Abstract
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.
Highlights
Alzheimer’s disease (AD) is a major neurocognitive disorder defined by a cognitive impairment that may interfere with independence
Another important reason was the use of this technique for pathologies other than AD or mild cognitive impairment (MCI), such as Parkinson or schizophrenia
They focus on other neurodegenerative processes (Boschi et al, 2017), conduct a general analysis of speech elicited by pictures in AD (Mueller et al, 2018; Slegers et al, 2018), or make a comprehensive but unsystematic review (Szatloczki et al, 2015)
Summary
Alzheimer’s disease (AD) is a major neurocognitive disorder defined by a cognitive impairment that may interfere with independence. Despite memory deficit being the earliest and most characteristic symptom, there is a growing interest in language impairments. This is attributable to the fact that language deficits are present as from the early—and even prodromal—stages (Cuetos et al, 2007), and they are a key for early diagnosis. The challenge today is to accurately differentiate between patients with mild cognitive impairment (MCI) and those in the early stage of AD, on the one hand, and people with healthy aging, on the other. 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. A systematic review was conducted to determine these features and their diagnostic accuracy
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