Systems and methods for tracking non-stationary spectral structure and dynamics in physiological data
First Claim
1. A system for tracking dynamic structure in physiological data, the system comprising:
- at least one input configured to receive electroencephalography (“
EEG”
) data acquired from a subject;
a processor configured to;
(i) receive the EEG data from the at least one input;
(ii) assemble a time-frequency representation of signals from the EEG data;
(iii) generate a dynamic model of at least one non-stationary spectral peak using the time-frequency representation and a user indication;
(iv) apply the dynamic model in a parameter estimation algorithm to compute concurrent estimates of peak parameters describing the at least one non-stationary spectral peak, the peak parameters including a peak frequency, a peak bandwidth and a peak amplitude;
(v) generate a report tracking the peak parameters of the at least one non-stationary spectral peak over time; and
a display providing the report to a user.
2 Assignments
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Accused Products
Abstract
Systems and methods for tracking dynamic structure in physiological data are provided. In some aspects, the method includes providing physiological data, including electroencephalogram (“EEG”) data, acquired from a subject and assembling a time-frequency representation of signals from the physiological data. The method also includes generating a dynamic model of at least one non-stationary spectral feature, such as at least one non-stationary spectral peak, using the time-frequency representation and a user indication, and applying a dynamic model of at least one non-stationary spectral feature in a parameter estimation algorithm to compute concurrent estimates of spectral parameters describing the at least one non-stationary spectral feature. The method also includes tracking the spectral parameters of the at least one spectral feature over time.
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Citations
35 Claims
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1. A system for tracking dynamic structure in physiological data, the system comprising:
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at least one input configured to receive electroencephalography (“
EEG”
) data acquired from a subject;a processor configured to; (i) receive the EEG data from the at least one input; (ii) assemble a time-frequency representation of signals from the EEG data; (iii) generate a dynamic model of at least one non-stationary spectral peak using the time-frequency representation and a user indication; (iv) apply the dynamic model in a parameter estimation algorithm to compute concurrent estimates of peak parameters describing the at least one non-stationary spectral peak, the peak parameters including a peak frequency, a peak bandwidth and a peak amplitude; (v) generate a report tracking the peak parameters of the at least one non-stationary spectral peak over time; and a display providing the report to a user. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method for tracking dynamic structure in physiological data comprising:
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providing electroencephalogram (“
EEG”
) data acquired from a subject using a plurality of EEG sensors;using at least one processor configured for; assembling a time-frequency representation of signals from the EEG data; generating a dynamic model of at least one non-stationary spectral peak using the time-frequency representation and a user indication; applying the dynamic model of at least one non-stationary spectral peak in a parameter estimation algorithm to compute concurrent estimates of peak parameters describing the at least one non-stationary spectral peak, the peak parameters including a peak frequency, a peak bandwidth and a peak amplitude; generating a report tracking the peak parameters of the at least one non-stationary spectral peak over time; and providing the report to a user. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23)
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24. A system for tracking dynamic structure in physiological data, the system comprising:
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at least one input configured to receive physiological data acquired from a subject; a processor configured to; (i) receive the physiological data from the at least one input; (ii) assemble a time-frequency representation of signals from the physiological data; (iii) generate a dynamic model of at least one non-stationary spectral feature using the time-frequency representation and a user indication; (iv) apply the dynamic model in a parameter estimation algorithm to compute concurrent estimates of spectral parameters describing the at least one non-stationary spectral feature; (v) generate a report tracking the spectral parameters of the at least one non-stationary spectral feature over time; and (vi) communicate the report to one of a user via a display or to a drug delivery system to control operation of the drug delivery system. - View Dependent Claims (25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35)
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Specification