114 results about "Respiratory motion" patented technology

The invention discloses a tumor respiratory movement trajectory prediction method and system based on spatio-temporal feature separation LSTM, and the method comprises the following steps: collecting a four-dimensional CT respiratory cycle image, extracting a tumor centroid coordinate, and generating a standardized tumor centroid coordinate sequence through sliding window standardization; the method comprises the following steps: inputting bidirectional LSTM to calculate Euclidean distance screening features and weighting to generate a weighted spatial feature vector sequence, extracting time recursion feature weighted fusion through one-dimensional convolution and unidirectional LSTM, predicting a tumor motion trajectory through autoregression, and comparing real-time coordinate correction to generate an adaptive correction trajectory prediction result. A four-dimensional image sequence is extracted and standardized through registration, a two-way network is combined to calculate two-way distance features to recognize breathing phase changes, spatial-temporal features are fused to establish a nonlinear recursive relation to capture tumor motion differences, real-time correction optimization is achieved through deviation statistics and weight self-adjustment, and prediction stability and trajectory fitting precision are improved.

Disclosed herein is a medical device for tracking movement of a region of a patient's body. The region has a range of motion, for example a range of respiratory motion. The device comprises a controller configured to determine a motion of the region based on one or more initial images depicting at least part of the region. The controller is further configured to predict, based on the determined motion, a motion event time at which at least one property associated with the motion or position of the region will meet at least one criterion, wherein the at least one criterion comprises the region being located at a particular point in its range of motion. The controller is further configured to determine, based on the predicted motion event time, at least one subsequent image capture time at which at least one subsequent image should be captured.

The invention relates to the technical field of medical image processing and surgical navigation, in particular to a liver segmentation, modeling and surgical simulation system based on a cascade neural network and a multi-scale reconstruction technology. The multi-scale dynamic registration module is used for carrying out coarse segmentation and fine segmentation on liver and focus areas of the medical image and is used for non-rigid registration and respiratory motion compensation of the multi-modal medical image; the physical enhancement modeling engine is used for constructing a liver vessel tree three-dimensional model containing hemodynamic characteristics; the operation navigation and risk assessment module is used for performing real-time navigation and operation path planning in the operation; and the self-adaptive computing framework provides underlying computing resource support for the system. And high-precision segmentation: through a cascade recursive network and a boundary sensitive loss function, the liver tumor segmentation Dice coefficient reaches 94-96%, which is increased by 6-12% compared with the traditional method.

The invention relates to a PET / CT (positron emission tomography / computed tomography) image breathing motion artifact correction method based on a triple subgroup convolutional network, and belongs to the field of nuclear medicine imaging. The invention provides a lightweight triple-subgroup convolution kernel, and the convolution kernel focuses on analyzing the rotation and translation characteristics of coronal planes, sagittal planes and cross sections closely related to PET / CT images so as to realize efficient detail analysis under the condition of clinical small samples. And then, a Transform-subgroup convolution fusion encoder and a pyramid network are constructed in combination, a constructed triple subgroup convolution registration network can combine sub-deformation fields of multiple dimensions to obtain a smooth deformation field, and the deformation field is used for spatial distortion transformation to achieve the purpose of artifact correction. According to the method, artifact correction experiment comparison is carried out by using pixel body membrane simulation data and clinical data, the superiority of the method in the aspects of robustness and generalization ability is proved, and the quality of PET / CT images is effectively improved.

The invention discloses an AI auxiliary radiotherapy dose intelligent optimization device, which comprises a multi-modal image fusion module, a dose distribution prediction module, a dynamic adaptive optimization module and a prognosis model integration module, and is characterized in that the multi-modal image fusion module is used for aligning anatomical features of different images, eliminating respiratory motion artifacts and predicting the dose distribution of the different images; the dose distribution prediction module is used for rapidly predicting radiotherapy dose distribution based on anatomical features and historical data, the dynamic adaptive optimization module is used for monitoring anatomical changes in real time and dynamically adjusting a dose plan, and the prognosis model integration module is used for quantifying correlation between dose distribution and radioactive injury risks. High-precision alignment and respiratory motion artifact elimination of an anatomical structure are achieved through the multi-modal image fusion module, three-dimensional dose calculation is rapidly and accurately conducted through the dose distribution prediction module, organ displacement and deformation are effectively coped with through the dynamic self-adaptive optimization module through a real-time image monitoring and reinforcement learning algorithm, and the accuracy of the three-dimensional dose calculation is improved. And the prognosis model integration module constructs an individualized risk prediction model.

