Claims Analysis
Total Claims: 39
Claim 1
Independent Claim
137 words
An EEG (electroencephalograph) system comprising: (a) a plurality of EEG electrode means adapted to be removably connected to the scalp of a subject to detect the subject's brain waves; (b) amplification means connected to the EEG electrode means to amplify the detected brain waves and produce an amplified signal output for each EEG electrode means; (c) a three-axis translation accelerometer adapted to be removably positioned on the head of the subject to detect the subject's head movement, the accelerometer producing at least one signal output indicative of the head movements; (d) an interference canceler connected to the outputs of the amplification means and the accelerometer signal output, the canceler comprising a filter having an output and an adder connected to the output of the filter and the amplification means, the adder producing corrected and usable EEG signals.
Claim 2
Dependent Claim
137 words
An EEG (electroencephalograph) system comprising: (a) a plurality of EEG electrode means adapted to be removably connected to the scalp of a subject to detect the subject's brain waves; (b) amplification means connected to the EEG electrode means to amplify the detected brain waves and produce an amplified signal output for each EEG electrode means; (c) a three-axis translation accelerometer adapted to be removably positioned on the head of the subject to detect the subject's head movement, the accelerometer producing at least one signal output indicative of the head movements; (d) an interference canceler connected to the outputs of the amplification means and the accelerometer signal output, the canceler comprising a filter having an output and an adder connected to the output of the filter and the amplification means, the adder producing corrected and usable EEG signals.
Claim 3
Dependent Claim
40 words
An EEG system as in claim 1 and further comprising an eye movement sensor means adapted to be removably connected proximate an eye of the subject to generate an eye movement reference signal which is an input to the filter.
Claim 4
Dependent Claim
31 words
An EEG system as in claim 1 wherein the filter uses an algorithm embodied in a software program executed on a digital computer system or embodied in a digital hardware circuit.
Claim 5
Dependent Claim
31 words
An EEG system as in claim 3 wherein the filter is an adaptive filter having a coefficient matrix which is adjusted with time according to a Least Mean Squares (LMS) algorithm.
Claim 6
Dependent Claim
41 words
An EEG system as in claim 4 wherein the filter is an adaptive filter having a filter coefficient matrix which is adjusted with time according to an Exponentially Weighted Recursive Least Squares (EWRLS) algorithm or a Recursive Least Squares (RLS) algorithm.
Claim 7
Dependent Claim
48 words
An EEG system as in claim 3 wherein the filter uses a block adaptive filter algorithm selected from the group of autoregressive with external input (ARX), autoregressive and moving average with external input (ARMAX), Wiener filters, Kalman filters, Linear Predictors, autoregressive and moving average (ARMA) and Box-Jenkins model.
Claim 8
Dependent Claim
15 words
An EEG system as in claim 1 wherein the filter is an analog hardware circuit.
Claim 9
Dependent Claim
14 words
An EEG system as in claim 1 wherein the filter is a non-adaptive filter.
Claim 10
Dependent Claim
133 words
An EEG (electroencephalograph) system comprising: (a) a plurality of EEG electrode means adapted to be removably connected to the scalp of a subject to detect the subject's brain waves; (b) amplification means connected to the EEG electrode means to amplify the detected brain waves and produce an amplified signal output for each EEG electrode means; (c) signal averaging means to combine and average at least some of the amplified signal outputs to generate a spatial average EEG signal as a head and body reference signal; and (d) an interference canceler connected to the outputs of the amplification means and the signal averaging means, the canceler comprising a filter having an output, and an adder connected to the output of the filter and the amplification means, the adder producing corrected and usable EEG signals.
Claim 11
Dependent Claim
133 words
An EEG (electroencephalograph) system comprising: (a) a plurality of EEG electrode means adapted to be removably connected to the scalp of a subject to detect the subject's brain waves; (b) amplification means connected to the EEG electrode means to amplify the detected brain waves and produce an amplified signal output for each EEG electrode means; (c) signal averaging means to combine and average at least some of the amplified signal outputs to generate a spatial average EEG signal as a head and body reference signal; and (d) an interference canceler connected to the outputs of the amplification means and the signal averaging means, the canceler comprising a filter having an output, and an adder connected to the output of the filter and the amplification means, the adder producing corrected and usable EEG signals.
