Desenvolvimento de um sistema de análise de Emissões Otoacústicas Evocadas Transientes para auxílio à triagem auditiva

• Autor(a) principal: Pinto, Kayo Luann Nogueira
• Data de Publicação: 2016
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Digital da Universidade Federal Rural do Semi-Árido (RDU)
• Texto Completo: https://repositorio.ufersa.edu.br/handle/tede/665
• topic: TEOAE; Otoleitor; M-Health; Telemedicina; Sinais otoacústicos; TEOAE; Otoleitor; M-Health; Telemedicine; Otoacustic signals; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO

Telemedicine has enabled a closer relationship between the health professional and the patient, the use of smartphones as a tool for data exchange has allowed monitoring the distance of both the patient’s situation daily, as performing medical procedures. A problem that requires great attention and that telemedicine can be applied as a possible solution is the pre-diagnosis of hearing loss. When not diagnosed in time, in neonates, it can cause a number of complications, such as behavioral maladjustment, oral and written language disorders, poor school performance of the newborn, among others. But if previously diagnosed and treated, the child may also develop itself like a non-defective, such diagnosis can be given through the Otoacoustic Emissions test. Considering the importance of the audiological analysis, the Brazilian Congress approved Law No. 12.303, of August 2, 2010, which made mandatory the completion of the Otoacoustic Emissions test across the primary care network in the country. However the equipment responsible for performing the test has a high cost, leading to non-realization of most of the population, in its great majority poor, because the few devices distributed in the hospital network of public health. Observing this need, this paper makes use of a smartphone connected to a prototyping board Arduino Mega ADK to develop a tool that helps the realization of the Transient Evoked Otoacoustic Emissions (TEOAE) test in neonates. Using Arduino board to generate the signal and the smartphone to perform recording through a probe positioned in the patient’s ear were performed 3 noise floor recordings, 5 stimulus signal recording and 7 recordings tests in the patient’s ear. The recordings occurred continuously, starting and ending simultaneously with the stimulus. Subsequently held a spectral analysis via Matlab seeking to identify the existence of TEOAE, despite the identification of ear responses in the recordings, we still can not confirm that such responses are really TEOAE