Method, apparatus, and computer program product for assessment of attentional impairments

• US 7,403,814 B2
• Filed: 05/06/2002
• Issued: 07/22/2008
• Est. Priority Date: 05/04/2001
• Status: Active Grant

• Current Assignee: University of Virginia Patent Foundation (University of Virginia)
• Original Assignee: University of Virginia Patent Foundation (University of Virginia)
• Inventors: Cox, Daniel J., Kovatchev, Boris P., Robeva, Rayna S., Penberthy, Jennifer Kim
• Primary Examiner(s): Marmor, II; Charles A.
• Assistant Examiner(s): Natnithithadha; Navin
• Application Number:
  US10/476,826
• Publication Number:
  US 20040152995A1
• Time in Patent Office: 2,269 Days
• Field of Search: 600/544, 600/545, 600/300
• US Class Current: 600/544
• CPC Class Codes: A61B 5/168 Evaluating attention deficit, hyperactivity
• CPC Class Codes: A61B 5/374 Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
• CPC Class Codes: A61B 5/378 Visual stimuli
• CPC Class Codes: A61B 5/4088 Diagnosing of monitoring cognitive diseases, e.g. Alzheimer, prion diseases or dementia
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/726 using Wavelet transforms

Abstract

A method, apparatus, and computer useable medium that provides, among other things, a standardized test protocol for screening and evaluation of attentional impairment using EEG data. Further, the method, apparatus, and computer program product enhances existing psychological, behavioral, and physiological EEG data acquisition systems by introducing a sequential stochastic model procedure, and an intelligent data interpretation component capable of assessing EEG inconsistencies associated attentional impairments. Potential users of this product will be any person or organization that diagnoses or treats persons with attentional or cognitive impairments. The method can be used for initial screening and diagnosis of disorders associated with impaired attention, such as ADHD, as well as for treatment and evaluation of the effects of treatments, such as medication or additional therapies.

Claims

1. A method for assessing individuals for disorders associated with attentional impairments, said method comprising:

a) placing at least one electrode at a respective cranial site on an individual;

b) obtaining digitized EEG data at epochs of a plurality of frequency bands, said EEG data collected from a first cognitive task period, a rest period, and a second cognitive task period, wherein;

the individual performs predetermined tasks during said first and second cognitive task periods, and the individual rests during said rest period;

c) processing said EEG data to determine electrophysical power (pW) obtained from said first cognitive task period and said second cognitive task period;

d) calculating the power change distance (PCD) between said first and second cognitive task periods;

e) filtering said PCD data by comparing said PCD data with a noise threshold number;

f) applying a cutoff frequency dividing said filtered PCD data into two ranges, a first range being PCD data below said cut-off frequency and a second range being PCD data above said cut-off frequency;

g) calculating a Consistency Index, said Consistency Index being defined by the absolute value of the difference between a sum of said below cut-off PCD data and a sum of said above cut off PCD data; and

h) comparing said Consistency Index to a control group database to provide the assessment of the individual.

2. The method of claim 1, wherein calculating said PCD in step (d) is calculated using the following formula:

$\mathrm{PCD}=\frac{\mathrm{M1}-\mathrm{M2}}{\sqrt{\frac{{\mathrm{SD1}}^2}{\mathrm{N1}}+\frac{{\mathrm{SD2}}^2}{\mathrm{N2}}}}$

wherein M1 and M2 are the mean powers at two contiguous tasks, SD1 and SD2 are their standard deviation, and N1 and N2 are the epoch counts at said cognitive task periods.

3. The method of claim 2 wherein filtering said PCD data in step (e) comprises:

comparing said PCD data with said noise threshold number, wherein any said PCD that are larger by an absolute value than said threshold value are marked by 1 or −

1 depending on their direction, and whereas any said PCD below threshold are marked by zero, whereby filtering transforms said PCD into a sequence of 1, 0, −

1.

4. The method of claim 3, wherein said noise threshold number is a number or range of numbers ranging from about 1.5 to about 4.0.