Claim 12
Dependent Claim
72 words
An EEG system as in claim 9 and further including an accelerometer or movement detector adapted to be removably positioned on the head of the subject to detect the subject's head movements, the accelerometer or movement detector generating at least one signal indicative of head movements, which signal is used to determine the starting and ending of the head movements, and means to operate the canceler only during said determined head movements.
Claim 13
Dependent Claim
24 words
An EEG system as in claim 11 wherein an accelerometer is positioned on the subject's head and the accelerometer is a three-axis translational accelerometer.
Claim 14
Dependent Claim
14 words
An EEG system as in claim 9 wherein the filter is an adaptive filter.
Claim 15
Dependent Claim
29 words
An EEG system as in claim 12 wherein the adaptive filter comprises a filter coefficient matrix which is adjusted with time according to a Least Mean Squares (LMS) algorithm.
Claim 16
Dependent Claim
37 words
An EEG system as in claim 12 wherein the adaptive filter comprises a filter coefficient matrix which is adjusted with time according to an Exponentially Weighted Recursive Least Squares (EWRLS) algorithm or Recursive Least Squares (RLS) algorithm.
Claim 17
Dependent Claim
31 words
An EEG system as in claim 9 wherein the filter is an algorithm embodied in a software program executed on a digital computer system or embodied in a digital hardware circuit.
Claim 18
Dependent Claim
15 words
An EEG system as in claim 9 wherein the filter is an analog hardware circuit.
Claim 19
Dependent Claim
48 words
An EEG system as in claim 9 wherein the filter comprises a block adaptive filter algorithm selected from the group of autoregressive with external input (ARX), autoregressive and moving average with external input (ARMAX), Wiener filters, Kalman filters, Linear Predictors, autoregressive and moving average (ARMA) and Box-Jenkins model.
Claim 20
Dependent Claim
40 words
An EEG system as in claim 9 and further comprising an eye movement sensor means adapted to be removably connected proximate an eye of the subject to generate an eye movement reference signal which is an input to the filter.
Claim 21
Dependent Claim
14 words
An EEG system as in claim 9 wherein the filter is a non-adaptive filter.
Claim 22
Dependent Claim
150 words
An EEG (electroencephalograph) method comprising the steps of: (a) connecting a plurality of EEG electrodes to the scalp of a subject to detect the subject's brain waves; (b) amplifying the subject's brain waves using amplification means connected to the EEG electrodes to produce an amplified signal output for each EEG electrode; (c) connecting a three-axis translation on the head of the subject to detect the subject's head movements, the accelerator producing at least one reference signal output indicative of the head movements; (d) using an interference canceler to produce corrected EEG signals, the canceler being connected to the output of the amplification means and to the reference signal, the canceler comprising a filter having an input connected to the output of the reference signal and having an output, and an adder connected to the output of the filter and the amplification means, the adder producing corrected and usable EEG signals.
Claim 23
Dependent Claim
150 words
An EEG (electroencephalograph) method comprising the steps of: (a) connecting a plurality of EEG electrodes to the scalp of a subject to detect the subject's brain waves; (b) amplifying the subject's brain waves using amplification means connected to the EEG electrodes to produce an amplified signal output for each EEG electrode; (c) connecting a three-axis translation on the head of the subject to detect the subject's head movements, the accelerator producing at least one reference signal output indicative of the head movements; (d) using an interference canceler to produce corrected EEG signals, the canceler being connected to the output of the amplification means and to the reference signal, the canceler comprising a filter having an input connected to the output of the reference signal and having an output, and an adder connected to the output of the filter and the amplification means, the adder producing corrected and usable EEG signals.
Claim 24
Dependent Claim
36 words
An EEG method as in claim 20 wherein the filter is an adaptive filter executed in an algorithm embodied in a software program executed on a digital computer system or embodied in a digital hardware circuit.
Claim 25
Dependent Claim
29 words
An EEG method as in claim 21 wherein the adaptive filter comprises a filter coefficient matrix which is adjusted with time according to a Least Means Squares (LMS) algorithm.
