63 results about "Physiological motion" patented technology

The invention discloses a personalized rehabilitation training method based on state monitoring, and particularly relates to the technical field of intelligent medical treatment. According to the method, the technical problems of insufficient individuation, poor safety, limited effect and the like caused by single monitoring dimension, lagging adjustment strategy and lack of self-optimization capability in the existing rehabilitation training are solved. According to the scheme, physiological, motion and subjective multi-dimensional data of a patient are synchronously collected through a multi-source sensor and input into a machine learning model for real-time state evaluation after fusion processing, a personalized training scheme is generated and executed accordingly, meanwhile, parameters are dynamically adjusted according to real-time monitoring data in training, and the training efficiency is improved. And the model and the strategy are optimized by analyzing historical data after the period is ended. According to the invention, safe, accurate and self-adaptive evolution personalized rehabilitation training is realized, and the safety, adaptability and rehabilitation effect of training are improved.

The invention discloses a psychotherapy and healing robot based on high human emotion fitting degree simulation analysis, and the robot comprises a multi-mode perception layer which is used for collecting the interaction data of physiology, movement and environment; the multi-modal sensing layer comprises a heterogeneous data acquisition module, a spatial-temporal feature extraction network and an attention fusion mechanism module; the dynamic decision-making layer is used for generating an intervention strategy based on the interaction data; the dynamic decision-making layer comprises a reinforcement learning strategy engine and a hierarchical intervention selection tree; the generative interaction layer is used for generating a co-estrus response conforming to ethical specifications based on the intervention strategy; the generative interaction layer comprises an ethical constraint system and an emotional response generator; the brain science verification layer is used for monitoring neural feedback in real time through EEG and adjusting an intervention strategy; and the brain science verification layer comprises a neural feedback regulation module and a multi-mode feedback design module. Therefore, a precise and personalized psychological intervention decision closed loop is provided, and the defects of an existing AI psychological product in the aspects of emotion recognition, intervention strategies and effect quantification are overcome.

The invention discloses a control method, system and equipment of an intelligent throat surgical robot and a medium. According to the scheme, a three-dimensional tissue model is constructed according to visual image data, laser imaging data and tomography image data; determining lesion data according to the historical lesion data and the tomography image data, superposing the lesion data and the three-dimensional tissue model, and determining a target operation model; determining prediction trajectory data according to the tomography image data and the physiological motion data; planning a path according to the predicted trajectory data, the target operation model and the constraint condition, and controlling the operation robot to perform an operation according to the planned path; through multi-modal data fusion, a three-dimensional tissue model is established to improve the surgical accuracy; the data are analyzed to determine the lesion direction, the motion trail of the organ tissue is predicted, the three-dimensional tissue model is integrated for path planning, the interference of physiological activities of the organ tissue on the operation is avoided, and the safety of the operation is improved. The embodiment of the invention can be widely applied to the field of intelligent robots.

The invention relates to the technical field of image enhancement, in particular to a throat structure and detail high-resolution image enhancement method based on deep learning. The method comprises the following steps: acquiring a low-resolution image of a laryngeal endoscope and corresponding laryngeal three-dimensional image data; the method comprises the following steps: extracting features from a low-resolution image based on a ResNet model, extracting features from three-dimensional image data by using a 3D-ResNet model, constructing a time-varying weight matrix modulated by a sine period in the 3D-ResNet model, so that the physiological motion state of the throat can be perceived in real time in an image enhancement process, and fusing the extracted features by using a cross-scale feature pyramid technology; and a U-Net + + model combined with a sub-pixel convolutional layer is utilized to carry out super-resolution reconstruction on the image subjected to feature fusion processing. According to the design, by introducing an anatomical attention module and a dynamic receptive field adjustment technology, the characteristics of clinical key areas (such as vocal cord free edges and anterior joint areas) can be enhanced in a targeted manner.

