Intelligent parameterization of time-frequency analysis of encephalography signals

Patent metadata

Field	Value
Publication number	US-10856755-B2
Application number	US-201815913880-A
Country	US
Kind code	B2
Filing date	Mar 6, 2018
Priority date	Mar 6, 2018
Publication date	Dec 8, 2020
Grant date	Dec 8, 2020

Abstract

A system assists users in time and frequency analysis of magnetoencephalography (MEG) signals. In one aspect, a system includes an analysis module, a configuration module and a user interface. The analysis module performs a time and frequency analysis of the MEG signal, for example a short time Fourier transform (STFT) or a continuous wavelet transform (CWT) analysis. The analysis is parameterized by a parameter set that affects the time and frequency resolution of the analysis, for example window size and overlap size for STFT or center frequency and decay parameter for CWT. The configuration module automatically determines or assists the user to determine correct values for the parameter set.

First claim

What is claimed is:

1. A system for displaying magnetoencephalography (MEG) signals, the system comprising:
an interface module that receives an MEG signal;
an analysis module that performs a time and frequency analysis of the MEG signal, the time and frequency analysis parameterized by a parameter set that affects a tradeoff between time resolution and frequency resolution of the analysis;
a configuration module that automatically determines values for the parameter set based at least in part on the MEG signal; and
a user interface that displays the time and frequency analysis of the MEG signal performed using the automatically determined values for the parameter set,
wherein:
the user interface also receives user input defining the tradeoff between the time resolution and the frequency resolution of the analysis, the user input not expressly specifying values for the parameter set; and
the configuration module automatically determines the values for the parameter set also based on the user input defining the tradeoff.

2. The system of claim 1 wherein the configuration module performs a Fourier transform of the MEG signal and automatically determines values for the parameter set based on frequency content of the Fourier transform.

3. The system of claim 1 wherein:
the user input defining the tradeoff between the time resolution and the frequency resolution of the analysis specifies a relative importance between time accuracy and frequency accuracy.

4. The system of claim 1 wherein the configuration module also determines a knowledge level of the user and determines the values for the parameter set differently depending on the knowledge level of the user.

5. The system of claim 4 wherein, if the configuration module determines that the user has sufficient knowledge, the user interface allows the user to directly select the values for the parameter set.

6. The system of claim 4 wherein, if the configuration module determines that the user does not have sufficient knowledge, the user interface allows the user to specify the tradeoff between the time resolution and the frequency resolution of the analysis without expressly specifying the values for the parameter set.

7. The system of claim 1 wherein:
the user interface receives another user input specifying a frequency band of interest; and
the configuration module determines a range of values for another parameter set of another time and frequency analysis based on the frequency band of interest.

8. The system of claim 1 wherein:
the time and frequency analysis is a short time Fourier transform (STFT) analysis, and the parameter set for the STFT analysis includes a window size and an overlap size;
and
the configuration module automatically determines values for the window size and the overlap size based on the user input.

9. The system of claim 8 wherein the configuration module increases the window size in response to the user input increasing a relative importance of frequency accuracy.

10. The system of claim 8 wherein the configuration module determines a range of possible window sizes based on a frequency analysis of the MEG signal, and determines the value for the window size within the range based on the user input.

11. The system of claim 10 wherein the range of possible window sizes has a maximum based on a temporal size of the MEG signal.

12. The system of claim 10 wherein the range of possible window sizes has a minimum based on a primary frequency component of the MEG signal.

13. The system of claim 10 wherein the configuration module further determines the value of the overlap size as a function of the value of the window size.

14. The system of claim 1 wherein:
the time and frequency analysis is a continuous wavelet transform (CWT) analysis, and the parameter set for the CWT analysis includes a center frequency and a decay parameter;
and
the configuration module automatically determines values for the center frequency and the decay parameter based on the user input.

15. The system of claim 14 wherein the configuration module increases the center frequency in response to the user input increasing a relative importance of frequency accuracy.

16. The system of claim 14 wherein the configuration module determines a range of possible center frequencies based on a frequency analysis of the MEG signal, and determines the value for the center frequency within the range based on the user input.

17. The system of claim 14 wherein the configuration module further determines the value of the decay parameter as a function of the value of the center frequency.

18. A method implemented on a computer system comprising a processor, the processor executing instructions to effect a method for displaying magnetoencephalography (MEG) signals, the method comprising:
receiving a MEG signal;
receiving a user input defining a tradeoff between time resolution and frequency resolution of a time and frequency analysis of the MEG signal, the user input not expressly specifying values for a parameter set that affects the tradeoff between the time resolution and the frequency resolution of the analysis;
determining values for the parameter set that affects the tradeoff between the time resolution and the frequency resolution of the time and frequency analysis of the MEG signal, wherein the values are determined based on the MEG signal to be displayed and the user input defining the tradeoff;
performing the time and frequency analysis of the MEG signal using the automatically determined values of the parameter set; and
displaying the time and frequency analysis of the MEG signal performed using the automatically determined values of the parameter set.

19. A non-transitory computer-readable storage medium storing executable computer program instructions for displaying magnetoencephalography (MEG) signals, the instructions executable by a computer system and causing the computer system to perform a method comprising:
receiving a MEG signal;
receiving a user input defining a tradeoff between time resolution and frequency resolution of a time and frequency analysis of the MEG signal, the user input not expressly specifying values for a parameter set that affects the tradeoff between the time resolution and the frequency resolution of the analysis;
determining values for the parameter set that affects the tradeoff between the time resolution and the frequency resolution of the time and frequency analysis of the MEG signal, wherein the values are determined based on the MEG signal to be displayed and the user input defining the tradeoff;
performing the time and frequency analysis of the MEG signal using the automatically determined values of the parameter set; and
displaying the time and frequency analysis of the MEG signal performed using the automatically determined values of the parameter set.

Assignees

• Prasad Agara Venkatesha Rao Krishna
• Srinivasa Srinidhi
• Ricoh Co Ltd

Inventors

• Prasad Agara Venkatesha Rao Krishna
• Srinivasa Srinidhi

Classifications

• A61B5/7257 Primary

  using Fourier transforms · CPC title

• A61B5/245 Primary

  specially adapted for magnetoencephalographic [MEG] signals · CPC title

• A61B5/726

  using Wavelet transforms · CPC title

• A61B5/742

  using visual displays (displays for heart-related electrical signals, e.g. ECG, A61B5/339) · CPC title

• G06F3/14

  Digital output to display device {; Cooperation and interconnection of the display device with other functional units} · CPC title