Abstract: A method for generating stimulation parameters, an electrical stimulation control apparatus and an electrical stimulation system are provided. After receiving a brainwave signal, the brainwave signal is decomposed to obtain a first sub-signal and a second sub-signal. Then, the first sub-signal is analyzed to obtain an intrinsic frequency series, and the second sub-signal is converted to a Boolean signal. Subsequently, the intrinsic frequency series and the Boolean signal, which serve as a set of stimulation parameters, are outputted to the stimulator, enabling the stimulator to generate a stimulus signal.

Abstract: A method and a system for processing an electroencephalogram (EEG) signal are provided. The method for processing the EEG signal includes: performing a spike detection on the EEG signal to obtain a spike distribution waveform, performing an instantaneous frequency oscillation energy analysis on the EEG signal to obtain multiple energy distribution waveforms; performing a complexity analysis on the EEG signal to obtain a complexity change waveform, obtaining a determination result of a specified neural waveform based on the spike distribution waveform, the energy distribution waveforms, and the complexity change waveform, and outputting the determination result.

Abstract: A method for generating stimulation parameters, an electrical stimulation control apparatus and an electrical stimulation system are provided. After receiving a brainwave signal, the brainwave signal is decomposed to obtain a first sub-signal and a second sub-signal. Then, the first sub-signal is analyzed to obtain an intrinsic frequency series, and the second sub-signal is converted to a Boolean signal. Subsequently, the intrinsic frequency series and the Boolean signal, which serve as a set of stimulation parameters, are outputted to the stimulator, enabling the stimulator to generate a stimulus signal.

Abstract: A method and a system for processing an electroencephalogram (EEG) signal are provided. The method for processing the EEG signal includes: performing a spike detection on the EEG signal to obtain a spike distribution waveform, performing an instantaneous frequency oscillation energy analysis on the EEG signal to obtain multiple energy distribution waveforms; performing a complexity analysis on the EEG signal to obtain a complexity change waveform, obtaining a determination result of a specified neural waveform based on the spike distribution waveform, the energy distribution waveforms, and the complexity change waveform, and outputting the determination result.

Abstract: An electrical stimulation controlling device and an electrical stimulation system are provided. In which, the electrical stimulation controlling device includes a receiving circuit and a controller coupled to the receiving circuit. The receiving circuit is configured to receive an ictal neural signal which is a signal obtained by a detector when a neural event has been occurring. The controller is further coupled to a stimulator and configured to: determine a time point to start an electrical stimulation according to the ictal neural signal after an onset of the neural event has been determined; and generate and transmit a control signal to the stimulator for providing the electrical stimulation according to the determined time point.

Abstract: An electrical stimulation controlling device and an electrical stimulation system are provided. In which, the electrical stimulation controlling device includes a receiving circuit and a controller coupled to the receiving circuit. The receiving circuit is configured to receive an ictal neural signal which is a signal obtained by a detector when a neural event has been occurring. The controller is further coupled to a stimulator and configured to: determine a time point to start an electrical stimulation according to the ictal neural signal after an onset of the neural event has been determined; and generate and transmit a control signal to the stimulator for providing the electrical stimulation according to the determined time point.

Abstract: A method for neurological event detection is provided and include: obtaining a neural oscillation signal and extracting a plurality of features from the neural oscillation signal; obtaining a plurality of classification results corresponding to a plurality of times according to the plurality of features by using a classification model constructed based on a plurality of training data, wherein whether a neurological event occurs is known in each training data; and calculating a final determination result corresponding to each of a plurality of evaluation time windows according to a preset time window width and the plurality of classification results and displaying the final determination result. The final determination result indicates whether the neurological event occurs. Each evaluation time window corresponds to a plurality of classification results and one single final determination result.