The invention discloses a personalized physical training load intelligent regulation and control system based on multi-modal physiological data fusion, and relates to the technical field of intelligent physical training and health monitoring. The system comprises a multi-modal data acquisition module, an intelligent fusion analysis module, a personalized decision module and a real-time regulation and control module. The method comprises the following steps: acquiring physiological, motion and environmental parameters of a user, and performing multi-modal data fusion by using a time sequence-causal attention mechanism to generate a comprehensive physiological state feature vector; a dynamic personalized baseline is established based on a meta-learning framework, a load adjustment decision is generated by adopting a hierarchical reinforcement learning algorithm, and regulation and control safety is ensured through causal reasoning verification; and finally, load adjustment is executed through the real-time regulation and control module to form closed-loop control. According to the method, the problems that in the prior art, training load regulation depends on a single physiological parameter, the individuation degree is insufficient, and decision making is lack of scientificity are solved, and accurate, self-adaptive and safe individualized physical training management is achieved.

The invention relates to the technical field of audio signal processing, in particular to an audio equalization adjustment method and device and a storage medium. The audio equalization adjustment method comprises the following steps: acquiring a physiological movement signal and an environment audio signal of a user; respectively processing the physiological motion signal and the environment audio signal to obtain physiological motion features and environment noise features; performing fusion decision based on the physiological motion features and the environmental noise features to generate a target equilibrium parameter set; and based on the target equalization parameter set, performing equalization adjustment on the audio output signal of the near-to-eye display device. According to the method, the auditory experience of the near-to-eye display equipment in the motion scene can be intelligently optimized.

Provided is a nanoparticle-mediated targeted drug delivery robotic system for the precision treatment of breast cancer. **Solution**: This system 100 integrates robot-assisted movement, real-time image processing, an artificial intelligence-driven control mechanism, and sensor-guided targeting to ensure the accurate delivery of therapeutic drugs to cancer tissue while minimizing damage to surrounding healthy structures. The system consists of a six-degree-of-freedom articulated robotic arm 102, a drug release control actuator 114, a targeting module 106 equipped with optical and electromagnetic sensors, and a control unit 110 equipped with machine learning technology for real-time decision-making. The image subsystem 112 utilizes magnetic resonance imaging, ultrasound, and infrared imaging to provide a detailed anatomical and functional view of breast tissue. The artificial intelligence-driven technology of this system continuously processes image and sensor data, guides the robotic arm towards the tumor site, and dynamically adjusts the positioning based on physiological movements and tissue changes. A force feedback mechanism minimizes tissue damage during insertion, and an automatic calibration system finely adjusts the movement of the robotic arm in real time. The actuator is designed as an electric syringe or a controlled valve system to accurately administer nanoparticle-based therapeutic drugs directly to the tumor, optimizing the drug efficacy while suppressing systemic toxicity.

The invention discloses a bacteriophage virus multi-host prediction method, system and device and a medium, and the method comprises the steps: receiving knee joint data through a sliding window, building a joint physiological kinematics constraint, and building a joint physiological motion optimization equation based on the joint physiological kinematics constraint; solving the joint physiological motion optimization equation to obtain a joint axis and a joint position vector; based on the joint axis and the joint position vector, two groups of joint angles are obtained through acceleration information and angular velocity integration; and solving the weighted average of the two groups of joint angles through complementary filtering to obtain the joint angle. According to the method, the problem of disturbance caused by unstable wearing or external disturbance in the measurement process of the inertial sensing wearable inertial node is solved.

The present disclosure relates to a coil assembly of an MRI device. The MRI device may be configured to perform an MR scan on a subject. The coil assembly may include one or more coil units, a substrate, and a sensor mounted within or on the substrate. The one or more coil units may be configured to receive an MR signal from the subject during the MR scan. The substrate may be configured to position the one or more coil units during the MR scan. The one or more coil units may be mounted within or on the substrate. The sensor may be configured to detect a motion signal relating to a physiological motion of the subject before or during the MR scan.

