A method in electroconvulsive therapy (ECT) to use ictal EEG data for clinical determination of the adequacy of an induced seizure in a patient. The method includes employing an ECT device to apply electricity to the patient in an ECT session to induce seizure activity. The electroencephalographic (EEG) data is detected during the seizure and selected EEG data parameters are derived therefrom. Next, the likely adequacy of the induced seizure is computed by comparing the selected EEG data parameters of the patient to ictal EEG data parameters wherein the adequacy of the corresponding seizure or seizures is known, and the computed likely therapeutic adequacy of the induced seizure is displayed.
In medical convulsive therapy (CV), comprising electroconvulsive therapy (ECT) and magnetoconvulsive therapy (MCT), a computer system is used to analyze the effectiveness of the treatment. In one embodiment the effectiveness is determined by measuring the physiological effects on the heart (ECG) muscles (EMG) and brain (EEG).
A system (10) analyzes signals representative of a subject's brain activity in a signal processor (12) for information indicating the subject's current activity state and for predicting a change in the activity state. One preferred embodiment uses a combination of nonlinear filtering methods to perform real-time analysis of the electro-encephalogram (EEG) or electro-corticogram (ECoG) signals from a subject patient for information indicative of or predictive of a seizure, and to complete the needed analysis at least before clinical seizure onset. The preferred system then performs an output task for prevention or abatement of the seizure, or for recording pertinent data.
Disclosed is a multiple electrode, closed-loop, responsive system for the treatment of certain neurological diseases such as epilepsy, migraine headaches and Parkinson's disease. Brain electrodes would be placed in close proximity to the brain or deep within brain tissue. When a neurological event such as the onset of an epileptic seizure occurs, EEG signals from the electrodes are processed by signal conditioning means in a control module that can be placed beneath the patient's scalp, within the patient's chest, or situated externally on the patient. Neurological event detection means in the control module will then cause a response to be generated for stopping the neurological event. The response could be an electrical signal to brain electrodes or to electrodes located remotely in the patient's body. The response could also be the release of medication or the application of a sensory input such as sound, light or mechanical vibration or electrical stimulation of the skin. The response to the neurological event can originate from devices either internal or external to the patient. The system also has the capability for multi-channel recording of EEG related signals that occur both before and after the detection of a neurological event. Programmability of many different operating parameters of the system by means of external equipment provides adaptability for treating patients who manifest different symptoms and who respond differently to the response generated by the system.
A system (10) analyzes signals representative of a subject's brain activity in a signal processor (12) for information indicating the subject's current activity state and for predicting a change in the activity state. One preferred embodiment uses a combination of nonlinear filtering methods to perform real-time analysis of the electro-encephalogram (EEG) or electro-corticogram (ECoG) signals from a subject patient for information indicative of or predictive of a seizure, and to complete the needed analysis at least before clinical seizure onset. The preferred system then performs an output task for prevention or abatement of the seizure, or for recording pertinent data.
A method of judging a biological state comprising using: (1) correlation and/or symmetry between Lyapunov exponent and entropy; and/or (2) Higuchi fractal dimension, wherein the Lyapunov exponent, entropy and Higuchi fractal dimension are indices that can express chaotic nature and derived from time series data of biological signals from a subject.