5. The method of claim 3, wherein calculating said Consistency Index of step (g) is calculated using the following formula:

$\mathrm{CI}=100<br><br><br><br>\frac{1}{N}<br><br>\left(\underset{\mathrm{belowcutof}<br><br><br><br>f}{\sum <br><br>}<br><br>{\mathrm{\delta <br><br>}}_i-\underset{\mathrm{abovecutof}<br><br><br><br>f}{\sum <br><br>}<br><br>{\mathrm{\delta <br><br>}}_j\right)<br><br><br><br><br><br>\mathrm{percent},<br><br>\%<br><br><br><br>\mathrm{wherein}<br><br><br><br>{\mathrm{\delta <br><br>}}_i,{\mathrm{\delta <br><br>}}_j=-1,0,1.$

6. The method of claim 1, wherein:

said first cognitive task period has a duration within a range of about 8 to about 25 minutes;

said rest period has a duration within a range of about 3 to about 8 minutes; and

said second cognitive task period has a duration within a range of about 8 to about 25 minutes.

7. The method of claim 6, wherein:

said first cognitive task period has a duration within a range of about 9 to about 11 minutes;

said rest period has a duration within a range of about 4 to about 6 minutes; and

said second cognitive task period has a duration within a range of about 9 to about 11 minutes.

8. The method of claim 7, wherein:

said first cognitive task period has a duration of about 10 minutes;

said rest period has a duration of about 5 minutes; and

said second cognitive task period has a duration of 10 minutes.

9. The method of claim 1, wherein the individual during said first and second cognitive task periods participate in an activity selected from the group consisting of:

reading, performing math, viewing video, tracking on a computer screen, and listening.

10. The method of claim 1, wherein said digitized EEG data in step (b) is obtained by utilizing a Fast Fourier Transform analysis.

11. The method of claim 1, wherein said digitized EEG data in step (b) is obtained in four frequency bands:

Theta (4-8 Hz), Alpha (8-14 Hz), Beta (13-22 Hz) and High Beta (22-40 Hz).

12. The method of claim 1, wherein number of electrodes range from 1 to 15.

13. The method of claim 1, wherein the disorders include at least one of mild cognitive impairment (MCI) in individuals with pre-dementia, dementia, dementia with Lewy bodies, Alzheimer'"'"'s Disease, traumatic brain injury, Attention Deficit/Hyperactivity Disorder (ADHD), and cognitive/attentional declines associated with chronic diseases such as diabetes, cardiovascular disease, and HIV infection.

14. The method of claim 1, wherein the assessment of the individual is utilized to determine the type of medication or other treatment or the amount of medication or other treatment or both the type and the amount to be prescribed to the individual for treating the disorder.

15. The method of claim 1, wherein as the individuals receive a course of treatment for any of the disorders, the method further comprises:

repeating steps (a) through (g) at least one or more times over a select duration to determine success or efficacy of the treatment.

16. An apparatus for assessing individuals for disorders associated with attentional impairments, said apparatus comprising:

an EEG device having at least one electrode adapted for attachment at a respective cranial site on an individual, said EEG device obtaining digitized EEG data at epochs of a plurality of frequency bands, said EEG data collected from a first cognitive task period, a rest period, and a second cognitive task period, wherein;

the individual performs predetermined tasks during said first and second cognitive task periods, and the individual rests during said rest period;

a processor programmed to;

a) process said EEG data to determine electrophysical power (pW) obtained from said first cognitive task period and said second cognitive task period;

b) calculate the power change distance (PCD) between said first and second cognitive task periods;

c) filter said PCD data by comparing said PCD data with a noise threshold number;

d) apply a cutoff frequency dividing said filtered PCD data into two ranges, a first range being PCD data below said cut-off frequency and a second range being PCD data above said cut-off frequency;

e) calculate a Consistency Index, said Consistency Index being defined by the absolute value of the difference between a sum of said below cut-off PCD data and a sum of said above cut off PCD data; and

f) compare said Consistency Index to a control group database to provide the assessment of the individual.

17. The apparatus of claim 16, wherein calculating said PCD in step (d) is calculated using the following formula:

$\mathrm{PCD}=\frac{\mathrm{M1}-\mathrm{M2}}{\sqrt{\frac{{\mathrm{SD1}}^2}{\mathrm{N1}}+\frac{{\mathrm{SD2}}^2}{\mathrm{N2}}}}$

wherein M1 and M2 are the mean powers at two contiguous tasks,

SD1 and SD2 are their standard deviation, and

N1 and N2 are the epoch counts at said cognitive task periods.

18. The apparatus of claim 17 wherein filtering said PCD data in step (e) comprises:

comparing said PCD data with said noise threshold number, wherein any said PCD that are larger by an absolute value than said threshold value are marked by 1 or −

1 depending on their direction, and wherein any said PCD data below threshold are marked by zero, whereby filtering transforms said PCD into a sequence of 1, 0, −

1.

