Easy Screening for Mild Alzheimer's Disease and Mild Cognitive Impairment from Elderly Speech

Kato, Shōhei; Homma, Akira; Sakuma, Tetsuya

doi:10.2174/1567205014666171120144343

Cited by 27 publications

(15 citation statements)

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“…The correlation with disease severity also suggests that assessment of EPR can be used as an additional tool to characterize the disease stage. There are studies using additional aspects of prosody or even complex music stimuli, and it has been recently proposed that speech sound analysis can be used to screen older adults for MCI or AD [ 47 ]. In another study, it was shown that subjects with dementia and aMCI also experience difficulty in recognizing the emotions conveyed by music [ 48 ].…”

Section: Discussionmentioning

confidence: 99%

Emotional prosody recognition is impaired in Alzheimer’s disease

et al. 2022

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Background The ability to understand emotions is often disturbed in patients with cognitive impairments. Right temporal lobe structures play a crucial role in emotional processing, especially the amygdala, temporal pole (TP), superior temporal sulcus (STS), and anterior cingulate (AC). Those regions are affected in early stages of Alzheimer´s disease (AD). The aim of our study was to evaluate emotional prosody recognition (EPR) in participants with amnestic mild cognitive impairment (aMCI) due to AD, AD dementia patients, and cognitively healthy controls and to measure volumes or thickness of the brain structures involved in this process. In addition, we correlated EPR score to cognitive impairment as measured by MMSE. The receiver operating characteristic (ROC) analysis was used to assess the ability of EPR tests to differentiate the control group from the aMCI and dementia groups. Methods Eighty-nine participants from the Czech Brain Aging Study: 43 aMCI due to AD, 36 AD dementia, and 23 controls, underwent Prosody Emotional Recognition Test. This experimental test included the playback of 25 sentences with neutral meaning each recorded with different emotional prosody (happiness, sadness, fear, disgust, anger). Volume of the amygdala and thickness of the TP, STS, and rostral and caudal parts of AC (RAC and CAC) were measured using FreeSurfer algorithm software. ANCOVA was used to evaluate EPR score differences. ROC analysis was used to assess the ability of EPR test to differentiate the control group from the aMCI and dementia groups. The Pearson’s correlation coefficients were calculated to explore relationships between EPR scores, structural brain measures, and MMSE. Results EPR was lower in the dementia and aMCI groups compared with controls. EPR total score had high sensitivity in distinguishing between not only controls and patients, but also controls and aMCI, controls and dementia, and aMCI and dementia. EPR decreased with disease severity as it correlated with MMSE. There was a significant positive correlation of EPR and thickness of the right TP, STS, and bilateral RAC. Conclusions EPR is impaired in AD dementia and aMCI due to AD. These data suggest that the broad range of AD symptoms may include specific deficits in the emotional sphere which further complicate the patient’s quality of life.

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Section: Discussionmentioning

confidence: 99%

Emotional prosody recognition is impaired in Alzheimer’s disease

et al. 2022

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“…Lópezde-Ipiña et al (2018a,b) also used combinations of features with 73-95% accuracy for MCI. By combining prosodic features produced while repeating numbers backwards, Kato et al (2018) classified people with MCI with 76.4% accuracy. Themistocleous et al (2018) focused on formants produced while reading, thus achieving an accuracy value of 83%.…”

Section: Predictive Studies On the Early Diagnosis Of Ad And MCImentioning

confidence: 99%

Ten Years of Research on Automatic Voice and Speech Analysis of People With Alzheimer's Disease and Mild Cognitive Impairment: A Systematic Review Article

et al. 2021

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Background: The field of voice and speech analysis has become increasingly popular over the last 10 years, and articles on its use in detecting neurodegenerative diseases have proliferated. Many studies have identified characteristic speech features that can be used to draw an accurate distinction between healthy aging among older people and those with mild cognitive impairment and Alzheimer's disease. Speech analysis has been singled out as a cost-effective and reliable method for detecting the presence of both conditions. In this research, a systematic review was conducted to determine these features and their diagnostic accuracy.Methods: Peer-reviewed literature was located across multiple databases, involving studies that apply new procedures of automatic speech analysis to collect behavioral evidence of linguistic impairments along with their diagnostic accuracy on Alzheimer's disease and mild cognitive impairment. The risk of bias was assessed by using JBI and QUADAS-2 checklists.Results: Thirty-five papers met the inclusion criteria; of these, 11 were descriptive studies that either identified voice features or explored their cognitive correlates, and the rest were diagnostic studies. Overall, the studies were of good quality and presented solid evidence of the usefulness of this technique. The distinctive acoustic and rhythmic features found are gathered. Most studies record a diagnostic accuracy over 88% for Alzheimer's and 80% for mild cognitive impairment.Conclusion: Automatic speech analysis is a promising tool for diagnosing mild cognitive impairment and Alzheimer's disease. The reported features seem to be indicators of the cognitive changes in older people. The specific features and the cognitive changes involved could be the subject of further research.

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“…While further research is advocated on a larger scale, the results support future plans for a predictive model to enable an earlier diagnosis of AD. A study in Japan (48) distinguished between cognitive normal individuals and elderly people with cognitive impairment using prosodic signals extracted from speech; even though the study was applicable to older adults in Japan, a similar study is advocated in the UK, which incorporates all signs and symptoms in both the early and late onset AD, for the development of the predictive model for early detection of the disease. Another systematic review (49) that identified the functional alterations in the retina as an early biomarker for late-stage AD could to support the predictive model and could discriminate individuals at different stages of the disease.…”

Section: Resultsmentioning

confidence: 99%