5910results about "Electrotherapy" patented technology

A system and method for maintaining an oxygen concentration of a biological sample. The oxygen concentration can be maintained by measuring the oxygen concentration within the biological sample and adjusting a rate of an oxygen supplier in response to this measurement. For example, when the oxygen concentration is below a threshold, oxygen can be delivered to the biological sample at a higher rate.

Systems and methods herein generally relate to prolonging viability of bodily tissue, especially an organ, by adjusting pressure as needed to maintain a constant pressure within the organ even during external pressure fluctuations due, for example, to transportation of the organ in an airplane. The systems and methods herein can include an electronic pump that pumps gas into an organ and a mechanical pressure regulator to release gas based on organ pressure.

The invention discloses an intelligent management system and method applied to a radio frequency energy output device, and belongs to the technical field of intelligent management of the radio frequency energy output device.An integrated sensor array is deployed on a radio frequency host and a hand tool electrode, and load voltage, output current, electrode temperature and tissue impedance are synchronously collected; a dynamic thermal impedance collaborative analysis model is constructed after time synchronization alignment, a three-dimensional thermal field simulation map is generated, and a thermal accumulation trend is predicted; a double-layer control framework is constructed, a first control layer generates a dynamic power adjustment rule base based on a preset treatment target and a safety threshold value and outputs an instruction, a second control layer receives the instruction and adjusts output parameters in real time, and a strategy is adjusted by combining a model prediction result in the execution process; meanwhile, the operation state is continuously monitored, a fault classification model is constructed for anomaly detection, a fault source is positioned, and a visual report is generated; and finally, constructing a mapping relation based on historical data, and generating an energy control scheme adapted to individualized requirements through iterative optimization.

The invention discloses a sleep monitoring and intervention method and system based on electroencephalogram signals, and belongs to the technical field of sleep monitoring and intervention. The method comprises the steps that electroencephalogram signals are collected through a dry electrode worn on the head of a user; the signals are preprocessed; performing automatic sleep staging on the pre-processed signal based on a layered space-time joint modeling network, and outputting a waking period label, an N1 period label, an N2 period label, an N3 period label and an REM period label; whether intervention conditions are met or not is judged based on the staging labels and the real-time electroencephalogram spectrum features; and if yes, generating and applying an alternating current stimulation signal for intervention. The system comprises a wearable electroencephalogram acquisition device, a signal analysis module and an intervention module. According to the method, the deep learning model integrating front-end self-adaptive processing, the graph neural network and Transform is adopted for sleep staging, closed-loop phase synchronous stimulation driven by the digital phase-locked loop is combined on the basis, connection from sleep monitoring to closed-loop intervention is achieved, and the sleep monitoring accuracy and the intervention effect are effectively improved.

The invention belongs to the technical field of brain-computer interfaces, and particularly relates to a brain-computer interface driven emotion recognition and self-adaptive regulation and control system which comprises a multichannel nerve-peripheral coupling module, an emotion intensity probability mapping module and a closed-loop nerve regulation and control current module. The multi-channel nerve-peripheral coupling module is used for realizing overall quantification of central and peripheral emotional physiology; the emotion intensity probability mapping module is used for generating continuous emotion probabilities ranging from 0 to 1 through normalization and nonlinear mapping by utilizing emotion energy and combining eye movement fatigue and electroencephalogram entropy; and the closed-loop nerve regulation and control current module is used for dynamically adjusting the transcranial electrical stimulation intensity within the safety current upper limit according to the difference value between the emotion probability and the expected target. According to the invention, the recognition precision, the response speed and the use comfort are obviously improved.

The invention relates to the technical field of biomedicine, and discloses a female private rehabilitation training system integrating a breathing method and neural motor control, and the system comprises a data collection module which is used for collecting physiological data of a user; the personalized training scheme generation module is used for generating a personalized nerve-muscle-fascia training scheme; the nerve-muscle synchronous resonance training module is used for constructing a time sequence matching model and generating an adaptive training dynamic control instruction; the space-time adaptability training module is used for adjusting training duration, intensity and stimulation frequency; the multi-dimensional nerve-muscle feedback fusion module is used for constructing a feedback response model; and the fascia synchronous activation and relaxation module is used for coordinating the tension relationship between the fascia and the muscle system. According to the method, feature matching is carried out on an electric activation heat map matrix through the convolutional neural network, analysis of a myoelectricity response state transition probability is carried out in combination with a hidden Markov model, and stimulation parameters and respiratory rhythm are optimized in real time according to a training process.