The invention discloses an accurate X-ray radiation dose measurement system based on artificial intelligence, which comprises the following steps: acquiring CT image data of a patient and pulse irradiation parameters of radiotherapy equipment through terminal equipment, and calculating a patient specific anatomical structure dynamic influence factor set, a pulse waveform time domain characteristic factor and a tissue interface scattering correction factor; all the parameters are substituted into a dose measurement formula to obtain an accurate X-ray radiation dose value; through a deep fusion image recognition technology (such as a high-resolution anatomical structure, tissue density gradient and heterogeneous region distribution provided by CT / MRI), a secondary particle scattering effect of a junction region of a tumor and a normal tissue can be accurately represented; and dynamic anatomical information (such as respiratory movement and organ displacement) in the image is combined to correct the time characteristic (such as dynamic change under an instantaneous high dose rate) of the pulse radiation field in real time, so that the dose calculation accuracy of a fast algorithm in a complex scene is remarkably improved.

The invention discloses a small animal in-vivo multi-parameter dynamic monitoring method based on photoacoustic imaging, and relates to the technical field of biomedical imaging, and the method comprises the steps: obtaining a photoacoustic signal generated by a small animal under the excitation of pulse laser output by an optical excitation module through an acoustic detection module; reconstructing a photoacoustic image of the photoacoustic signal through a filtering back projection algorithm; calculating the similarity between adjacent images in the photoacoustic image, identifying the image of which the similarity is lower than a set frame threshold value as a cross section slice polluted by respiratory motion artifacts and removing the cross section slice, and replacing the removed image frame by using the interpolation of an adjacent artifact-free image so as to obtain an updated photoacoustic image; selecting a region of interest in the photoacoustic image, and carrying out oxygenation kinetics monitoring, pharmacokinetics monitoring, perfusion kinetics monitoring or nanoparticle in-vivo kinetics monitoring; according to the monitoring method, motion artifacts caused by breathing of the small animals are effectively inhibited, and in-vivo multi-parameter dynamics monitoring of the small animals is achieved.

The invention provides a regional anesthesia puncture path planning method and system under ultrasonic guidance, and relates to the technical field of ultrasonic image.According to the regional anesthesia puncture path planning method and system, dynamic motion information of a tissue structure is obtained by collecting ultrasonic image data of a target region and conducting motion analysis, and electrocardiosignals are synchronously collected to determine heart beat time phase information; determining a vascular movement mode based on the two, learning a time change rule by using a long-short-term memory network, and establishing an association relationship between a vascular spatial position and a heart beat phase; constructing a motion prediction model to predict the future motion trend of the blood vessel, and fusing the respiratory motion information to correct to obtain the blood vessel motion information; and finally, a safe puncture window is calculated according to the information, a regional anesthesia puncture path is planned, vascular movement prediction and safe puncture window calculation based on vascular movement rule learning and breathing correction in regional anesthesia under ultrasonic guidance can be achieved, and then the puncture path is precisely planned.

A drug testing platform for simulating a lung environment includes a microfluidic chip and a stretching device. The microfluidic chip defines a microfluidic channel structure. The microfluidic channel structure includes a test unit, a cell shunt unit and a drug shunt unit. The stretching device is configured to stretch and contract the test unit in a manner of a reciprocal motion, thereby making degree of deformation of a plurality of test area of the test unit to be same during the reciprocal motion. The drug testing platform for simulating the lung environment according to the present disclosure may configure an environment that simulates a breathing motion of a human lung, and obtain multiple results within a single test.

The invention discloses a respiratory movement tracking method and system, computer equipment and a medium thereof, which are applied to the technical field of medical treatment, and the method comprises the following steps: inputting a CT image sequence into a network model pre-constructed based on a conditional diffusion model, identifying the morphological change of a target area along with respiration, and generating a sequential deformation field changing along with respiration; selecting representative tracking points such as organ edge special position points and focus area center points from a target area, tracing position information at different moments according to a time sequence deformation field, calculating displacement and forming a displacement track; irrelevant frequency interference in displacement track data is filtered out through a band-pass filtering technology, breathing movement related signals are highlighted, phase information is extracted through Hilbert transform, a breathing movement curve is drawn, visual presentation and tracking of breathing movement are achieved, doctors can be helped to more accurately grasp the breathing law of a patient, and the accuracy of breathing movement tracking is improved. Errors caused by respiratory movement are avoided in advance in surgical planning.

The invention relates to the technical field of image segmentation, in particular to an automatic real-time outline drawing system for a liver tumor ablation area based on an ultrasonic image. The method comprises the following steps: firstly, registering and aligning preoperative and intraoperative ultrasonic images, and eliminating displacement deviation caused by factors such as respiratory movement and probe shaking; further based on the essential difference between the ablation region and the surrounding normal liver tissue in ultrasonic echo expression, dynamic changes of region features are analyzed to obtain ablation feature parameters of each sub-region in the intraoperative ultrasonic image so as to evaluate the ablation state, and then the image is enhanced based on the ablation state so as to enhance the boundary definition, and finally the ablation state of the intraoperative ultrasonic image is evaluated. And the outline drawing accuracy of the outline of the liver tumor ablation area is improved.

