13 results about "Bio feedback" patented technology

The invention is suitable for the technical field of biological feedback, and provides a non-invasive feedback method, device, equipment and program product for pelvic floor muscle training. The method comprises the steps that in the pelvic floor muscle training process of a living body, a first electromyographic signal generated by pelvic floor muscle fiber depolarization when the pelvic floor muscle of the living body contracts is obtained through an active electrode arranged on the pelvic floor muscle of the living body; and according to the first electromyographic signal, determining whether pelvic floor muscle training performed by the living body meets a preset requirement or not. According to the method, the electromyographic signal for determining whether the pelvic floor muscle training carried out by the living body meets the preset requirement or not is obtained by the active electrode arranged on the pelvic floor muscle of the living body, and the active electrode can be directly attached to the skin, so that the pelvic floor muscle training effect can be determined without using a vaginal probe; therefore, the effect of pelvic floor muscle training performed by the living body can be determined noninvasively, and the safety and comfort of pelvic floor muscle training are improved.

The invention discloses an intelligent meibomian gland targeted therapy system based on multi-mode biological feedback, which comprises an intelligent thermal therapy module, a targeted drug penetration module, a bionic massage module, a multi-mode monitoring module and an AI central controller, and is characterized in that the AI central controller is electrically connected with the intelligent thermal therapy module, the targeted drug penetration module, the bionic massage module and the multi-mode monitoring module; the control module is used for receiving real-time monitoring data of the multi-mode monitoring module, generating a control instruction, dynamically regulating and controlling heating parameters of the intelligent thermal therapy module, drug delivery parameters of the targeted drug penetration module and massage parameters of the bionic massage module, and forming a closed-loop feedback system based on the thickness of a tear film lipid layer and a gland image; through closed-loop control of the graphene heating film and the infrared temperature sensor, the temperature fluctuation is small, the precision is far better than that of traditional equipment, and the cornea burning risk is thoroughly avoided.

The invention belongs to the technical field of biological equipment testing, and provides a gastrointestinal pacemaker testing method and system based on biofeedback, and the method comprises the steps: carrying out a gastrointestinal stimulation test in a set testing range, continuously collecting physiological signals, judging whether the physiological signals are successfully followed, and if the following is not successful, preliminarily judging that the traction is insufficient; whether functional lag exists or not is judged by comparing the stimulation lag of the gastrointestinal pacemaker with the gastrointestinal rhythm fluctuation period of the subject; the functional lag degree and the traction insufficiency degree of a to-be-analyzed stimulation test are correlated, compared and analyzed, a target correction stimulation test is screened, a dominant frequency following error and an amplitude synchronization degree are corrected, and whether traction of the gastrointestinal pacemaker is sufficient or not is judged again. The problem of misjudgment of the functional traction test of the gastrointestinal pacemaker caused by functional lag interference of the gastrointestinal pacemaker is prevented; and the rapid and effective test of the traction capability of the gastrointestinal pacemaker is realized.

The present disclosure is directed to a bio-feedback sensor in combination with AI and ML that can be implemented to optimize neuromodulation parameters for the management of a medical condition such a type II diabetes. The bio-feedback obtained by the sensors is optimized by the ML tools to predict and recommend the upregulation or downregulating the neuroregulators to modulate treatment. The algorithms could also learn to sense a life-threating pathological state, or bio-chemical imbalance, and in the case of diabetes a life-threating low blood sugar level the system overrides to stimulate the target fibers that control organs to regulate blood glucose levels.

The invention relates to the technical field of intelligent control, and discloses a massage robot intelligent control method and system based on multi-mode biological feedback, and the method comprises the steps: collecting data of different body parts, and carrying out the standardization processing; extracting a fluctuation feature sequence to analyze a change trend; when the change trend exceeds a stable threshold value, calculating a body signal characteristic value and a deviation value between the body signal characteristic value and a normal body data interval, generating a running track, matching hardware response duration, when the response duration exceeds a time limit, adjusting an action sequence, calculating a deviation value between the action sequence and historical data, and if the response duration exceeds an adjustment threshold value, executing the step of executing the step of executing the step of executing the step of executing the step of executing the step. If yes, performing personalized adjustment on the control of the massage robot according to the situation data and the body surface temperature; and adjusting the massage parameters according to the real-time tactile feedback data, generating an adjusted execution instruction, and updating the body data of the user. According to the method, scattered and heterogeneous information of the body state of the user can be integrated into an integral judgment basis, and personalized accurate control is carried out.

A system and method for supporting personal growth and well-being, comprising a mobile application with a user interface providing access to a plurality of evidence-based tools, including gratitude affirmations, manifestation practices, guided meditations, therapeutic hypnosis, breathwork exercises, and sound therapies. The system receives user input selecting one or more tools, stores user progress data, and displays insights derived from the data. Personalized features include a printable electronic gratitude journal, daily Bible verses, and motivational push notifications based on user goals and app interaction data. An artificial intelligence component analyzes user data to generate personalized recommendations for optimizing the user's personal growth journey. A social community feature enables users to connect, share experiences, and participate in group challenges and accountability programs. The invention provides a comprehensive, personalized, and accessible approach to self-improvement using advanced technologies such as biometric feedback.

