Oral function as an indexing parameter for mild cognitive impairment in older adults

Watanabe, Yutaka; Arai, Hidenori; Hirano, Hirohiko; Morishita, Shiho; Ohara, Yuki; Edahiro, Ayako; Murakami, Masaharu; Shimada, Hiroyuki; Kikutani, Takeshi; Suzuki, Takao

doi:10.1111/ggi.13259

Cited by 48 publications

(40 citation statements)

References 30 publications

(63 reference statements)

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“…We believe that compared with spontaneous speech tasks used in other studies [ 6 , 36 ], both these tasks tapped the speaker’s ability to rapidly change between different places of articulation, thus having a high speech planning load. This result aligns with many previous studies on temporal changes in the speech of individuals with cognitive impairment [ 11 , 12 , 25 ]. It is possible that the lower speech tempo and more hesitation time in utterances is a consequence of low language processing speed and disordered speech planning abilities.…”

Section: Discussionsupporting

confidence: 92%

“…Diadochokinesis is a task that has been widely used for checking speech planning abilities. Previous studies have suggested its potential to detect individuals with MCI from HCs [ 11 , 12 ]. In this task, we extracted the same features used in the tongue twister task.…”

Section: Methodsmentioning

confidence: 99%

“…As speech production requires coordinated movements of articulatory organs, impaired speech planning has a potential influence on articulation speed. It has been well documented that individuals with MCI and AD displayed markedly reduced articulatory agility during an articulatory oral motor task, in which the participants were asked to produce sequential speech as fast as possible [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

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Automatic Detection of Cognitive Impairments through Acoustic Analysis of Speech

Nagumo

Ya-ming

Ogawa

et al. 2020

CAR

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Background: Early detection of mild cognitive impairment is crucial in the prevention of Alzheimer’s disease. The aim of the present study was to identify whether acoustic features can help differentiate older, independent community-dwelling individuals with cognitive impairment from healthy controls. Methods: A total of 8779 participants (mean age 74.2 ± 5.7 in the range of 65-96, 3907 males and 4872 females) with different cognitive profiles, namely healthy controls, mild cognitive impairment, global cognitive impairment (defined as a Mini Mental State Examination score of 20-23), and mild cognitive impairment with global cognitive impairment (a combined status of mild cognitive impairment and global cognitive impairment), were evaluated in short-sentence reading tasks, and their acoustic features, including temporal features (such as duration of utterance, number and length of pauses) and spectral features (F0, F1, and F2), were used to build a machine learning model to predict their cognitive impairments. Results: The classification metrics from the healthy controls were evaluated through the area under the receiver operating characteristic curve and were found to be 0.61, 0.67, and 0.77 for mild cognitive impairment, global cognitive impairment, and mild cognitive impairment with global cognitive impairment, respectively. Conclusion: Our machine learning model revealed that individuals’ acoustic features can be employed to discriminate between healthy controls and those with mild cognitive impairment with global cognitive impairment, which is a more severe form of cognitive impairment compared with mild cognitive impairment or global cognitive impairment alone. It is suggested that language impairment increases in severity with cognitive impairment.

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Section: Discussionsupporting

confidence: 92%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Automatic Detection of Cognitive Impairments through Acoustic Analysis of Speech

Nagumo

Ya-ming

Ogawa

et al. 2020

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“…The risk of death is also significantly increased in those with oral frailty (Iwasaki et al., 2018). It has been reported that oral motor skills, such as lip movement, are impaired in patients with cognitive impairment (Watanabe et al., 2018). These lines of evidence suggest that a reduced oral function is an important factor for physical frailty and is associated with cognitive impairment (See Figure 2).…”

Section: Tooth Loss and Frailty/sarcopeniamentioning

confidence: 99%

Oral dysfunctions and cognitive impairment/dementia

Nakamura

Zou

Shibuya

et al. 2020

J of Neuroscience Research

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The number of people with dementia is increasing worldwide and is projected to double every 20 years to 74.7 million by 2030 and 131.5 million by 2050. As of 2001, globally, the number of people with dementia aged 60 years or older was estimated to be 24.3 million, and the prevalence of dementia was 3.9%; therefore, approximately 4.6 million new-onset dementia patients will be diagnosed annually (Ferri et al., 2005). Compared with the 2009 report, the prevalence is increasing in Asia and Africa, especially in low-and middle-income countries. However, the prevalence has declined in Europe and North America. Various studies have been conducted on the development of treatments for Alzheimer's disease (AD), but at present, no effective countermeasures are available. With the increasing number of dementia patients, attention has focused on mild cognitive impairment (MCI), a predementia stage. MCI is a concept proposed by Petersen et al. in 1995, and it is defined as a condition in which cognitive function is lower than expected owing to physiological aging changes, but is not dementia. In MCI, the ability to carry out daily activities

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“…The characteristics of the participants of the present study, which included MMSE scores, the prevalence of cognitive impairment, educational history, maximum walking speed and Tokyo Metropolitan Institute of Gerontology Index of Competence, were similar to other large-scale cohort studies carried out in Japan. [18][19][20] Therefore, the samples in this study were regarded as representative of community-dwelling older individuals in Japan.…”

Section: Discussionmentioning

confidence: 99%

Development and validity of the Computer‐Based Cognitive Assessment Tool for intervention in community‐dwelling older individuals

Takahashi

Kawai

Suzuki

et al. 2020

Geriatrics Gerontology Int

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Aim The Mini‐Mental State Examination is a widely used cognitive assessment tool. However, it has several limitations, including the learning effect and interrater reliability. Therefore, we developed a Computer‐Based Cognitive Assessment Tool (CompBased‐CAT), which runs on a tablet or personal computer. In this study, we examined the validity and discrimination ability of the CompBased‐CAT. Methods Participants were recruited from the Otasha‐Kenshin study carried out in 2016. We included 773 community‐dwelling older individuals in Japan (332 men, 441 women, aged 65–97 years). CompBased‐CAT scores were converted to z‐scores, and the correlation with Mini‐Mental State Examination scores was examined using Pearson's correlation coefficient. Furthermore, the ability to discern cognitive impairment was examined using the receiver operating characteristic curve. Results The Pearson's correlation coefficient for the Mini‐Mental State Examination scores and each task component of the CompBased‐CAT ranged from 0.24 to 0.41 (P < 0.001), and the correlation coefficient of the total z‐scores was 0.51 (P < 0.001). The sensitivity, specificity and area under the receiver operating characteristic curve of the discriminating ability of the CompBased‐CATool for cognitive impairment were 0.81, 0.77 and 0.85, respectively. Conclusions The CompBased‐CAT certainly possesses validity, discriminating ability and utility as a new cognitive assessment tool in community‐dwelling older individuals. Geriatr Gerontol Int 2020; ••: ••–••.

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Oral function as an indexing parameter for mild cognitive impairment in older adults

Abstract: Oral motor skill, such as lip movement, might be impaired in patients with MCI. Detecting decreasing oral motor dexterity supports the early detection of MCI, and might be key to improve the prognosis of dementia. Geriatr Gerontol Int 2018; 18: 790-798.

Cited by 48 publications

References 30 publications

Automatic Detection of Cognitive Impairments through Acoustic Analysis of Speech

Automatic Detection of Cognitive Impairments through Acoustic Analysis of Speech

Oral dysfunctions and cognitive impairment/dementia

Development and validity of the Computer‐Based Cognitive Assessment Tool for intervention in community‐dwelling older individuals

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