The present application pertains to the technical field of neural stimulation. Disclosed are a temporal interference-based closed-loop multimodal neural stimulation system and method. The system comprises a temporal interference stimulation system, an electroencephalography-functional near-infrared spectroscopy sampling system, and an upper-level control system. The temporal interference stimulation system utilizes a beat-frequency electric field generated by two sets of electrodes to precisely stimulate a specified brain region. The electroencephalography-functional near-infrared spectroscopy sampling system is a bimodal collector coupling electroencephalography and functional near-infrared spectroscopy, including two parts: signal extraction and correlation analysis, and analyzes stimulation effects and adjusts stimulation schemes by integrating unified brain signal data that combines the temporal precision of EEG and the spatial precision of fNIRS. The upper-level control system includes bimodal fusion model computation, graph convolutional neural network prediction, and stimulation scheme formulation. The present application addresses the problems that traditional stimulation methods lack a closed-loop regulation system, have no means for calibration and optimization, and require a long adaptation period between the stimulation scheme and the user, thus being disadvantageous for applications.

A neuromodulation system including at least one input module for inputting a planned neuromodulation event or a series of neuromodulation events and at least one analyzing module for analyzing a neuromodulation event or a series of neuromodulation events.The analyzing module and the input module may be connected such that the input module is configured to forward the planned neuromodulation event or a series of neuromodulation events to the analyzing module and the analyzing module is configured to analyze the planned neuromodulation event or a series of neuromodulation events regarding one or more possible neuromodulation conflict(s).

The invention belongs to the technical field of nerve regulation and control, and discloses a portable noninvasive brain deep electrical stimulation system based on time interference, and the system comprises an electroencephalogram signal collection unit which is used for obtaining an electroencephalogram signal in a high-quality resting state, and carrying out the signal preprocessing and feature extraction, thereby obtaining an optimal stimulation envelope frequency; the personalized finite element modeling unit is used for constructing a head personalized model and outputting optimal electrode configuration and stimulation parameters for a target brain region target spot; the electrode positioning and stimulation execution unit is used for realizing accurate positioning of an electrode position and implementing time interference electrical stimulation; the MCU unit is used for realizing data management, task scheduling and remote communication; the human-computer interaction unit is used for realizing visual treatment flow and parameter setting; and the power supply management unit provides stable working voltage for the system. According to the invention, the portable, intelligent and personalized modeling of the electrical stimulation treatment equipment is realized, and the precision and efficiency of nerve regulation and control are remarkably improved.

A digital healthcare architecture including a cloud-based virtual clinic platform configured to facilitate remote therapy of one or more patients based on biometric authentication systems and methods. In an example arrangement, one or more biometric indicia of a user (e.g., a clinician and / or a patient) as well as one or more non-biometric input factors may be used in authenticating the user prior to granting access to a protected resource or application (e.g., a therapy application executing on a UE device) configured for effectuating remote programming of an implantable medical device (IMD) operative to provide therapy to the patient.

The invention provides a transcranial stimulation magnetic therapy closed-loop control method and system, and the method comprises the steps: determining a multi-modal physiological signal of a user, the multi-modal physiological signal at least comprising an electroencephalogram signal, an autonomic nerve physiological signal and a subjective feedback signal; constructing an individual dynamic baseline spectrum based on user multi-state data collected before treatment; the method comprises the following steps: preprocessing a multi-modal physiological signal collected in a treatment process, and extracting a real-time feature vector; calculating a comprehensive deviation index of the real-time feature vector and the individual dynamic baseline spectrum, and determining a deviation type based on the comprehensive deviation index; the adjustment amount of transcranial magnetic stimulation parameters is dynamically calculated according to the deviation type, the individual response characteristics and the historical treatment data, stimulation operation is conducted according to the adjustment amount of the transcranial magnetic stimulation parameters, and the transcranial magnetic stimulation parameters at least comprise the stimulation frequency, the intensity, the pulse width and the stimulation duration. Parameters of transcranial magnetic stimulation are adaptively changed according to changes of neuron oscillation of a patient in the treatment process.