19. The apparatus of claim 18, wherein said noise threshold number is a number or range of numbers ranging from about 1.5 to about 4.0.

20. The apparatus of claim 18, wherein calculating said Consistency Index of step (g) is calculated using the following formula:

$\mathrm{CI}=100<br><br><br><br>\frac{1}{N}<br><br>\left(\underset{\mathrm{belowcutof}<br><br><br><br>f}{\sum <br><br>}<br><br>{\mathrm{\delta <br><br>}}_i-\underset{\mathrm{abovecutof}<br><br><br><br>f}{\sum <br><br>}<br><br>{\mathrm{\delta <br><br>}}_j\right)<br><br><br><br><br><br>\mathrm{percent},<br><br><br><br><br><br>\%<br><br><br><br>\mathrm{wherein}<br><br><br><br>{\mathrm{\delta <br><br>}}_i,{\mathrm{\delta <br><br>}}_j=-1,0,1.$

21. The apparatus of claim 16, wherein:

said first cognitive task period has a duration within a range of about 8 to about 25 minutes;

said rest period has a duration within a range of about 3 to about 8 minutes; and

said second cognitive task period has a duration within a range of about 8 to about 25 minutes.

22. The apparatus of claim 21, wherein:

said first cognitive task period has a duration within a range of about 9 to about 11 minutes;

said rest period has a duration within a range of about 4 to about 6 minutes; and

said second cognitive task period has a duration within a range of about 9 to about 11 minutes.

23. The apparatus of claim 22, wherein:

said first cognitive task period has a duration of about 10 minutes;

said rest period has a duration of about 5 minutes; and

said second cognitive task period has a duration of 10 minutes.

24. The apparatus of claim 16, wherein the individual during said first and second cognitive task periods participate in an activity selected from the group consisting of:

reading, performing math, viewing video, tracking on a computer screen, and listening.

25. The apparatus of claim 16, wherein said digitized EEG data in step (b) is obtained by utilizing a Fast Fourier Transform analysis.

26. The apparatus of claim 16, wherein said digitized EEG data in step (b) is obtained in four frequency bands:

Theta (4-8 Hz), Alpha (8-14 Hz), Beta (13-22 Hz) and High Beta (22-40 Hz).

27. The apparatus of claim 16, wherein number of electrodes range from 1 to 15.

28. The apparatus of claim 16, wherein the disorders include at least one of mild cognitive impairment (MCI) in individuals with pre-dementia, dementia, dementia with Lewy bodies, Alzheimer'"'"'s Disease, traumatic brain injury, Attention Deficit/Hyperactivity Disorder (ADHD), and cognitive/attentional declines associated with chronic diseases such as diabetes, cardiovascular disease, and HIV infection.

29. The apparatus of claim 16, wherein the assessment of the individual is utilized to determine the type of medication or other treatment or the amount of medication or other treatment or both the type and the amount to be prescribed to the individual for treating the disorder.

30. The apparatus of claim 16, wherein as the individuals receive a course of treatment for any of the disorders, the apparatus further comprises:

repeating steps (a) through (g) at least one or more times over a select duration to determine success or efficacy of the treatment.

31. A computer program product comprising a computer readable medium having stored therein computer executable instructions for enabling at least one processor in a computer system to assess individuals for disorders associated with attentional impairments based on digitized EEG data, said digitized EEG data obtained at epochs of a plurality of frequency bands from an individual, said EEG data collected from a first cognitive task period, a rest period, and a second cognitive task period, wherein the individual performs predetermined tasks during said first and second cognitive task periods, and the individual rests during said rest period, said computer executable instructions comprising instructions for:

a) processing said EEG data to determine electrophysical power (pW) obtained from said first cognitive task period and said second cognitive task period;

b) calculating the power change distance (PCD) between said first and second cognitive task periods;

c) filtering PCD data by comparing said PCD data with a noise threshold number;

d) applying a cutoff frequency dividing said filtered PCD data into two ranges, a first range being PCD data below said cut-off frequency and a second range being PCD data above said cut-off frequency;

e) calculating a Consistency Index, said Consistency Index being defined by the absolute value of the difference between a sum of said below cut-off PCD data and a sum of said above cut off PCD data; and

f) comparing said Consistency Index to a control group database to provide the assessment of the individual.