Do you have COVID-19? An artificial intelligence-based screening tool for COVID-19 using acoustic parameters.
J Acoust Soc Am
; 150(3): 1945, 2021 09.
Article
in English
| MEDLINE | ID: covidwho-1621987
ABSTRACT
This study aimed to develop an artificial intelligence (AI)-based tool for screening COVID-19 patients based on the acoustic parameters of their voices. Twenty-five acoustic parameters were extracted from voice samples of 203 COVID-19 patients and 171 healthy individuals who produced a sustained vowel, i.e., /a/, as long as they could after a deep breath. The selected acoustic parameters were from different categories including fundamental frequency and its perturbation, harmonicity, vocal tract function, airflow sufficiency, and periodicity. After the feature extraction, different machine learning methods were tested. A leave-one-subject-out validation scheme was used to tune the hyper-parameters and record the test set results. Then the models were compared based on their accuracy, precision, recall, and F1-score. Based on accuracy (89.71%), recall (91.63%), and F1-score (90.62%), the best model was the feedforward neural network (FFNN). Its precision function (89.63%) was a bit lower than the logistic regression (90.17%). Based on these results and confusion matrices, the FFNN model was employed in the software. This screening tool could be practically used at home and public places to ensure the health of each individual's respiratory system. If there are any related abnormalities in the test taker's voice, the tool recommends that they seek a medical consultant.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Artificial Intelligence
/
COVID-19
Type of study:
Prognostic study
Limits:
Humans
Language:
English
Journal:
J Acoust Soc Am
Year:
2021
Document Type:
Article
Affiliation country:
10.0006104
Similar
MEDLINE
...
LILACS
LIS