Systems and methods for training a machine learning model for use by a processing unit in a cochlear implant system

Inventors: Daniel J. Alfsmann (Valencia, CA); Raphael S. Koning (Wedemark, DE); Joachim Thiemann (Hannover, DE)

Assignee: Advanced Bionics AG

A61N1/36039 G06N3/08 G16H40/63

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Quick Facts

Patent No.: US 12667725
App. No.: 17/620,040
Granted: Jun 30, 2026
Kind: B2

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Abstract

An exemplary system is configured to maintain data representative a machine learning model for use in a cochlear implant system and train the machine learning model. The training may include applying audio content as a training input to the machine learning model, the machine learning model configured to apply a machine learning heuristic to the audio content to output an electrical signal representative of the audio content; applying the electrical signal to a brain processing model, the brain processing model configured to output synthesized audio content representative of the electrical signal; generating an error metric representative of a difference between the audio content and the synthesized audio content; and feeding back the error metric into the machine learning model, the machine learning model configured to use the error metric to adjust the machine learning heuristic applied to the audio content.

Claims (25)

1 . A system comprising:

a computing device configured to:

maintain data representative a machine learning model for use in a cochlear implant system; and

train the machine learning model by

applying audio content as a training input to the machine learning model, the machine learning model configured to apply a machine learning heuristic to the audio content to output an electrical signal representative of the audio content, the electrical signal comprising one or more electrical stimulation pulses configured to represent the audio content;

applying the electrical signal to a brain processing model, the brain processing model configured to output synthesized audio content representative of the electrical signal;

generating an error metric representative of a difference between the audio content and the synthesized audio content; and

feeding back the error metric into the machine learning model, the machine learning model configured to use the error metric to adjust the machine learning heuristic applied to the audio content;

a sound processor remote from the computing device; and

a cochlear implant configured to be implanted within a recipient and communicatively coupled to the sound processor by way of a wireless communication link;

wherein the sound processor is configured to:

receive an audio signal,

use the machine learning model to perform at least one processing stage with respect to the audio signal to generate one or more stimulation parameters, and

transmit the one or more stimulation parameters to the cochlear implant by way of the wireless communication link; and

wherein the cochlear implant is configured to:

receive the one or more stimulation parameters by way of the wireless communication link, and

apply, based on the one or more stimulation parameters, electrical stimulation representative of the audio signal to the recipient.

2 . The system of claim 1 , wherein the training continues until the error metric is below a predetermined threshold.

3 . The system of claim 1 , wherein the processor is further configured to pre-process the audio content before the audio content is applied as the training input to the machine learning model.

4 . The system of claim 1 , wherein the machine learning model is implemented by a multi-layer neural network.

5 . The system of claim 1 , wherein the brain processing model is implemented by a vocoder.

6 . The system of claim 1 , wherein the training of the machine learning model further comprises limiting an amount of charge of the electrical signal before the electrical signal is applied to the brain processing model.

7 . The system of claim 1 , wherein the computing device is further configured to transmit the data representative of the machine learning model to the sound processor.

8 . The system of claim 7 , wherein the transmitting comprises transmitting the data representative of the machine learning model to the sound processor by way of a network that interconnects the system and the sound processor.

9 . The system of claim 7 , wherein the transmitting comprises transmitting the data representative of the machine learning model to a computing device configured to load the data representative of the machine learning model onto the sound processor.