Method and system for detecting and/or predicting cerebral disorders
First Claim
1. A method of detecting or predicting a cerebral disorder, comprising the steps of:
- analyzing input biological or physical data using a data processing routine including a set of application parameters associated with biological data correlating with the cerebral disorder to produce a data series, determining whether a slope of the data series is smaller than a predetermined value;
if the slope is less than a predetermined value, setting the slope to a predetermined number; and
using the data series to detect or predict the onset of the cerebral disorder.
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Abstract
Cerebral disorders are detected and/or predicted by analyzing input biological or physical data using a data processing routine. The data processing routine includes a set of application parameters associated with biological data correlating with the biological anomalies. The data processing routine uses an algorithm to produce a data series, e.g., a PD2i data series. The data series is used to detect or predict the onset of the cerebral disorders. To reduce noise in the data series, the slope is set to a predetermined number if it is less than a predetermined value. To further reduce noise, a noise interval within the data series is determined and, if the noise interval is within a predetermined range, the data series is divided by another predetermined number, and new values are produced for the data series.
35 Citations
22 Claims
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1. A method of detecting or predicting a cerebral disorder, comprising the steps of:
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analyzing input biological or physical data using a data processing routine including a set of application parameters associated with biological data correlating with the cerebral disorder to produce a data series, determining whether a slope of the data series is smaller than a predetermined value;
if the slope is less than a predetermined value, setting the slope to a predetermined number; and
using the data series to detect or predict the onset of the cerebral disorder.
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2. The method of claim 1, wherein the cerebral disorder is bovine spongioform encephalitis.
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3. The method of claim 1, wherein the cerebral disorder is Alzheimer'"'"'s disease.
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4. The method of claim 1, wherein the data processing routine uses the following algorithm to produce a data series PD2i:
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PD2i⊂
log C(n, r, nref*)/log rwhere ⊂
means scales as, C is the correlation integral for PD2i in which n equals the data length, r equals the scaling range, and nref* equals a location of the reference vector for estimating the scaling region slope of log C/log r in a restricted small log-r range that is devoid of the effects of non-stationary data.
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5. The method of claim 1, wherein the predetermined value is approximately 0.5.
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6. The method of claim 1, wherein the predetermined number is zero.
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7. The method of claim 1, further comprising:
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determining a noise interval within the data series; and
if the noise interval is within a predetermined range, dividing the data series by another predetermined number and repeating the step of analyzing to produce new values for the data series.
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8. The method of claim 7, wherein the other predetermined number is two.
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9. The method of claim 7, wherein the predetermined range is −
- x to x, where x is any number.
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10. The method of claim 9, wherein the predetermined range is −
- 5 to 5.
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11. The method of claim 1, wherein the input biological or physical data includes electrophysiological data.
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12. A method of detecting or predicting cerebral disorder, comprising the steps of:
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analyzing input biological or physical data using a data processing routine including a set of application parameters associated with biological data correlating with the cerebral disorder to produce a data series;
determining a noise interval within the data series; and
if the noise interval is within a predetermined range, dividing the data series by a predetermined number and repeating the step of analyzing to produce new values for the data series;
orif the noise interval is outside the predetermined range, using the data series to detect or predict the onset of cerebral disorder.
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13. The method of claim 12, wherein the cerebral disorder is bovine spongioform encephalitis.
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14. The method of claim 12, wherein the cerebral disorder is Alzheimer'"'"'s disease.
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15. The method of claim 12, wherein the data processing routine uses the following algorithm to produce a data series PD2i:
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PD2i⊂
log C(n, r, nref*)/log rwhere ⊂
means scales as, C is the correlation integral for PD2i in which n equals the data length, r equals the scaling range, and nref* equals a location of the reference vector for estimating the scaling region slope of log C/log r in a restricted small log-r range that is devoid of the effects of non-stationary data.
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16. The method of claim 12, wherein the predetermined number is two.
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17. The method of claim 12, wherein the predetermined range is −
- x to x, where x is any number.
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18. The method of claim 17, wherein the predetermined range is −
- 5 to 5.
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19. The method of claim 12, further comprising:
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determining whether a slope of the data series is smaller than a predetermined value; and
if the slope is less than a predetermined value, setting the slope to another predetermined number.
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20. The method of claim 19, wherein the predetermined value is approximately 0.5.
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21. The method of claim 19, wherein the other predetermined number is zero.
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22. The method of claim 12, wherein the biological or physical data includes electrophysiological data.
Specification