Feasibility of efficient smartphone-based threshold and loudness assessments in typical home settings

Abstract

Ambient noise is a critical factor affecting the precision of mobile hearing tests conducted in home environments. Monitoring noise levels during out-of-booth measurements provides essential information about the suitability of the setting for accurate audiometric testing. When ambient noise is controlled, results are expected to be comparable to in-booth measurements. This study remotely conducted air-conduction pure-tone audiometry and adaptive categorical loudness scaling (ACALOS) tests at 0.25, 1, and 4 kHz using a smartphone, while an integrated microphone and a dosimeter app were used to quantify ambient noise levels. Additionally, a reinforced ACALOS (rACALOS) method was proposed to integrate threshold measurement into the ACALOS procedure. The rACALOS method not only improves the accuracy of threshold estimation but also increases efficiency by combining two independent procedures into a single, streamlined process. As a result, ambient noise levels were mostly below the maximum permissible level. Hearing tests conducted via smartphone demonstrated moderate-to-excellent reliability, with intraclass correlation coefficients (ICCs) exceeding 0.75, and strong validity, with biases of less than 1 dB. In simulations, the rACALOS method reduced the bias towards pre-assumed thresholds, and in behavioral experiments, it showed a stronger correlation with pure-tone audiometric thresholds than the baseline method. Overall, this study demonstrates that administering pure-tone audiometry and ACALOS tests at home is feasible, valid, efficient, and reliable when ambient noise is sufficiently low.