Systems and methods for seizure detection using compression-enabled joint entropy estimation
AssigneeThe Board of Trustees of the Leland Stanford Junior University
InventorsPaul Nuyujukian, Lisa Yamada
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Abstract
Systems and methods for seizure detection in accordance with embodiments of the invention are illustrated. One embodiment includes an automated seizure treatment system, including an electroencephalogram (EEG) device configured to record neural activity from a brain of a patient, a treatment device, a processor, and a memory, the memory containing a seizure detection application that configures the processor to obtain an EEG signal from the EEG device, calculate an inverse compression ratio based on the EEG signal, and when the inverse compression ratio is greater than a classification threshold, deliver treatment capable of stopping the seizure to the patient using the treatment device.
Claims18
An automated seizure treatment system, comprising:
- an electroencephalogram (EEG) device configured to record neural activity from a brain of a patient;
- a treatment device;
- a processor;
- and
- a memory, the memory containing a seizure detection application that configures the processor to:
- obtain an EEG signal from the EEG device;
- calculate an inverse compression ratio based on the EEG signal, wherein calculating the inverse compression ratio comprises:
- measuring an uncompressed size of the EEG signal;
- compressing the EEG signal using a lossless compression algorithm;
- measuring a compressed size of the EEG signal;
- and
- dividing the compressed size by the uncompressed size;
- and
- when the inverse compression ratio is greater than a classification threshold, automatically deliver treatment capable of stopping the seizure to the patient using the treatment device.
An automated seizure treatment method, comprising:
- obtaining an electroencephalogram (EEG) signal from an EEG device configured to record neural activity from a brain of a patient;
- calculating, using a processor, an inverse compression ratio based on the EEG signal using a seizure detector, wherein calculating the inverse compression ratio comprises:
- measuring an uncompressed size of the EEG signal;
- compressing the EEG signal using a lossless compression algorithm;
- measuring a compressed size of the EEG signal;
- and
- dividing the compressed size by the uncompressed size;
- and
- when the inverse compression ratio is greater than a classification threshold, automatically delivering treatment capable of stopping the seizure to the patient using the treatment device.
Dependencies are inferred from the claim text.