Adaptive cancellation system for implantable hearing instruments

• US 8,096,937 B2
• Filed: 11/30/2006
• Issued: 01/17/2012
• Est. Priority Date: 01/11/2005
• Status: Active Grant

• Current Assignee: Otologics, LLC
• Original Assignee: Otologics, LLC
• Inventors: Miller, Scott Allan III
• Primary Examiner(s): Marmor, II, Charles A
• Assistant Examiner(s): MATTHEWS, CHRISTINE HOPKINS
• Application Number:
  US11/565,014
• Publication Number:
  US 20080132750A1
• Time in Patent Office: 1,874 Days
• Field of Search: 600/25, 607 55- 57, 381/94, 381/71, 381/83, 381/93, 381/60, 381/23.1
• US Class Current: 600/25
• CPC Class Codes: H04R 25/453 electronically
• CPC Class Codes: H04R 25/606 acting directly on the eardrum, the ossicles or the skull, e.g. mastoid, tooth, maxillary or mandibular bone, or mechanically stimulating the cochlea, e.g. at the oval window

Abstract

The invention is directed to an implanted microphone having reduced sensitivity to vibration. In this regard, the microphone differentiates between the desirable and undesirable vibration by utilizing at least one motion sensor to produce a motion signal when an implanted microphone is in motion. This motion signal is used to yield a microphone output signal that is less vibration sensitive. In a first arrangement, the motion signal may be processed with an output of the implantable microphone transducer to provide an audio signal that is less vibration-sensitive than the microphone output alone. Specifically, the motion signal may be scaled to match the motion component of the microphone output such that upon removal of the motion signal from the microphone output, the remaining signal is an acoustic signal.

Claims

1. A method for use with an implantable hearing instrument, comprising:

generating a first system model of a first relationship of output signals of an implantable microphone and a motion sensor in response to a first operating environment;

generating a second system model of a second relationship of output signals of said implantable microphone and said motion sensor in response to a second operating environment, wherein said first and second operating environments are different; and

using said first and second system models, generating a variable system model of relationships of output signals of said implantable microphone and said motion sensor, wherein said variable system model is at least partially dependent upon a variable operating environment of said hearing instrument.

2. The method of claim 1, wherein said variable operating environment comprises a latent parameter associated with said variable operating environment.

3. The method of claim 2, further comprising:

interactively identifying a value associated with said latent parameter.

4. The method of claim 1, further comprising:

identifying a value associated with said variable operating environment; and

based on said value, utilizing said variable system model to alter at least a first characteristic of subsequent output signals of said motion sensor and generate altered output signals.

5. The method of claim 4, further comprising:

combining said altered output signals with corresponding output signals of said implantable microphone.

6. The method of claim 5, wherein combining comprises subtracting said altered output signals from said corresponding output signals of said implantable microphone.

7. The method of claim 1, wherein generating said first and second system models comprises generating first and second mathematical functions approximating said first and second relationships, respectively.

8. The method of claim 7, wherein generating said variable system model comprises:

identifying two or more parameters associated with each of said first and second mathematical functions that vary based on said first and second operating environments; and

reducing a dimensionality of said parameters to define a range of variance associated with said first and second operating environments.

9. The method of claim 8, further comprising:

identifying dependency relationships between corresponding parameters of said functions and said range of variance; and

utilizing said dependency relationships to generate filter coefficients for said variable system model, wherein each said filter coefficient is dependent upon said range of variance.

10. The method of claim 1, wherein generating first and second system models in response to said first and second operating environments comprises generating said first and second systems models in response to first and second different postures of a user of said implantable hearing instrument.

11. The method of claim 1, further comprising:

generating a plurality of system models associated with a plurality of operating conditions; and

using said plurality of system models to generate said variable system model.

12. A method for use with an implantable hearing instrument, comprising:

generating a plurality of system models defining relationships of corresponding outputs of an implantable microphone and a motion sensor, wherein said plurality of system models are associated with a corresponding plurality of different operating environments for said hearing instrument;

identifying at least one parameter of said system models that varies between different system models;

fitting a function to a set of values corresponding to said at least one parameter that varies between different system models, wherein said function defines a range of variance for said plurality of operating environments;

utilizing said function and said system models to generate a variable system model that is dependent on an operating environment variable associated with said range of variance.

13. The method of claim 12, wherein said different operating environments each comprise a different posture of a user of the hearing instrument.

14. The method of claim 13, wherein said operating environment variable comprises a posture dependent variable.

15. The method of claim 12, wherein identifying comprises identifying at least two parameters for each said system model, wherein said at least two parameters vary between system models.

16. The method of claim 15, wherein fitting a function comprises:

performing a principal component reduction on values associated with said at least two parameters.

17. The method of claim 12, wherein utilizing said function further comprises:

identifying relationships of said system models to said function; and

utilizing said relationships to generate filter coefficients for said variable system model, wherein said filter coefficients are dependent on said operating environment variable.

18. The method of claim 17, further comprising:

generating an estimated value of said operating environment variable;

based on said estimated value, utilizing said variable system model to adjust at least a portion of an output of a motion sensor to generate an adjusted output; and

removing said adjusted output from an output of an implantable microphone.

19. The method of claim 18, further comprising:

iteratively adjusting said estimated value to minimize a residual associated with the removing of said adjusted output from said output of said implantable microphone.