Of ten, individuals with hearing loss have difficulties understanding speech in noisy environments. Aim: It was the aim of this study to assess the performance of adult individuals with sensorineural hearing loss, associated with speech perception using digital hearing aids with a sound reduction algorithm called Speech Sensitive Processing, on and off, in the presence of noise. Materials and Methods: This case study was performed with 32 individuals with sensorineural hearing loss of mild, moderate or mild to moderate level. Our evaluation involved a speech perception test, where we investigated the recognition of sentences in noise, in order to get a signal/noise ratio, with a digital hearing aid. Result Description: The algorithm provided a benefit for most hearing impaired individuals, in the investigation of signal/noise ratio and the results pointed to a statistically significant difference when the algorithm was on, compared to when the algorithm was off. Conclusion: The use of a sound reduction algorithm must be considered as a clinical alternative -since we observed an efficacy in noise reduction and heightened speech perception.

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The development of new low-cost transducers and systems has been extensively aimed at in both industry and academia to promote a correct failure diagnosis in aerospace, naval, and civil structures. In this context, structural health monitoring (SHM) engineering is focused on promoting human safety and a reduction in the maintenance costs of these components. Traditionally, SHM aims to detect structural damages at the initial stage, before it reaches a critical level of severity. Numerous approaches for damage identification and location have been proposed in the literature. One of the most common damage location techniques is based on acoustic waves triangulation, which stands out as an effective approach. This method uses a piezoelectric transducer as a sensor to capture acoustic waves emitted by cracks or other damage. Basically, the damage location is defined by calculating the difference in the time of arrival (TOA) of the signals. Although it may be simple, the detection of TOA requires complex statistical and signal processing techniques. Based on this issue, this work proposes the evaluation of a low-cost piezoelectric transducer to determine damage location in metallic structures by comparing two methodologies of TOA identification, the Hinkley criterion and the statistical Akaike criterion. The tests were conducted on an aluminum beam in which two piezoelectric transducers were attached at each end. The damage was simulated by pencil lead break (PLB) test applied at four different points of the specimen and the acoustic signals emitted by the damage were acquired and processed by Hinkley and Akaike criteria. The results indicate that, although both signal processing methodologies were able to determine the damage location, Akaike presented higher precision when compared to Hinkley approach. Moreover, the experimental results indicated that the low-cost piezoelectric sensors have a great potential to be applied in the location of structural failures.

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