Examining the Profile of Noise-Induced Cochlear Synaptopathy Using iPhone Health App Data and Cochlear and Brainstem Electrophysiological Responses to Fast Clicks Rates

Abstract

Little is known about objective classifying of noise exposure risk levels in personal listening device (PLD) users and electrophysiologic evidence of cochlear synaptopathy at very fast click rates. The aim of the study was to objectively classify noise exposure risk using iPhone Health app and identify signs of cochlear synaptopathy using behavioral and electrophysiologic measures. Thirty normal-hearing females (aged 18–26 years) were grouped based on their iPhone Health app's 6-month listening level and noise exposure data into low-risk and high-risk groups. They were assessed using a questionnaire, extended high-frequency (EHF) audiometry, QuickSIN test, distortion-product otoacoustic emission (DPOAE), and simultaneous recording of electrocochleography (ECochG) and auditory brainstem response (ABR) at three click rates (19.5/s, 97.7/s, 234.4/s). A series of ANOVAs and independent samples t-test were conducted for group comparison. Both groups had within-normal EHF hearing thresholds and DPOAEs. However, the high-risk participants were over twice as likely to suffer from tinnitus, had abnormally large summating potential to action potential amplitude and area ratios at fast rates, and had slightly smaller waves I and V amplitudes. The high-risk group demonstrated a profile of behavioral and objective signs of cochlear synaptopathy based on ECochG and ABR recordings at fast click rates. The findings in this study suggest that the iPhone Health app may be a useful tool for further investigation into cochlear synaptopathy in PLD users.