The invention belongs to the technical field of medical electronic equipment, and discloses a control system for alternative electrical stimulation of idiopathic tremor, and the system comprises a signal collection module which is used for obtaining tremor motion data of a patient in real time; the signal processing module is used for analyzing tremor frequency, amplitude and phase characteristics; the dynamic parameter generation module is used for generating an alternate stimulation mode according to the tremor characteristics; and the electrode array module comprises at least two stimulating electrodes and a reference electrode. The invention provides a non-invasive and dynamically optimized alternate electrical stimulation control system which is used for inhibiting hand tremor of an idiopathic tremor patient, regulation and control of a tremor network can be enhanced by alternately stimulating different peripheral nerves, the curative effect can be improved through closed-loop feedback optimization parameters, long-acting and safe tremor inhibition is achieved, and the treatment effect is improved. The problems of insufficient curative effect, nerve adaptability, surgical risk and the like in the prior art are solved.

The invention discloses an electrical stimulation type nerve regeneration method based on calcium signal regulation and control, and relates to the technical field of electrical stimulation type nerve regeneration, and the method comprises the following steps: based on a Schwann cell population calcium signal response feature set, identifying whether the calcium ion concentration is in a microliter stage which breaks through a lowest activation threshold and does not reach a stable state; judging whether the target nervous tissue is in a calcium signal activation critical state or not based on the behavior mode change of the Schwann cell population; based on the judgment result of the calcium signal activation critical state, an electrical stimulation adjustment control instruction is generated in real time in combination with the calcium ion concentration fluctuation trend and Schwann cell population response characteristics, and the calcium ion concentration stability is optimized and the activation state is maintained by adjusting the electrical stimulation intensity, the electrical stimulation pulse width, the electrical stimulation waveform type and the electrical stimulation application time sequence. According to the method, the problem that a calcium signal is difficult to recognize and dynamically optimize in a microliter stage is solved, and precise maintenance of Schwann cell activation and improvement of nerve regeneration efficiency are realized.

The invention relates to a transcranial magnetic stimulation high-precision positioning method, device and equipment based on optical navigation. Comprising the steps of selecting non-coplanar reference points based on a three-dimensional brain model of a patient, obtaining image coordinates and physical coordinates of all the reference points, carrying out corresponding point matching through the image coordinates and the physical coordinates, calculating and generating an optimal rigid transformation matrix, carrying out target registration error calculation, and realizing registration of an image coordinate system and a physical coordinate system. And according to the registered brain tissue conductivity parameters, calculating electric field space distribution induced by the transcranial magnetic stimulation coil in a target brain area, dynamically correcting stimulation target point coordinates of the virtual coil, and according to a completed coordinate system registration result, dynamically displaying the position and direction of the virtual coil corresponding to the transcranial magnetic stimulation coil on the three-dimensional brain model. And synchronously updating the brain slice view based on the corrected target point coordinates, and highlighting the actually stimulated brain region boundary. According to the method, adaptive neural navigation is driven through electric field remapping, and compensation target point correction is achieved.

The utility model discloses a tumor electric field treatment device and a treatment system, the tumor electric field treatment device is provided with a frame body and a pole piece module, the frame body forms a skeleton structure of the treatment device, the pole piece module is attached to the frame body, the pole piece module is provided with a plurality of electrode contacts, and each electrode contact can form an active contact or a passive contact. The active contact and the radio frequency generation module can form a loop; after the treatment device is implanted into a tumor excision part, all the electrode contacts form active contacts, and all the electrode contacts and the radio frequency generation module form a loop to distinguish normal tissues from pathological tissues; after the normal tissue and the lesion tissue are distinguished, the electrode contacts in the normal tissue area form passive contacts, and the electrode contacts in the lesion tissue area form active contacts, so that targeted treatment of the lesion tissue is realized, and side effects generated by electric field treatment are reduced.

