PubMed · 8483377
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D L Beck. 1993. Auditory brainstem response testing.. https://doi.org/10.1288/00005537-199305000-00020
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In the clinical application of auditory brainstem responses (ABRs), the latencies of five to seven main peaks are extremely important parameters for diagnosis. In practice, the latencies have mainly been done by manual measurement so far. In recent years, some new techniques have been developed involving automatic computer recognition. Computer recognition is difficult, however, since some peaks are complicated and vary a lot individually. In this paper, we introduce an artificial neural network method for ABR research. The detection of ABR is performed by using artificial neural networks. A proper bandpass filter is designed for peak extraction. Moreover, a new approach to estimate the latencies of the peaks by artificial neural networks is presented. The neural networks are studied in relation to the selection of model, number of layers and number of neurons in each hidden layer. Experimental results are described showing that artificial neural networks are a promising method in the study of ABR.
The change in the performance of the HVDT as targeted neonatal hearing screening has been introduced has been examined for the Nottingham district. The records for all children born in the period 1984-1993 within the district and having a permanent hearing loss of > or = 50 dB in the better ear have been examined. The referral route leading to ascertainment of the hearing loss as well as the result of any screening tests were noted. The data shows an increase in the number referred prior to the HVDT, mainly as a result of neonatal screen failure. At the same time there has been a reduction in the sensitivity of the HVDT from 78% in the first half of the decade to 38% for the second half. There are also some indications of an increase in the coverage and the failure rate over the time. Possible reasons for these changes are discussed.
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