fixed questions that constrain its repeated use. Thus, the MMSE cannot be used as a daily assessment to facilitate early detection of cognitive impairment. To address this issue, we developed an automated system to detect older adults with lower MMSE scores by analyzing performance during a dual task involving stepping and calculation, which can be used repeatedly because its questions were randomly created. Leveraging this advantage, this paper proposes a learning-based method to detect subjects with lower MMSE scores using multiple trials with the dual-task system. We investigated various patterns for effectively combining the features acquired during multiple continuous trials, and analyzed the sensitivity of the number <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> of trials on detection performance to find the optimal <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> via experiments. We compared our approach with previous methods and demonstrated the superiority of our strategy. Using the cross-trial feature, our approach achieved an overall performance (sensitivity &#x002B; specificity) as high as 1.79 for detecting older adults whose MMSE score is equal to or less than 23 (indicate a relatively high probability of dementia), and 1.75 for detecting older adults whose MMSE score is equal to or less than 27 (indicative of a relatively high probability of mild cognitive impairment (MCI)).