Morphologic clustering of earcanals using deep learning algorithm to design artificial ears dedicated to earplug attenuation measurement

Reliability of an extended version of the 3m™ Eargage tool to assess earcanal size and assist earplug selection

OBJECTIVE

Evaluate the ability of an extended version of the 3 MTM Eargage to estimate the earcanal size and assess the likelihood that a particular earplug can fit an individual's earcanal, ultimately serving as a tool for selecting earplugs in the field.

DESIGN

Earcanal morphology, assessed through earcanal earmolds scans, is compared to earcanal size assessed with the extended eargage (EE) via box plots and Pearson linear correlations coefficients. Relations between attenuation measured on participants (for 6 different earplugs) and their earcanal size assessed with the EE are established via comparison tests.

STUDY SAMPLE

121 participants exposed to occupational noise (103 men, 18 women, mean age 47 years).

RESULTS

The earcanal size assessed with the EE allows for estimating the area of the earcanal's first bend cross-section (correlation coefficient   r = 0.533, p < 0.001). Extremely large earcanals (12.7% of earcanals in our sample) lead to significantly lower earplug attenuation (potentially inadequate) than smaller earcanals.

CONCLUSIONS

The EE is a simple and inexpensive tool easily deployable in the field to assist earplugs selection. When extended with sizes larger than the maximum size of the commercial tool, it allows for detecting individuals with extremely large earcanals who are most likely to be under-protected.

Morphological analysis of the human earcanal deformations during face-related activities

Ear-related technologies are spreading in our daily life and have become essential in several applications. The comfort, retention and battery life of in-ear devices can be substantially improved by considering the dynamic behavior of the earcanal. A better understanding of the earcanal dynamic motion would not only result in the improved fit and performance of earpieces but could also pave the way to harvest energy from these movements to power future ear-related technologies. The contours of the left and right ears of 18 healthy subjects during closed mouth and 4 activities (mouth opening, turning head left, raising eyebrows and smiling) were discretized. Eight parameters were analyzed to investigate the possible relation between each of these face-related activities and the radial and axial deformations of the earcanal. The largest significant deformations in reference to the closed-mouth geometry were observed during mouth-opening and smiling at the earcanal entrance and between the two bends.