The present application relates to a system and method for motion detection. The method includes acquiring initial cardiac motion information of a subject via a first sensor; acquiring detection information of the subject via a second sensor, the detection information including at least one of physiological motion information and postural motion information of the subject; correcting the initial cardiac motion information based on the detection information to generate target cardiac motion information of the subject; generating a control signal for a medical device based on the target cardiac motion information; and controlling the medical device to perform a scan on the subject based on the control signal.

The application discloses an interventional surgery instrument operation track intelligent planning dynamic navigation control method and system, and belongs to the technical field of minimally invasive interventional surgery intelligent navigation. A patient's preoperative three-dimensional medical image and intraoperative two-dimensional perspective image are acquired, and a digital twin model of a surgery region containing anatomical structures and physical properties is constructed; an initial optimal operation track is generated through a rapidly expanding random tree and convex optimization, and an anatomical structure displacement caused by physiological motion is compensated by adopting nonlinear elastic registration based on feature points; dynamic resistance feedback is calculated in combination with an instrument mechanical response model, track correction instructions and feedback signals are output, and a closed-loop navigation is realized by driving an executing mechanism and a main operating handle. The system contains five modules of image processing, track planning, registration compensation, control calculation and executing feedback, can effectively improve operation precision and safety in a complex blood vessel environment, solves problems of interventional surgery hand feeling loss, dynamic adaptation difference and navigation precision deficiency, and is suitable for various blood vessel interventional minimally invasive treatments.

Methods and devices provide physiological movement detection with active sound generation. In some versions, a processor may detect breathing and / or gross body motion. The processor may control producing, via a speaker coupled to the processor, a sound signal in a user's vicinity. The processor may control sensing, via a microphone coupled to the processor, a reflected sound signal. This reflected sound signal is a reflection of the sound signal from the user. The processor may process the reflected sound, such as by a demodulation technique. The processor may detect breathing from the processed reflected sound signal. The sound signal may be produced as a series of tone pairs in a frame of slots or as a phase-continuous repeated waveform having changing frequencies (e.g., triangular or ramp sawtooth). Evaluation of detected movement information may determine sleep states or scoring, fatigue indications, subject recognition, chronic disease monitoring / prediction, and other output parameters.

The invention provides a CT-guided puncture navigation method and system, and relates to the field of puncture navigation, and the method comprises the following steps: determining a plurality of groups of puncture routes according to a CT image; according to the real-time physiological movement data, dividing the plurality of groups of puncture routes into a plurality of sub-routes, and performing CT scanning on each sub-route to obtain real-time image data of each sub-route under the influence of physiological movement; according to the real-time image data of each sub-route under the influence of the physiological movement, in combination with the real-time physiological movement data, carrying out potential influence evaluation on puncture of each sub-route by the physiological movement to obtain an influence evaluation result; according to the influence evaluation result, selecting sub-routes with the smallest influence, and combining the sub-routes into an optimal puncture navigation path; in the puncture process, changes of physiological movement are continuously monitored, and the optimal puncture navigation path is dynamically adjusted according to real-time movement data. The defect that in the prior art, physiological movement is difficult to accurately predict and compensate, and consequently puncture precision is reduced is overcome.

Methods and devices provide physiological movement detection with active sound generation. In some versions, a processor may detect breathing and / or gross body motion. The processor may control producing, via a speaker coupled to the processor, a sound signal in a user's vicinity. The processor may control sensing, via a microphone coupled to the processor, a reflected sound signal. This reflected sound signal is a reflection of the sound signal from the user. The processor may process the reflected sound, such as by a demodulation technique. The processor may detect breathing from the processed reflected sound signal. The sound signal may be produced as a series of tone pairs in a frame of slots or as a phase-continuous repeated waveform having changing frequencies (e.g., triangular or ramp sawtooth). Evaluation of detected movement information may determine sleep states or scoring, fatigue indications, subject recognition, chronic disease monitoring / prediction, and other output parameters.