The invention relates to the field of medical instruments, and discloses an anesthesia injury monitoring evaluation and management system for pain monitoring and rehabilitation acceleration. Comprising a sensor module configured to collect acupuncture point skin temperature data in a percutaneous acupuncture point electrical stimulation process, current parameter data output by an electrical stimulation device and skin impedance change data in real time; the control module is used for inputting the temperature data, the current parameter data and the skin impedance data which are acquired in real time into a multi-parameter risk assessment model, calculating a real-time risk value and generating a parameter change curve containing a time sequence; when the real-time risk value exceeds a preset safety threshold value, or any single parameter in the parameter change curve reaches a temperature change rate threshold value, an accumulated electrical stimulation energy threshold value or a skin impedance abnormal fluctuation threshold value, triggering a multi-stage early warning signal; according to the early warning level of the early warning module, the output power, the pulse frequency or the action time of the electrical stimulation device is automatically adjusted, or electrical stimulation is forcibly terminated when early warning is performed at the highest level.

Wearable modular mask systems for combination face and skincare diagnostics and therapeutics. Systems include devices that can be attached to wearable masks for diagnosis and treatment of skin conditions, diseases, and disorders, as well as for cosmetic improvements to the skin of the face and scalp.

The invention discloses a transcranial magnetic navigation and curative effect evaluation system based on electroencephalogram power spectrum analysis, particularly relates to the technical field of electroencephalogram signal processing, and is used for solving the technical problem that existing transcranial magnetic stimulation treatment lacks interference evaluation and stimulation path optimization on a cortical collaborative area. According to the method, electroencephalogram signals of a testee in a resting state and a task state are collected, phase-amplitude coupling indexes between frequency bands are extracted, a frequency-crossing coupling matrix is constructed, a nested chain structure with modulation direction consistency is identified, a stable resonance channel group is extracted from a channel intersection set to form a collaborative active region, and the collaborative active region is constructed. And after mapping to a standard brain map, carrying out space matching with a TMS target spot, evaluating an interference risk level, formulating a stimulation avoidance strategy, recording side reactions during treatment, and constructing a curative effect scoring window in a normalization manner, so as to realize synchronous optimization of stimulation planning and curative effect evaluation.

The invention provides an electronic acupuncture closed-loop control method and system based on multi-modal information feedback. The method comprises the following steps: acquiring long-term, short-term and real-time representation information of a testee under an initial stimulation scheme; the long-term and short-term characterization information is input into a collaborative generative network model for learning, a target stimulation scheme is output, the collaborative generative network model comprises traditional Chinese and western medicine agents, the traditional Chinese and western medicine agents learn the long-term and short-term characterization information, and a corresponding traditional Chinese medicine treatment scheme and an electrical stimulation scheme are output. The collaborative generation network model carries out collaborative training on traditional Chinese and western medicine agents; calculating an index deviation between the real-time characterization information and the standard characterization information to generate a real-time information deviation matrix; inputting the target electrical stimulation scheme and the real-time information deviation matrix into a parameter deviation prediction agent for learning and prediction; and performing parameter adjustment on the target stimulation scheme based on the predicted stimulation parameter deviation matrix to realize long / short time and real-time double-layer closed-loop control of the electronic acupuncture.

Systems, devices, and methods described herein relate to generation and delivery of pulsed waveforms, e.g., for therapy delivery in soft tissue ablation procedures. In some embodiments, a pulse generator is configured to generate a voltage pulse train including a plurality of biphasic pulses, each biphasic pulse of the plurality of biphasic pulses including a positive pulse, a negative pulse, and an inter-phase delay separating the positive pulse and the negative pulse. In some embodiments, successive biphasic pulses of the plurality of biphasic pulses can be separated by a pulse-to-pulse delay such that the plurality of biphasic pulses is separated by a plurality of pulse-to-pulse delays, and the plurality of pulse-to-pulse delays can include increasing or decreasing sequences of pulse-to-pulse delays.

