System and method for adaptive stimulus-response signal filtering

• US 8,484,270 B2
• Filed: 06/12/2008
• Issued: 07/09/2013
• Est. Priority Date: 06/12/2007
• Status: Active Grant

• Current Assignee: Vivosonic, Inc.
• Original Assignee: Vivosonic, Inc.
• Inventors: Kurtz, Isaac, Steinman, Aaron, Sokolov, Yuri
• Primary Examiner(s): Malzahn, David H
• Application Number:
  US12/138,271
• Publication Number:
  US 20090149148A1
• Time in Patent Office: 1,853 Days
• Field of Search: None
• US Class Current: 708/300
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/367 Electrophysiological study [EPS], e.g. electrical activation mapping or electro-anatomical mapping
• CPC Class Codes: A61B 5/7253 characterised by using transforms
• CPC Class Codes: G06F 2218/12 Classification; Matching
• CPC Class Codes: H03H 17/0211 using specific transformation algorithms, e.g. WALSH functions, Fermat transforms, Mersenne transforms, polynomial transforms, Hilbert transforms correlation computation G06F17/156
• CPC Class Codes: H03H 2222/06 using wavelets

Abstract

A system and method for filtering a signal comprising: receiving a signal of interest; receiving a signal indicating that a stimulus has been applied; receiving the synchronized stimulus signal and signal of interest; recursively selecting a portion of the signal of interest associated with a stimulus being applied and assign the selected portion of the signal of interest to one of the plurality of buffers; combining all responses in each of said plurality of buffers; transforming the combination of all responses in each buffer to a transform space; comparing the transform components of the buffers to determine a scaling factor; applying the scaling factor to the spectral components of the buffers; performing an inverse transform on the result of combining the buffers to return to the time domain to produce a filtered signal, and outputting the filtered signal received from the processor.

Claims

1. A system for processing a noisy signal comprising multiple instances of a signal of interest added to noise, wherein each instance of the signal of interest is causally related to a stimulus, the system comprising:

an input module for receiving the noisy signal while a plurality of stimuli occur, each stimulus corresponding to a distinct instance of the signal of interest;

a plurality of memory buffers;

a processor configured to;

receive the noisy signal from the input module;

distribute a plurality of segments of the noisy signal, each segment corresponding to a stimulus, among at least two of the plurality of memory buffers;

within each of the at least two of the plurality of memory buffers, mathematically combine the plurality of segments to form a combined result for each of the at least two of the plurality of memory buffers;

transform the combined result for each of said plurality of memory buffers to a transform space to obtain transform components;

calculate a degree of synchronicity among select corresponding transform components for the plurality of memory buffers;

apply a scaling factor derived from the degree of synchronicity to select transform components; and

apply an inverse transform to the scaled select transform components for the plurality of memory buffers to provide at least one filtered signal derived from the plurality of memory buffers, and

an output module configured to output the at least one filtered signal, wherein each filtered signal represents the signal of interest.

2. The system of claim 1, wherein the processor is further configured to, prior to applying the scaling factor:

recursively, for a predetermined number of times;

randomly order the plurality of segments of the noisy signal among at least two of the plurality of memory buffers and combine the plurality of segments of the noisy signal within each of the at least two of the plurality of memory buffers to form a combined result for each of the at least two of the plurality of memory buffers;

transform the combined result for each of said plurality of memory buffers to a transform space to obtain transform components; and

calculate a degree of synchronicity among select corresponding transform components for the plurality of memory buffers,

derive a final degree of synchronicity from among the degrees of synchronicity for each random ordering; and

utilize the final degree of synchronicity as the scaling factor when applying the scaling factor to select transform components.

3. The system of claim 2, wherein the processor is further configured to distribute the plurality of segments of the noisy signal among at least two of the plurality of memory buffers by:

assigning the plurality of segments of the noisy signal to the plurality of memory buffers in a biased manner so that the reliability of a comparative statistic is increased.

4. The system of claim 1, wherein the processor is further configured to distribute the plurality of segments of the noisy signal among at least two of the plurality of memory buffers by:

assigning the plurality of segments of the noisy signal to the plurality of memory buffers in a biased manner so that the reliability of a comparative statistic is increased.

5. The system of claim 1, wherein the stimulus is a recurring feature of a steady state waveform.

6. The system of claim 5, wherein the steady state waveform is an auditory steady state signal and the recurring feature is a fixed phase of the auditory steady state signal.

7. The system of claim 1, wherein the stimulus is a sensory stimulus and the signal of interest is a physiological response.

8. The system of claim 7, wherein the sensory stimulus is an auditory stimulus.

9. The system of claim 1, wherein the processor is configured to perform the transform on each of the plurality of segments before combining the plurality of segments within each of said plurality of memory buffers.

10. The system of claim 1, wherein the scaling factor further comprises a predetermined threshold.

11. The system of claim 1, wherein the processor is further configured to, after calculating a degree of synchronicity, determine a presence of at least two instances of the signal of interest based on a value of the degree of synchronicity for at least one of the transform components.

12. The system of claim 11, wherein the processor is configured to determine the presence of the signal of interest based on at least one of the degrees of synchronicity satisfying a predetermined threshold.

13. A system for buffering a noisy signal comprising multiple instances of a signal of interest added to noise, wherein each instance of the signal of interest is causally related to a stimulus, the system comprising:

an input module for receiving the noisy signal while a plurality of stimuli occur, each stimulus corresponding to a distinct instance of the signal of interest;

a plurality of memory buffers;

a processor configured to;

receive the noisy signal from the input module;

assign a plurality of segments of the noisy signal, each segment corresponding to a stimulus, to the plurality of memory buffers in a biased manner so that the reliability of a comparative statistic is increased; and

an output module configured to output the contents of at least one of the plurality of memory buffers or a value of the comparative statistic for further processing.

14. The system of claim 13, wherein the processor is further configured to determine a presence of at least two instances of the signal of interest based on the comparative statistic.

15. The system of claim 14, wherein the processor is configured to determine the presence of at least two instances of the signal of interest based on the comparative statistic satisfying a predetermined threshold.

16. A system for buffering a noisy signal comprising multiple instances of a signal of interest added to noise, wherein each instance of the signal of interest is causally related to a stimulus, the system comprising:

an input module for receiving the noisy signal while a plurality of stimuli occur, each stimulus corresponding to a distinct instance of the signal of interest;

a plurality of memory buffers;

a processor configured to;

receive the noisy signal from the input module;

recursively, for a predetermined number of times;

randomly order a plurality of segments of the noisy signal and assign the plurality of segments of the noisy signal to the plurality of memory buffers in a random manner;

calculate a comparative statistic for each random ordering;

select a random ordering having a final comparative statistic that is representative of a distribution of the comparative statistics

an output module configured to output the selected random ordering for further processing.

17. The system of claim 16, wherein the processor is further configured to determine a presence of the signal of interest based on the comparative statistic.

18. The system of claim 17, wherein the processor is configured to determine the presence of the signal of interest based on the comparative statistic satisfying a predetermined threshold.