Methods and devices provide physiological movement detection, such as breathing, cardiac and / or gross body motion, with active sound generation using electronic processing device(s). The processor may control producing, via a speaker coupled to the processor, a sound signal in a user's vicinity. The processor may control sensing, via a microphone coupled to the processor, a reflected sound signal. This reflected sound signal is a reflection of the sound signal from the vicinity or user. The processor may process the reflected sound, such as by a demodulation technique. The sound signal may be produced as a dual tone frequency modulation continuous wave signal. Evaluation of detected movement information may determine sleep states or scoring, fatigue indications, subject recognition, chronic disease monitoring / prediction, and other output parameters.

Method acquiring a target physiological motion signal, including: acquiring multi-channel complex signals received by multiple channels; and acquiring, from the multi-channel complex signals using a motion signal synthesis vector corresponding to a target motion signal, a target motion complex signal with interference removed; acquiring data received by multiple channels, the data including data without external interference in a first sub-period and data with external interference in a second sub-period; acquiring an external interference suppression matrix based on the data, and acquiring external interference suppression data based on the data without external interference or the data with external interference and the external interference suppression matrix; acquiring a motion signal correlation matrix of the target motion signal in frequency domain based on a frequency range of the target motion signal; and using, as a motion signal synthesis vector, an eigenvector acquired according to an eigenvalue of the motion signal correlation matrix.

Aspects of the of the disclosure relate to a non-contact physiological motion sensor and a monitor device that can incorporate use of the Doppler effect. A continuous wave of electromagnetic radiation can be transmitted toward one or more subjects and the Doppler-shifted received signals can be digitized and / or processed subsequently to extract information related to the cardiopulmonary motion in the one or more subjects. The extracted information can be used, for example, to determine apneic events and / or snoring events and / or to provide apnea or snoring therapy to subjects when used in conjunction with an apnea or snoring therapy device. In addition, methods of use are disclosed for sway cancellation, realization of cessation of breath, integration with multi-parameter patient monitoring systems, providing positive providing patient identification, or any combination thereof.

The invention belongs to the technical field of nuclear medicine imaging, and discloses a radioactive tracer agent distribution quantification optimization method and related equipment, and the method comprises the steps: obtaining scanning bed deformation information, moving track information and physiological motion dynamic information of a patient, and obtaining a radioactive tracer agent distribution quantification optimization result based on the scanning bed deformation information, the moving track information and the physiological motion dynamic information; the method comprises the steps of constructing a multi-source error integrated influence model, performing radioactive tracer distribution reconstruction on original detection data through an OSEM algorithm based on the multi-source error integrated influence model to obtain real distribution information of a radioactive tracer, and performing calculation according to the real distribution information to obtain a standardized uptake value. By means of the method, the accuracy of the radioactive tracer agent distribution quantification result is improved.

The present application relates to the field of biomedical engineering technology. The present application discloses a physiological signal detection method, apparatus, terminal device, and storage medium based on the moiré effect, which can improve the accuracy of detecting physiological signals. The physiological signal detection method based on the moiré effect comprises obtaining a target video of the chest and / or abdomen of a target user, wherein each frame of the original image in the target video contains moiré patterns, and the moiré patterns are used to amplify the pixel displacement caused by the physiological movement of the target user; performing moiré pattern enhancement processing on each frame of the original image to obtain multiple frames of target images; and performing signal extraction processing on the multiple frames of target images to obtain physiological signals.

The application provides a multimodal sensory-motor closed-loop control system and method for a nerve injury rehabilitation device, and relates to the technical field of intelligent medical rehabilitation devices. The system comprises: a multimodal sensing module that synchronously collects physiological signals, kinematic signals and semantic input signals and adds isogenic hardware time stamps; a subjective and objective alignment processing module that intercepts an asymmetric time window and generates a subjective and objective alignment state slice based on a semantic event anchor point; a multimodal parameter generation module that outputs a machine-resolvable structured control instruction in combination with state characteristics and a clinical background and is verified through a safety shadow network; and a closed-loop physical execution module that synchronously drives a motion intervention loop to output mechanical impedance and a sensory compensation loop to output electrical stimulation within the same hardware synchronous trigger cycle. The application realizes accurate alignment of subjective semantics and objective physiological motion data, synchronous driving of dual-loop execution, reduction of delay and semantic ambiguity, and improvement of safety and adaptability through multiple safety verification.