Claim 26
Dependent Claim
38 words
An EEG method as in claim 21 wherein the adaptive filter comprises a filter coefficient matrix which is adjusted with time according to an Exponentially Weighted Recursive Least Squares (EWRLS) algorithm or a Recursive Least Squares (LRS) algorithm.
Claim 27
Dependent Claim
48 words
An EEG method as in claim 20 wherein the filter comprises a block adaptive filter algorithm selected from the group of autoregressive with external input (ARX), autoregressive and moving average with external input (ARMAX), Wiener filters, Kalman filters, Linear Predictors, autoregressive and moving average (ARMA) and Box-Jenkins model.
Claim 28
Dependent Claim
45 words
An EEG method as in claim 20 and further including the step of generating an eye movement reference signal as an input to the filter, the eye movement reference signal being generated from an eye movement sensor removably connected proximate an eye of the subject.
Claim 29
Dependent Claim
14 words
An EEG method as in claim 20 wherein the filter is a non-adaptive filter.
Claim 30
Dependent Claim
144 words
An EEG (electroencephalograph) method comprising the steps of: (a) connecting a plurality of EEG electrodes to the scalp of a subject to detect the subject's brain waves; (b) analyzing the subject's brain waves using amplification means connected to the EEG electrodes to produce an amplified signal output for each EEG electrode; (c) combining and averaging at least some of the amplified signal outputs and thereby generating a spatial average EEG signal as a head and body reference signal; and (d) using an interference canceler to produce corrected EEG signals, the canceler being connected to the output of the amplification means and to the reference signal, the canceler comprising a filter having an input connected to the reference signal and having an output, and an adder connected to the output of the filter and the amplification means, the adder producing corrected and usable EEG signals.
Claim 31
Dependent Claim
144 words
An EEG (electroencephalograph) method comprising the steps of: (a) connecting a plurality of EEG electrodes to the scalp of a subject to detect the subject's brain waves; (b) analyzing the subject's brain waves using amplification means connected to the EEG electrodes to produce an amplified signal output for each EEG electrode; (c) combining and averaging at least some of the amplified signal outputs and thereby generating a spatial average EEG signal as a head and body reference signal; and (d) using an interference canceler to produce corrected EEG signals, the canceler being connected to the output of the amplification means and to the reference signal, the canceler comprising a filter having an input connected to the reference signal and having an output, and an adder connected to the output of the filter and the amplification means, the adder producing corrected and usable EEG signals.
Claim 32
Dependent Claim
66 words
An EEG method as in claim 27 and further comprising removably connecting an accelerometer or movement detector on the head of the subject to detect head movements, the accelerometer or movement detector generating at least one signal indicative of head movements, using the head movement signal to determine the starting and ending of head movements, and operating the interference canceler only during said determined head movements.
Claim 33
Dependent Claim
26 words
An EEG method as in claim 28 wherein an accelerometer is connected on the head of the subject and the accelerometer is a three-axis translational accelerometer.
Claim 34
Dependent Claim
36 words
An EEG method as in claim 27 wherein the filter is an adaptive filter which is an algorithm embodied in a software program executed on a digital computer system or embodied in a digital hardware circuit.
Claim 35
Dependent Claim
15 words
An EEG method as in claim 27 wherein the filter is an analog hardware circuit.
Claim 36
Dependent Claim
32 words
An EEG method as in claim 27 wherein the filter is an adaptive filter having a filter coefficient matrix which is adjusted with time according to a Least Mean Squares (LMS) algorithm.
Claim 37
Dependent Claim
41 words
An EEG method as in claim 27 wherein the filter is an adaptive filter having a filter coefficient matrix which is adjusted with time according to an Exponentially Weighted Recursive Least Squares (EWRLS) algorithm or a Recursive Least Squares (RLS) algorithm.
Claim 38
Dependent Claim
48 words
An EEG method as in claim 27 wherein the filter uses a block adaptive filter algorithm selected from the group of autoregressive with external input (ARX), autoregressive and moving average with external input (ARMAX), Wiener filters, Kalman filters, Linear Predictors, autoregressive and moving average (ARMA) and Box-Jenkins model.
Claim 39
Dependent Claim
14 words
An EEG method as in claim 27 wherein the filter is a non-adaptive filter.