Method and apparatus for the evaluation of EEG data
AssigneeSiemens Aktiengesellschaft
InventorsIna Pichlmayr, Olaf Eckert
Life of this patent
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Abstract
A method for the evaluation of EEG data for medical purposes includes the steps of acquiring EEG data, recognizing artifacts and determining an output data value with a neural network. In a training method for a neural network, training vectors are determined to which a respective data value is allocated, the neural network is trained with these training vectors, and an output data value is determined for each neuron that is based on the allocated data values of those training vectors that are contained in the data cluster represented by the neuron. A processing apparatus and an EEG monitor are configured for implementing the evaluation method for EEG data.
Claims24
A method for evaluating EEG data for medical purposes, comprising the steps of:
- (a) acquiring EEG data from a patient and editing said EEG data to produce edited EEG data;
- (b) identifying any sections of said EEG data falsified by artifacts and producing artifact information relating thereto;
- (c) calculating a feature vector from the edited EEG data and from said artifact information;
- (d) determining an initial data value in a neural network by allocating said feature vector to a data cluster represented by a neuron of said neural network, said initial data value being allocated to said data cluster;
- and
- (e) producing an output data value from said initial data value and displaying said output data value.
A method for training neural network for evaluating EEG data for medical purposes, comprising the steps of:
- (a) determining a plurality of training vectors, each training vector having a data value allocated thereto;
- (b) determining initial parameters of a neural network;
- (c) conducting a training algorithm on said neural network including modifying said parameters of said neural network for allocating one neuron of said neural network to each cluster of training vectors;
- and
- (d) determining an output data value for each neuron dependent on the respective data values for all training vectors that are contained in the cluster of training vectors allocated to that neuron.
A processor for training neural network for evaluating EEG data for medical purposes, comprising:
- means for determining a plurality of training vectors, each training vector having a data value allocated thereto;
- means for determining initial parameters of a neural network;
- means for conducting a training algorithm on said neural network including modifying said parameters of said neural network for allocating one neuron of said neural network to each cluster of training vectors;
- and
- means for determining an output data value for each neuron dependent on the respective data values for all training vectors that are contained in the cluster of training vectors allocated to that neuron.
An EEG apparatus comprising:
- means for acquiring EEG data from a patient and editing said EEG data to produce edited EEG data;
- means for identifying any sections of said EEG data falsified by artifacts and producing artifact information relating thereto;
- means for calculating a feature vector from the edited EEG data and from said artifact information;
- means for determining an initial data value in a neural network by allocating said feature vector to a data cluster represented by a neuron of said neural network, said initial data value being allocated to said data cluster;
- and
- means for producing an output data value from said initial data value and displaying said output data value.
Dependencies are inferred from the claim text.