The invention discloses a nasopharyngeal laryngoscope focus accurate positioning and image recognition system, which comprises a shape sensing subsystem, an absolute positioning subsystem and a data processing module, and is characterized in that the shape sensing subsystem senses deformation in real time through a strain sensor array in a hose, and the absolute positioning subsystem establishes a fixed reference coordinate system through a reference mark; the data processing module fuses the two kinds of data, establishes a dynamically maintained patient coordinate system and achieves accurate positioning and mapping of the laryngoscope tail end position, the system generates a lesion stereoscopic model through multi-view image collection and three-dimensional reconstruction, intelligent matching analysis is conducted in combination with a lesion database, and an evaluation result is provided. Meanwhile, dynamic compensation and self-checking functions are realized based on physiological movement signals, so that the problem of positioning drift caused by movement and physiological movement of a patient in traditional laryngoscopy is effectively solved, and accurate space positioning, three-dimensional visual representation and intelligent diagnosis assistance of a focus are realized; the diagnosis and treatment accuracy and the operation safety of the diseases of the nose and throat department are obviously improved.

The invention relates to the technical field of medical image processing, and provides an image sequence registration method, which comprises the following steps of: firstly, calculating relative displacement of adjacent frames, accumulating to obtain absolute displacement, decomposing the absolute displacement, and extracting trend components representing physiological movement and high-frequency residual errors representing random disturbance; meanwhile, a current frame and a reference frame are input into a displacement fine-tuning network to obtain a displacement fine-tuning amount, then the high-frequency residual error is negated and then weighted with the displacement fine-tuning amount to synthesize compensation displacement, and spatial transformation is carried out on the image. According to the method, motion components are separated, the physiological motion trend is reserved while random jitter is compensated, over-correction caused by integral accumulation errors or end-to-end learning is avoided, and high-precision image sequence registration is achieved.

A sensor 104 for non-contact sensing of a physiological parameter of a body 102 is described. In an embodiment, the sensor 104 comprises: a waveguide, the waveguide comprises a metamaterial and is configured to receive a transmitted signal and to propagate the transmitted signal in a spoof surface plasmon mode along the waveguide to produce an evanescent electromagnetic field and to provide a received signal, wherein the waveguide is placed at a predetermined distance away from the body 102 for non-contact sensing of a perturbation produced by a physiological motion of the body 102 using the evanescent electromagnetic field, the perturbation produces a phase shift between the transmitted signal and the received signal for use in determining the physiological parameter of the body 102. A system 100 and a method 200 for non-contact sensing of a physiological parameter of a body 102 are also described.

The invention relates to the field of medical image processing, and discloses a medical image virtual simulation method and system based on digital twinning. The method comprises the following steps: acquiring original physiological data and carrying out sliding window time sequence sampling to obtain a preliminary physiological movement sequence; extracting position deviation characteristics from the preliminary physiological movement sequence to obtain a dynamic interference distribution matrix; abnormal fluctuation in the dynamic interference distribution matrix is detected, nonlinear supplementary interference samples are generated and fused, and an enhanced interference data field is obtained; performing superposition operation on standard nuclear magnetic imaging data by using the enhanced interference data field to obtain a preliminary simulation image sequence; extracting time dynamic features of the preliminary simulation image sequence and a real clinical artifact image, and comparing the time dynamic features to generate a feature difference chart; and according to the feature difference image, calculating an adaptive fusion weight and performing residual feature completion to obtain a final medical image simulation result. According to the method, high-fidelity reproduction and closed-loop optimization of the dynamic artifacts of the medical image are realized.