This invention provides a non-contact method, device, equipment, and storage medium for measuring trunk respiratory parameters. It synchronously acquires three-dimensional motion data of optical reflective markers during respiration, with these markers positioned at multiple pre-defined anatomical landmark locations on the subject's trunk. Based on the three-dimensional motion data, it determines the volume change of the spatial envelope formed by the optical reflective markers. According to a pre-established mapping relationship between the volume change and tidal volume, it converts the volume change into tidal volume. Based on the signal of the volume change over time, it extracts the respiratory rate. Finally, it calculates the total respiratory volume based on the tidal volume and the respiratory rate. By combining optical motion capture with spatial geometric modeling, it achieves non-contact, continuous, and high-precision measurement of trunk respiratory motion, effectively overcoming the shortcomings of traditional methods, such as reliance on patient cooperation, invasiveness, expensive equipment, and complex operation.

This invention relates to the field of ultrasound examination auxiliary control, specifically disclosing a self-orthogonal scanning control method for an abdominal ultrasound robot. The method includes the following steps: system initialization, defining the end-effector coordinate system and configuring the hardware; then, by sampling the point cloud through the camera, fitting the surface normal to key points and neighborhoods along the scanning path, completing coarse alignment, and switching to high-frequency force feedback fine-tuning. The force-position hybrid control main loop is initiated, and the S variable is set according to the contact force state: if the contact force meets the standard, scanning proceeds along the set direction; otherwise, compensation is performed in a specific direction. This method, with "force feedback self-orthogonal" as its core, can adapt to complex curved surfaces and respiratory motion scenarios, optimize imaging quality and acoustic coupling effects, suppress measurement errors, and has strong anti-interference capabilities and high hardware compatibility, reducing the difficulty of implementation.

The invention relates to the technical field of surgical navigation, in particular to a children urinary system endoscopic surgery visual auxiliary operation system which comprises a respiratory displacement field generation module, a tissue stiffness inversion module, a visual scale correction module, a tangential gradient calculation module and an anisotropic registration correction module. According to the method, a respiration displacement field is analyzed to invert tissue hardness parameters, a preoperative physical model with biomechanical characteristics is constructed, non-rigid deformation behaviors of kidneys and ureters of children in a stress state are simulated, the physical depth of pixels is calculated in combination with endoscopic image characteristics, sparse feature point cloud is converted into real-scale spatial data, and the spatial depth of the kidneys and ureters of the children is calculated. And according to the tangential gradient change of the path, constructing an anisotropic weight matrix to dynamically adjust the registration constraint intensity, and driving the virtual model to follow the movement track of the endoscope to carry out adaptive deformation correction, so that real-time three-dimensional visual guidance for soft tissue respiratory movement and contact deformation is realized.

Disclosed in the present invention are a motion management method and system, and a related device, which relate to the technical field of radiotherapy. The system comprises: a real-time imaging module used for acquiring a body surface contour of a patient in real time and acquiring a respiratory curve of the patient according to the body surface contour, the body surface contour being used for auxiliary positioning of the patient; and a 4D acquisition module used for sending a time signal to a sliding gantry CT according to the respiratory curve of the patient to establish a respiratory phase synchronization timing sequence, wherein when a treatment couch is at a scanning position of the sliding gantry CT, according to a real-time respiratory signal of the patient, 4DCT images or breath-hold images of the patient in different respiratory phases are acquired using the sliding gantry CT. The 4DCT images or the breath-hold images are used for registration with a positioned 4DCT image, thereby overcoming the drawbacks that previously only tumor images at a certain respiratory phase are obtainable and the images are prone to motion artifacts, resulting in errors in registration. As a result, the registration accuracy of a tumor that is greatly affected by respiratory motion is improved, and the clinical efficiency is enhanced.

The invention discloses an X-ray machine intelligent examination scheme creation method based on pet identity recognition, and relates to the technical field of veterinary diagnostic images.The method has the advantages that variety-specific artifacts are accurately inhibited, modeling is performed through breathing movement driven by skeleton points, high-frequency vibration noise is separated, dynamic blurring of a trachea area of a short-nose dog is eliminated, and the accuracy of the examination scheme is improved. The tiny lesion detection capability is improved; the limitation of a single angle threshold value is avoided by adopting a composite geometric criterion, so that pets with different body types can be clearly imaged under abnormal body positions; full-process identity data binding, biological characteristic penetration scanning protocol formulation, radiation protection and data storage links are provided, real-time association of images and individual medical records is ensured, and manual checking errors are avoided; a block chain evidence storage mechanism is introduced to meet the electronic medical record compliance requirement of a diagnosis and treatment institution, and cross-institution data security sharing is realized; historical parameters are automatically loaded, repeated debugging is reduced, new pets are rapidly initialized through a variety parameter library, and the equipment preparation time is remarkably shortened.

