BACKGROUND: Speech variations enable us to map the performance of cognitive processes of syntactic, semantic, phonological, and articulatory planning and execution. Speaking is one of the first functions to be affected by neurodegenerative complaints such as Alzheimer's disease (AD), which makes the speech a highly promising biomarker for detecting the illness before the first preclinical symptoms appear.

OBJECTIVE: This paper has sought to develop and validate a technological prototype that adopts an automated approach to speech analysis among older people.

METHODS: It uses a mathematical algorithm based on certain discriminatory variables to estimate the probability of developing AD.

RESULTS AND CONCLUSION: This device may be used at a preclinical stage by non-expert health professionals to determine the likelihood of the onset of AD.