A battery-less, wirelessly powered localization system is described. In an embodiment, a wirelessly powered localization system, includes an external Tx antenna that generates a radio frequency (RF) signal that wirelessly powers a set of one or more localizers, an external Rx antenna that receives an output from the localizers, a localizer including: an Rx antenna that receives a radio frequency (RF) signal from an external Tx antenna, a passive four-stage full-wave CMOS rectifier that generates a DC voltage using the received RF signal, a low-dropout regulator that generates a stable DC voltage based on the rectifier-generated voltage, a frequency divider circuit to divide the frequency of received RF signal, and a Tx antenna that outputs an RF signal at the divided frequency to the external Rx antenna.

This application relates to the field of medical image processing technology, and discloses a method and system for lesion analysis of SPECT and spectral CT fusion images. The method includes acquiring SPECT and spectral CT images; identifying at least one anatomical feature point in the spectral CT image and identifying a functional feature point corresponding to the anatomical feature point in the SPECT image; calculating the first spatial coordinates of the anatomical feature point in the spectral CT image and the second spatial coordinates of the functional feature point in the SPECT image; determining the deformation parameters of a local region in the SPECT image based on the difference between the first and second spatial coordinates; and performing spatial transformation processing on the functional distribution features of the local region in the SPECT image to spatially align the processed functional distribution features with the anatomical features in the spectral CT image, actively eliminating image misalignment caused by physiological motion and other factors, and achieving alignment of functional information with anatomical structures.

The invention relates to the technical field of medical data compression, and discloses a lossless compression method for medical image data, which comprises the following steps of: 1, acquiring three-dimensional medical image data and ray beam path data in a radiotherapy plan, and segmenting the three-dimensional medical image data into a plurality of voxel blocks; and performing clinical importance grade labeling on the voxel blocks according to ray beam path data. According to the technical scheme, physiological motion signals of a patient are obtained to generate a displacement time table, motion compensation is executed based on the displacement time table to generate a prediction image, and finally reversible differential storage is conducted on a real image and the prediction image, so that the purposes of fully utilizing time sequence redundancy of three-dimensional medical image data, remarkably improving the compression ratio and improving the image quality are achieved. And compared with the technical scheme that compression is adopted piece by piece and time relevance is not utilized in the prior art, the problems that the compression efficiency is low and excessive storage resources are occupied are solved.

The invention relates to the technical field of biomedical engineering. The invention discloses a physiological signal detection method and device based on the molar effect, terminal equipment and a storage medium. The physiological signal detection accuracy can be improved. The physiological signal detection method based on the Moire effect comprises the steps that a target video of the chest and / or the abdomen of a target user is obtained, each frame of original image in the target video contains moire patterns, and the moire patterns are used for amplifying pixel displacement caused by physiological movement of the target user; performing moire enhancement processing on each frame of original image to obtain multiple frames of target images; and performing signal extraction processing on the multiple frames of target images to obtain physiological signals.

The invention provides a joint reconstruction and dynamic registration method and device, equipment and a medium, and relates to the technical field of image processing. The method comprises the following steps: obtaining a fused feature map through feature extraction operation and feature fusion operation, and carrying out dynamic deformation registration operation on a preprocessed SPECT basic image and a target CT image by using the fused feature map to obtain a registered CT image, a registered SPECT image and a dynamic displacement field for compensating physiological movement. And performing reconstruction operation on the registered SPECT image by using a reconstruction constraint condition, the registered CT image and the dynamic displacement field to obtain a reconstructed SPECT image. According to the method, a joint optimization framework is constructed by deeply embedding dynamic deformation registration into a reconstruction process, so that the SPECT reconstruction can fully utilize CT anatomy prior and displacement field constraint, a traditional serial error chain is broken, and the reconstruction precision and function-anatomy alignment degree are remarkably improved.