Research

Data-driven hearing care with time-stamped data-logging

Abstract

Modern hearing aids holds significant personalization potentials while the processes associated with the administration do not fully accommodate the dialogue for finding the optimized and personalized settings. The hearing aids presented here use a connected smartphone to log a snapshot of 21 sound environment parameters every minute, e.g., sound pressure level in low, mid, and high frequencies and broadband, the estimate of the signal-to-noise ratio in the same 4 bands, the sound environment detector, etc. This data stream shows the sound environments that the user of the hearing aids experiences. The continuous stream of sound environment data is supplemented by the user’s operation of the hearing aid, e.g., which program is chosen when, and how is the volume control adjusted as well. Whenever the user changes program or volume, the change is logged with the time stamp. Together, the continuous and event based data logging reveals in which situations the user prefers a given program and on the bigger time-scale, which program that should be the default program. The close integration of the hearing aid, the mobile phone, and cloud services turning the hearing aid into an Internet of Things device not only enable the learning and adaptation but also supplementing the dialogue between user and audiologist with objective data about the actual use of the hearing aids.

Info

Conference Paper, 2018

UN SDG Classification
DK Main Research Area

    Science/Technology

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