Automated auditory response detection: Improvement of the statistical test strategy

Abstract

Objective: Automated auditory response detection is always performed by applying an appropriate statistical test to a sample of stimulus-related epochs of the raw EEG. The often-used sequential test strategy saves time, but the multiple testing increases the probability of falsely detected responses. Therefore, the critical test value must guarantee the specified error probability for the maximum test step number. However, response detection at all lower test step numbers is disadvantaged. We propose calculating the critical test values for each test step number, which correspond exactly to the given error probability. Design: The critical test values for each test step were calculated by the method described by . A table with the test values was implemented with customized software of the Eclipse ASSR system^® (Interacoustics, Denmark). Study sample: Table-related testing was performed on a sample of raw EEG data collected during the routine clinical measurement of frequency-specific auditory steady-state responses (ASSR) for hearing threshold assessment. Results: The new test strategy leads to a significantly increased detection rate and a significantly shorter detection time. Conclusions: The new test strategy can improve the performance of the objective hearing threshold assessment and of the newborn hearing screening.

Key Words::

• ABR
• automated auditory response detection
• repeated testing
• error probability
• critical test value

Acknowledgements

The authors thank Christiane Walk and Ralph Keim for assisting with the data collection, Department of Audiology, University Clinic Würzburg.

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.