# Pitfalls in the Detection of Hearing Loss via Otoacoustic Emissions
## 1 Introduction  
Otoacoustic emissions (OAEs) are low-level sounds generated in the cochlea [1]. Their most common application is in the area of universal newborn hearing screening (UNHS) programs [2, 3]. Additionally, OAEs can be used in the diagnosis of various cochlear pathologies across all age groups [4]. The main advantages of the OAE acquisition procedures are that they require short measurement times and, since they are noninvasive, they do not require highly specialized clinical personnel [5]. The present study focuses on transiently evoked OAEs (TEOAEs), which are evoked by a click or a chirp [6, 7, 8]. In general, commercial OAE equipment can be divided into two classes: clinical systems and screening devices. Clinical systems offer numerous methods of OAE stimulation, OAE measurement (transient, spontaneous, and distortion product OAEs), and OAE signal analysis. Clinical systems can be used for hearing screening, but the greater size of the equipment and their higher price can be considered a disadvantage. Screening devices are small and handheld and, in most cases, provide limited information of the OAE response, i.e., a \"pass\" or a \"refer\" screening outcome. It is important to note that the objectivesof hearing screening are very different from those related to the clinical assessment of a patient, and this is why screening and clinical OAE protocols differ. In a hearing screening context, a high-quality OAE response is not so important as a quick reading that indicates whether an OAE signal is present or not. For this reason, screening protocols use shorter recording windows (usually 10 ms, compared to the 20 ms used in a standard clinical system), which result in shorter acquisition times and therefore faster responses. TEOAEs are very weak signals, and so in order to get a valid response, a large number of averages is needed (usually 1024). Shorter acquisition windows result in the acquisition of more responses in the same time, i.e., around 30 s. Additionally, different manufacturers use different signal processing techniques in order to achieve reliable OAE responses in the least possible time. Although screening OAE devices were initially developed for UNHS programs, they are also used to assess the hearing status of children and adults [9]. Recently, significant progress has been made in OAE measurement protocols and analysis methods [10; 11] as well as in OAE hardware and calibration [12; 13]. Unfortunately, these improvements have not been widely adopted in the clinic or in the available clinical equipment. It can be assumed that OAE manufacturers consider the achieved OAE performance as very good and not needing any further improvement. Despite the fact that a large volume of OAE data has been collected since the early 1990s, there have been relatively few reports presenting information on performance issues between different OAE systems or on methods of analysis, even though new methods of analysis have been developed and there is more knowledge about OAEs than when OAE-based UNHS was first recommended in the early 1990s [14]. Clinically used OAE measurement and detection procedures have remained more or less the same. The data in the literature suggest that OAE hearing screening does seem to work adequately, but if one considers the advances in electronics and signal processing over the last 15 years, there still seems to be considerable room for improvement in terms of OAE hardware, OAE protocols, and especially in the area of OAE screening criteria for infants, children, and adults. The stimulus for the present study stemmed from personal clinical observations related to a long series of unexplained and erroneous results of the OAE hearing screening system that we happened to be using, i.e., the Madsen Accuscreen. We observed that young subjects (neonates, toddlers) with apparently normal hearing sometimes received a \"refer\" assessment, while subjects presenting a moderate sensorineural hearing impairment were assessed as \"pass\" cases.