6 results about "Stimulus control" patented technology

Disclosed is a neurostimulation system and method. A control unit controls a stimulus source to deliver neural stimuli via selected electrodes to a neural pathway according to a stimulus intensity parameter. An external computing device in communication with the neurostimulation device comprises a display and processor. The processor initialises the stimulus intensity parameter, and renders on the display a stimulation control and a graphical element adjacent the stimulation control. Upon user activation of the stimulation control, the processor ramps a value of the stimulus intensity parameter, while instructing the control unit to cause delivery of stimuli according to the ramping value of the stimulus intensity parameter. Upon user deactivation of the stimulation control, the processor ceases ramping the value of the stimulus intensity parameter. The graphical element is configured to dynamically indicate the ramping value of the stimulus intensity parameter; and indicate a discomfort threshold for the selected electrodes.

An arousal state control system includes a sensor, a stimulation control unit, and a stimulator. The sensor acquires biological information of a user. The stimulation control unit determines, based on the biological information, one or more types of stimuli to control a state of arousal of the user. The stimulator applies the one or more types of stimuli determined by the stimulation control unit to the user.

Computer implemented method for selecting emotional stimuli control (X) among emotional stimuli candidates (V,S,N) for a group of individuals to be used in signal denoising to isolate the true cerebral signal, wherein the method comprises the following sequence of steps: determining fNIRS related superficial signals (LS,RS) and neural signals (NS) for each of the individual of the group subject to emotional stimuli candidates; calculating a superficial signal group response (SGR) and a neural signal group response (NGR) for each emotional stimuli candidate, and the significance (A,B) of each group responses; and selecting as an emotional stimuli control (X) for the group an emotional stimuli that does have a significance (A) superficial signal group response (SGR), and has a no-significance (B) corresponding neural signal group response (NGR). Also a data processing apparatus, a computer program and a computer-readable storage medium, related to the computer implemented method are disclosed.

This application relates to a neural modulation method, system, and medium for controlling premature ejaculation based on multimodal biosensing and AI algorithms, belonging to the field of communication stimulation control technology. The neural modulation method for controlling premature ejaculation includes: monitoring and collecting and processing different physiological activities of the human perineum to obtain multidimensional physiological response signal clusters; calculating the comprehensive arousal level based on historical multidimensional physiological signals and a preset physical pattern, and constructing an arousal curve model; identifying and judging the multidimensional physiological response signal clusters based on the arousal curve model, determining the type of arousal node, and matching behavioral intervention strategies; updating and optimizing the arousal curve model based on active behavioral actions and implicit feedback mechanisms; and by monitoring the user's biophysiological signals in real time, using AI algorithms to analyze the trend of arousal changes, and performing physical intervention through electrical stimulation at key nodes, thereby reducing sensitivity, delaying the ejaculation threshold, and achieving the goal of prolonging sexual intercourse time.

The invention discloses a physiological signal driven stimulation determination and adjustment system and method and a storage medium, and the method comprises the steps: receiving a stimulation control signal through a stimulation signal application module, and applying a target stimulation signal to a target object according to the stimulation control signal; acquiring a plurality of first physiological signals of the target object before the target stimulation signal is applied and a plurality of second physiological signals of the target object after the target stimulation signal is applied through a physiological signal acquisition module; determining an effect evaluation model corresponding to the physiological signals through a stimulation effect determination module, inputting the first physiological signal and the second physiological signal into the effect evaluation model to determine a first effect score of the target stimulation signal, and determining a stimulation effect grade according to the first effect score; the stimulation effect level is obtained through the stimulation signal adjusting module, the target stimulation signal is adjusted according to the stimulation effect level, personalized and self-adaptive accurate intervention is achieved, and therefore the treatment effectiveness and safety are remarkably improved.

The application discloses a mechanical arm grabbing method based on stimulus control adaptive updating, which can be used for matching a steady-state visual evoked potential (SSVEP) based rehabilitation auxiliary brain-computer interface system for different application requirements. The method process is as follows: a mask region model for the task is obtained by training a self-built data set, target recognition and mask segmentation of the experimental scene image are carried out by using the mask region model, the classification, the bounding box and the mask of the object in the image are obtained, adaptive frequency and phase distribution are carried out based on the same, the stimulus control is updated in real time, the user induces the SSVEP signal by staring at the corresponding stimulus control of the target object, the recognition result is intuitively fed back to the user through display mask and the like after classification analysis, and the mechanical arm is controlled to assist the user to complete the grabbing and the like.