A mobility augmentation system monitors a user's motor intent data and augments the user's mobility based on the monitored motor intent data. A machine-learned model is trained to identify an intended movement based on the monitored motor intent data. The machine-learned model may be trained based on generalized or specific motor intent data (e.g., user-specific motor intent data). A machine-learned model initially trained on generalized motor intent data may be re-trained on user-specific motor intent data such that the machine-learned model is optimized to the movements of the user. The system uses the machine-learned model to identify a difference between the user's monitored movement and target movement signals. Based on the identified difference, the system determines actuation signals to augment the user's movement. The actuation signals determined can be an adjustment to a currently applied actuation such that the system optimizes the actuation strategy during application.

The invention relates to the technical field of neuroscience and medical treatment, in particular to an individual head model dynamic optimization method and system based on transcranial alternating current stimulation. According to the method, the three-dimensional initial individual head model is partitioned, the parameters are set, the real-time electrical stimulation parameters and the real-time electroencephalogram information of the individual head under the stimulation effect are synchronously obtained, and then the parameters of the initial head model are adjusted according to the real-time data; then, according to the obtained data, simulating and calculating electrophysiological change data of the three-dimensional initial individual head model under the action of initial transcranial alternating current stimulation, and based on a focusing index value and a uniformity index value calculated through the electrophysiological change data, optimizing dynamically-adjusted head model parameters, and finally, calculating a focus index value and a uniformity index value of the three-dimensional initial individual head model under the action of initial transcranial alternating current stimulation. The information entropy difference value obtained through calculation of the optimized head model parameters and the real-time electroencephalogram information is compared with a preset difference threshold value, a clear termination condition is provided for optimization of the head model parameters, and therefore dynamic optimization of the individual head model is achieved.

The invention relates to the technical field of electric acupuncture apparatuses, and discloses a method and a system for automatically adjusting stimulation parameters of an electric acupuncture apparatus. According to the method, body surface electromyographic signals, skin impedance and capillary hemodynamic parameters of a user are collected in real time through a sensor set, feature extraction and analysis are conducted through a time sequence prediction model of a Transform architecture, and physiological feature data are generated. And then, constructing a user physiological state characterization model by adopting a multi-modal neural perception fusion algorithm, and carrying out collaborative optimization on the electrical stimulation parameters through an adaptive quantum particle swarm optimization algorithm to generate a stimulation parameter combination matched with the real-time neuromuscular response characteristics of the user. The system drives electrical stimulation output according to the parameter combination, monitors physiological data changes in real time, realizes closed-loop dynamic balance of stimulation parameters and biological feedback signals through the dynamic parameter compensation module, and improves the treatment effect and safety.

Methods and apparatus for changing a brain state of a person from an initial brain state to a target brain state are described. The method includes receiving information characterizing the initial brain state, the information including a structural composition and a functional architecture of the brain, estimating based, at least in part, on the received information, a potential for the brain to change from the initial brain state to the target brain state, determining based, at least in part, on the received information and the estimated potential for the brain to change from the initial brain state to the target brain state, a non-invasive brain stimulation protocol, and controlling at least one non-invasive brain stimulation device to stimulate the brain according to the non-invasive brain stimulation protocol. The method also includes using brain information to inform the design of computational general artificial intelligence agents.

The invention provides a transcranial deep electrical stimulation closed-loop regulation and control system and method based on fNIRS dynamic guidance. The method comprises the steps that a transcranial alternating current electrical stimulation module applies an electrical signal to a target deep brain region according to preset parameters to carry out electrical stimulation regulation and control; the synchronous triggering module is used for realizing millisecond-level synchronization of a stimulation task and near-infrared brain function data acquisition; the brain function monitoring module analyzes the concentration change of cortex oxyhemoglobin in real time through the multi-channel head cap; the electrical stimulation-response coupling mapping module positions a significant activation channel by adopting statistical test, and establishes an oxyhemoglobin concentration variable and electrical stimulation current amplitude quantitative model; and the dynamic parameter adjusting module optimizes the output current in real time. Personalized closed-loop regulation and control of non-invasive deep brain stimulation can be achieved, cerebral cortex blood oxygen signals are monitored in real time through near-infrared brain function imaging, stimulation parameters are dynamically adjusted, and the accuracy and individualization level of deep brain stimulation are remarkably improved.