ABSTRACT
Objective: The virus called SARS-CoV-2, which is known as the first epidemic of the twenty-first century, is known to affect the central and peripheral nervous system. In the literature, complaints of sudden hearing loss, tinnitus, and vertigo have been reported in the patients. The aim of this study is to objectively reveal the effect of the coronavirus disease 2019 on the efferent auditory system. Methods: Twenty-three participants, who had the coronavirus disease 2019, were included in the study group, while 20 healthy participants were included in the control group. The test of transient otoacoustic emissions with contralateral suppression was applied to individuals who had normal audiological and immitansmetric evaluations findings. Results: In audiological evaluation, a significant difference was observed between the groups in the 125–500 Hz low frequency range and 4 kHz–12.5 kHz high frequency range. In the test of TEOAE and TEOAE with contralateral suppression, a significant difference was observed between the groups at 4 kHz. Conclusion: The effect of the coronavirus disease 2019 on the peripheral hearing system has been shown. Its effect on the efferent hearing system in the high frequency region has been revealed. © 2022, The Author(s).
ABSTRACT
The usage of mask is necessary for the prevention and control of COVID-19 which is a respiratory disease that passes from person to person by contact and droplets from the respiratory tract. It is an important task to identify people who do not wear face mask in the community. In this study, performance comparison of the automated deep learning based models including the ones that use transfer learning for face mask detection on images was performed. Before training deep models, faces were detected within images using multi-task cascaded convolutional network (MTCNN). Images obtained from face mask detection dataset, COVID face mask detection dataset, mask detection dataset, and with/without mask dataset were used for training and testing the models. Face areas that are detected with MTCNN were used as input for convolutional neural network (CNN), MobileNetV2, VGG16 and ResNet50. VGG16 showed best performance with 97.82% accuracy. MobileNetV2 showed the worst performance for detecting faces without mask with 72.44% accuracy. Comparison results show that VGG16 can be used effectively to detect faces without mask. This system can be used in crowded public areas to warn people without mask that may help the reduce the risk of pandemic.
ABSTRACT
OBJECTIVE: This study aimed to evaluate different auditory regions with audiological tests, based on the presumption that there may be damage to the structures in the hearing system after coronavirus disease 2019. METHODS: Twenty individuals with no history of coronavirus disease 2019 and 27 individuals diagnosed with coronavirus disease 2019 were compared. Pure tone, speech and extended high-frequency audiometry, acoustic immitansmetry, transient evoked and distortion product otoacoustic emissions testing, and auditory brainstem response testing were conducted. RESULTS: The pure tone audiometry and extended high-frequency mean threshold values were higher in the coronavirus disease 2019 group. The transient evoked otoacoustic emissions signal-to-noise ratios were bilaterally lower at 4 kHz in individuals with a coronavirus disease 2019 history. In the auditory brainstem response test, only the interpeak latencies of waves III-V were significantly different between groups. CONCLUSION: Coronavirus disease 2019 may cause damage to the hearing system. Patients should be followed up in the long term with advanced audiological evaluation methods in order to determine the extent and level of damage.