The application provides an emotion state prediction method and system for the elderly based on multi-modal biological feedback, relates to the technical field of emotion state prediction and guidance for the elderly, and comprises the following steps: firstly, collecting a biological feedback signal sequence of the elderly in a natural life scene; then, constructing a biological feedback signal correlation chain based on a corresponding relationship between historical biological feedback data of the elderly and emotion states; comparing the biological feedback signal sequence with the biological feedback signal correlation chain to generate emotion correlation parameters; generating an emotion state deduction graph after integration; performing growth trend analysis on an evolution correlation path in the emotion state deduction graph; screening out a path with the highest future growth probability and generating an emotion state prediction result; and finally, combining daily preference data of the elderly to generate an emotion guidance scheme containing environmental element adjustment and interactive behavior guidance strategies, so that personalized and accurate guidance measures can be provided according to individual characteristics and emotion states of the elderly.

The invention discloses a self-adaptive regulation and control method and system for rheological parameters of a transdermal drug delivery preparation based on a biological feedback signal. A radial artery pressure waveform is collected, the pH, viscosity and surface tension of a target are calculated by using a deep neural network model, and the precise ratio of A / B / C / D functional media is controlled in a closed-loop manner. On-line viscosity / pH monitoring and feedback correction are introduced into the system, it is ensured that the permeability characteristic of the preparation is highly matched with the individual physiological status (CV is smaller than or equal to 12%), and the industrial problem that the individual difference of the bioavailability of a traditional transdermal drug delivery preparation is large is solved.

The invention discloses a self-adaptive environment control system and method based on multi-mode biological feedback. The system integrates physical sensing and two types of biological sensing, on one hand, an environment-biological coupling model is calibrated in real time through'two-channel self-adaption ', on the other hand, a set point is dynamically adjusted according to a welfare index, and an optimal control sequence is solved through MPC. According to the adaptive environment control method based on multi-modal biological feedback, continuous self-calibration can be achieved under data drift and working condition changes, biological requirements are accurately recognized, temperature, humidity, wind, light, ventilation and other factors are dynamically regulated and controlled, the control precision and energy efficiency are remarkably improved, fluctuation and stress are reduced, growth and output are improved, and the adaptive environment control method based on multi-modal biological feedback is suitable for large-scale popularization and application. The method is suitable for livestock and greenhouses.

The invention belongs to the technical field of medical intelligent auxiliary systems, and particularly relates to a method and a system for data acquisition and biological feedback of marine surgical operators. The physiological data acquisition module and the psychological data acquisition module are used for acquiring psychological and physiological index data of the marine surgical operation personnel in the virtual surgical operation process; a data acquisition and biological feedback system for marine surgical operators comprises a physiological data acquisition module used for acquiring physiological index data of the marine surgical operators in a virtual surgical operation process; the psychological data acquisition module is used for acquiring psychological index data of the operator in the virtual surgery operation process; according to the scheme, mixed reality, multi-source sensing, data fusion analysis and intelligent feedback technologies are integrated, so that the operation stability and the emergency disposal capability of operation workers are improved, and technical support is provided for marine operation safety.

The invention provides a multi-mode awakening control closed-loop biological feedback system and method and a medium, and relates to the field of biological signal processing and human-computer interaction control, and the system comprises a signal collection module which is used for collecting pupil features and HRV features, and detecting illumination intensity; the signal preprocessing module is used for filtering the pupil features, removing artifacts and normalizing illumination; the awakening index calculation module is used for calculating a unified awakening index PAI based on pupil feature and HRV feature fusion; the control law module is used for generating a feedback instruction by adopting a predictive control strategy of dual-threshold hysteresis and time delay compensation based on the deviation between the unified awakening index PAI and a preset target interval; and the multi-mode feedback execution module is used for outputting visual, auditory and tactile feedback according to the feedback instruction. The problems that in the prior art, due to the fact that physiological delay exists due to the influence of visual stimulation on the awakening level, oscillation of the awakening level is caused, and meanwhile regulation and control instability is further aggravated due to the fact that a single pupil signal is prone to being interfered can be solved.

The invention relates to the technical field of biological feedback correction, and provides a three-dimensional spiral biological feedback correction chair, which comprises a use structure: the use structure is coaxially mounted in the middle of the front end of a correction structure; the correcting structure comprises a base, a fixing frame, an adjusting rod and a seat; the fixing frame is fixedly connected to the two sides and the rear portion of the base, the adjusting rod is fixedly connected to the middle of the top end of the base, and the seat is fixedly connected to the top end of the adjusting rod. And the using structure comprises an empty groove and a spring rod. By arranging a using structure and through auxiliary cooperation between an empty groove and a cushion, when a patient sits on the seat, the cushion can be extruded by the hip of the patient, so that a sleeve slides down along the track of a spring rod and extrudes a first pressure sensor, and when the patient sits on the seat and waits for correction, the cushion can be extruded by the hip of the patient; the correction chair can be automatically started to work, the hands of workers are liberated, and meanwhile the workload of the workers is relieved.

The invention discloses a scoliosis active training method and system based on biological feedback, and relates to the field of scoliosis training.The method comprises the steps that firstly, through a personalized baseline calibration stage, an exclusive initial median frequency, a standard action IMU template and a personalized fatigue threshold value are established for each user; in a training stage, multi-modal synchronous analysis is performed on sEMG and IMU data, and a median frequency fatigue index reflecting a muscle fatigue degree and an action deviation degree reflecting attitude accuracy are calculated in real time. Finally, a decision engine combines the two indexes and a personalized threshold value for judgment, and accurate and real-time early warning of muscle fatigue and motion deformation is achieved. According to the scheme, by establishing the personalized model and fusing the myoelectricity and posture information, the problem that fatigue and action quality cannot be monitored simultaneously in dynamic training in the prior art is solved, and the training safety and effectiveness are remarkably improved.