@misc{10481/88705,
year = {2020},
url = {https://hdl.handle.net/10481/88705},
abstract = {Background and aim: Recent research has shown that acoustic voice analysis is a valuable tool for both the objective assessment of cognitive impairment and the monitoring of disease progression. The aim of this study is to determine whether automatic voice analysis is also useful for diagnosis of cognitive impairment.
Materials and methods: This is a descriptive cross-sectional correlational study in which a comparison is made between an experimental group composed of 10 participants with cognitive impairment and a control group with 10 healthy participants. Voice recordings were collected from both groups while they performed 4 tasks: counting backwards (from 305 to 285), description of an image and two tasks of verbal fluency (phonological and semantic). The voice samples were later acoustically analyzed to extract from them variables predictive of the cognitive state of the subject.
Results: The results show that the acoustic variables are effective for early detection of cognitive impairment, achieving a classification rate of 100% when predicting the cognitive status of the subjects in our sample. From the results it is clear that verbal fluency tasks are more effective than counting backwards and describing an image.
Conclusions: In light of our results, we consider that automatic voice analysis could be an additional objective assessment tool for elderly people with cognitive impairment. The implications of the results found are discussed.},
keywords = {Evaluación del deterioro cognitivo},
keywords = {Análisis acústico de la voz},
keywords = {Demencia},
keywords = {Aprendizaje automático},
title = {Análisis Acústico de la Voz para la Detección del Deterioro Cognitivo},
doi = {DOI: 10.1016/j.rlfa.2019.11.003},
author = {Hernández, Lixania and Calet Ruiz, Nuria and González López, José Andrés},
}