| Autor: |
Moises R. Pacheco-Lorenzo, Heidi Christensen, Luis E. Anido-Rifon, Manuel J. Fernandez-Iglesias, Sonia M. Valladares-Rodriguez |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
IEEE Access, Vol 12, Pp 122840-122851 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2024.3442431 |
| Popis: |
The objective of this work is to determine whether speech obtained from interactions with a smart speaker can be used to predict the level of cognitive impairment (CI). We use a voice assistant to administer a cognitive test in Spanish, and we record the conversations in order to extract features that could potentially be used as voice biomarkers. A total of 21 participants (14 patients and 7 healthy controls) between the ages of 68 and 86 are included in the study (15 were women). Using just speech we are able to perform a regression with machine learning models, in order to predict the Global Deterioration Scale (GDS) of cognitive functions. Then, we measure the performance of the estimations with standard metrics - an $R^{2}$ of 0.74 was obtained in the best case using Support Vector Machine (SVM) algorithms. Despite needing a bigger sample of participants in future studies, this is a positive and promising result for such a non-intrusive procedure, which could potentially be used as a screening tool for automatic cognitive impairment assessment. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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