3D printing and machine learning team up to improve cochlear implants

3D printing and machine learning team up to improve cochlear implants

Cochlear implants have transformed the lives of hundreds of thousands of people with severe or profound hearing loss. However, the effectiveness of the surgically implanted medical device has been hampered by "current propagation", a phenomenon caused by the high electrical conductivity of the fluids within the cochlear ducts.

Something that could be corrected thanks to the combined effort of two thriving technologies: 3D printing and machine learning algorithms.

Avoiding "fuzzy" hearing

The size and shape of a human cochlea is unique to each individual and varies from person to person. Together with its complicated location and complex anatomy, this makes it one of the most difficult tissues to study, and therefore analysis of the current problem of "current spread" has not been easily possible .

For this reason, a team of engineers and physicians has used 3D printing to create detailed replicas of human cochlea (the hollow, spiral-shaped bone of the inner ear) and combined them with machine learning to advance clinical predictions of " current spread "within the ear in patients with cochlear implants .

"Current spread" or electrical stimulus spread, as it is also known, affects IC performance and leads to "fuzzy" hearing for users, but until now there were no suitable test models to replicate the problem. in human cochlea.