APPARATUS, SYSTEM AND METHOD FOR NOISE CANCELLATION AND COMMUNICATION FOR INCUBATORS AND RELATED DEVICES

• US 20130204617A1
• Filed: 03/15/2013
• Published: 08/08/2013
• Est. Priority Date: 12/07/2007
• Status: Active Grant

• Current Assignee: Northern Illinois Research Foundation
• Original Assignee: Board of Regents for Northern Illinois University
• Inventors: Kuo, Sen M., Liu, Lichuan
• Granted Patent: US 9,247,346 B2
• Time in Patent Office: Days
• US Class Current: 704/233
• CPC Class Codes: A47G 2009/006 comprising sound equipment
• CPC Class Codes: A47G 9/10 Pillows pillow holders A47C21/00, A47C21/026; specially adapted for preventing snoring A61F5/56
• CPC Class Codes: A61G 11/00 Baby-incubators; Couveuses
• CPC Class Codes: G10K 11/17823 Reference signals, e.g. ambient acoustic environment
• CPC Class Codes: G10K 11/17837 by retaining part of the ambient acoustic environment, e.g. speech or alarm signals that the user needs to hear
• CPC Class Codes: G10K 11/17854 the filter being an adaptive filter
• CPC Class Codes: G10K 11/17855 for improving speed or power requirements
• CPC Class Codes: G10K 11/17881 the reference signal being an acoustic signal, e.g. recorded with a microphone
• CPC Class Codes: G10K 11/17885 additionally using a desired external signal, e.g. pass-through audio such as music or speech
• CPC Class Codes: G10K 2210/1081 Earphones, e.g. for telephones, ear protectors or headsets
• CPC Class Codes: G10K 2210/116 Medical; Dental
• CPC Class Codes: G10K 2210/3014 Adaptive noise equalizers [ANE], i.e. where part of the unwanted sound is retained
• CPC Class Codes: H04R 3/002 Damping circuit arrangements for transducers, e.g. motional feedback circuits
• CPC Class Codes: H04R 3/12 for distributing signals to two or more loudspeakers specially adapted for hearing aids H04R25/407

Abstract

Systems, apparatuses and methods for integrating adaptive noise cancellation (ANC) with communication features in an enclosure, such as an incubator, bed, and the like. Utilizing one or more error and reference microphones, a controller for a noise cancellation portion reduces noise within a quiet area of the enclosure. Voice communications are provided to allow external voice signals to be transmitted to the enclosure with minimized interference with noise processing. Vocal communications from within the enclosure may be processed to determine certain characteristics/features of the vocal communications. Using these characteristics, certain emotive and/or physiological states may be identified.

Claims

1. An enclosure, comprising:

a noise cancellation portion, comprising a controller unit, configured to be operatively coupled to one or more error microphones and a reference sensing unit, wherein the controller unit processes signals received from one or more error microphones and reference sensing unit to reduce noise in an area within the enclose using one or more speakers; and

a communications portion, comprising a sound analyzer and transmitter, wherein the communication portion is operatively coupled to the noise cancellation portion, said communications portion being configured to receive a voice signal from the enclosure and transform the voice signal to identify characteristics thereof.

2. The enclosure of claim 1, wherein the communications portion is configured to extract features from the voice signal.

3. The enclosure of claim 2, wherein the features comprise at least one of linear predictive coding (LPC), Mel-frequency cepstral coefficients (MFCC), Bark-frequency cepstral coefficients (BFCC).

4. The enclosure of claim 2, wherein the communications portion is configured to identify characteristics of the features of voice signal using at least one of a Gaussian mixture model (GMM), hidden Markov model (HMM), and artificial neural network (ANN).

5. The enclosure of claim 1, wherein the characteristics of the voice signal comprise at least one of an emotional or physiological state.

6. The enclosure of claim 1, further comprising a voice input operatively coupled to the noise cancellation portion, wherein the voice input is configured to receive external voice signals for reproduction on the one or more speakers.

7. The enclosure of claim 6, wherein the noise cancellation portion is configured to filter the external voice signals to minimize interference with signals received from one or more error microphones and reference sensing unit for reducing noise in the area within the enclose.

8. A method for providing noise cancellation and communication within an enclosure, comprising:

processing signals, received from one or more error microphones and reference sensing unit, in a controller of a noise cancellation portion to reduce noise in an area within the enclose using one or more speakers;

receiving internal voice signals from the enclosure;

extracting features from the internal voice signals; and

identifying characteristics of the voice signals based on the transformation.

9. The method of claim 8, wherein the transformation transforms the voice signal from a time domain to a frequency domain.

10. The method of claim 9, wherein the features comprise at least one of linear predictive coding (LPC), Mel-frequency cepstral coefficients (MFCC), Bark-frequency cepstral coefficients (BFCC) and short-time zero crossing.

11. The method of claim 9, wherein characteristic are identified of the transformed voice signal using at least one of a Gaussian mixture model (GMM), hidden Markov model (HMM), and artificial neural network (ANN).

12. The method of claim 8, wherein the characteristics of the voice signal comprise at least one of an emotional or physiological state.

13. The method of claim 8, further comprising the step of receiving an external voice signals from the enclosure for reproduction on the one or more speakers within the enclosure.

14. The method of claim 13, wherein the signals are processed in the noise cancellation portion to filter the external voice signals to minimize interference with the signals received from one or more error microphones and reference sensing unit to reduce noise in the area within the enclose.

15. An enclosure, comprising:

a noise cancellation portion, comprising a controller unit, configured to be operatively coupled to one or more error microphones and a reference sensing unit, wherein the controller unit processes signals received from one or more error microphones and reference sensing unit to reduce noise in an area within the enclose using one or more speakers;

a communications portion, comprising a sound analyzer and transmitter, wherein the communication portion is operatively coupled to the noise cancellation portion, said communications portion being configured to receive a voice signal from the enclosure and transform the voice signal to identify characteristics thereof; and

a voice input apparatus operatively coupled to the noise cancellation portion, wherein the voice input apparatus is configured to receive external voice signals for reproduction on the one or more speakers.

16. The enclosure of claim 15, wherein the communications portion is configured to extract features from the voice signal.

17. The enclosure of claim 16, wherein the feature comprises at least one of linear predictive coding (LPC), Mel-frequency cepstral coefficients (MFCC), Bark-frequency cepstral coefficients (BFCC) and short-time zero crossing.

18. The enclosure of claim 16, wherein the communications portion is configured to identify characteristics of the features of the voice signal using at least one of a Gaussian mixture model (GMM), hidden Markov model (HMM), and artificial neural network (ANN).

19. The enclosure of claim 15, wherein the characteristics of the voice signal comprise at least one of an emotional or physiological state.

20. The enclosure of claim 15, wherein the noise cancellation portion is configured to filter the external voice signals to minimize interference with signals received from one or more error microphones and reference sensing unit for reducing noise in the area within the enclose.