The application provides a three-dimensional reconstruction and quantitative analysis consistency control method and system of multi-center CT blood vessel imaging data, an electronic device and a storage medium, and relates to the technical field of medical image processing. The method comprises the following steps: first, synchronously acquiring original projection data of multi-center CT blood vessel imaging, blood vessel center line topological data and blood vessel respiratory motion displacement data, generating a blood vessel deformation correction matrix based on the respiratory motion displacement data, and dynamically registering the blood vessel center line data by using the matrix to obtain corrected center line data; then, inputting the corrected center line data and the original projection data into a multi-modal feature fusion network for three-dimensional reconstruction to generate an initial blood vessel model; then, performing morphological parameter quantitative analysis on the initial model; finally, comparing the analysis result with a clinical standard and adjusting the model parameters to output a target blood vessel three-dimensional model. The application improves the geometric accuracy and clinical applicability of the blood vessel model reconstruction.

The invention discloses an electronic control method of a medical laser positioning system, which comprises the following steps: a signal acquisition and conversion step: acquiring an optical signal reflected by positioning laser on the body surface of a patient and modulated by respiratory movement, and converting the optical signal into a corresponding sensing electric signal; phase identification: processing the sensing electric signal to identify whether the current respiratory cycle is in a preset stable phase or not; a laser gating step of controlling the output mode of the positioning laser according to the identification result of S2; when the positioning laser is identified to be in the preset stable phase, the positioning laser is controlled to work in a first output mode, and the laser positioning system is upgraded from a passive projection tool to an active system with the physiological signal sensing capacity. By extracting the breathing phase in real time and accurately controlling the laser output mode according to the breathing phase, the system can automatically provide a clear positioning mark at the most stable moment in the breathing cycle.

This invention relates to an active disturbance rejection control method and system suitable for biomimetic chest cavity motion simulation. The method includes: acquiring and preprocessing a nonlinear motion trajectory signal to generate an original target position command; processing the original target position command using a tracking differentiator to generate a smoothly transitioning desired position signal and desired velocity signal; receiving the actual position feedback signal of the controlled object and the control input of the previous control cycle through an extended state observer, and estimating the actual position state observation value, actual velocity state observation value, and total disturbance state observation value of the controlled object in real time; calculating the position tracking error and velocity tracking error based on the desired position signal, desired velocity signal, and the actual position state observation value and actual velocity state observation value of the controlled object, and calculating the initial state feedback control quantity; generating an actual control command and sending it to the motor driver to drive the biomimetic chest cavity motion simulation platform to reproduce the target respiratory motion trajectory.

This invention provides a deep learning (DL) model for fast deformable image registration using 2D sagittal cine MRI acquired during radiation therapy. A DL model for fast deformable image registration is trained using cine MRI scans acquired during MR-Linac treatments of thoracic and abdominal tumors. The model uses a pair of cine MRI images as inputs and outputs a dense motion vector field (MVF) which aligns the images. The trained model is applied to predict frame by frame motion from cine MRIs in which both cardiac and respiratory motion are visible. The number of respirations and heart beats is automatically extracted by performing peak detection on high-frequency and low-frequency components of the MVF displacements corresponding to the chest wall and cardiac regions.

The invention discloses a precise positioning puncture device for animal husbandry and veterinary treatment, which comprises a fixing mechanism for fixing an animal, an electrical control cabinet for controlling the device to operate and a control panel for operator interaction, and further comprises a multi-mode sensing puncture execution assembly arranged above the electrical control cabinet, the mechanical arm is composed of a mechanical arm body and a tail end integration unit. A dynamic modeling unit, a track prediction unit, a path planning unit and a puncture execution unit are arranged in the electrical control cabinet; a dynamic mapping model of body surface movement and target movement is established through an LSTM neural network, a respiratory component and a stress component are explicitly decomposed, and a complex movement track of a target under coupling of the respiratory movement and a stress event can be accurately predicted; the body type difference of different varieties of animals is adaptively processed through a multi-head attention mechanism, and universal adaptation of a single model to various animals such as cattle, pigs and sheep is achieved.

The invention relates to a blood vessel center line determination method and device, computer equipment, a medium and a product. The method comprises the following steps: acquiring a contrast agent center line corresponding to a target blood vessel; determining a search area corresponding to each point on the center line of the contrast agent; and performing optimal pixel point search in the search area corresponding to each point, and determining the center line of the target blood vessel according to the optimal pixel point. By adopting the method, optimal pixel point searching can be carried out in the searching area corresponding to each point, the pixel points in the time state that the breathing movement of the patient is small can be found, and therefore the center line of the target blood vessel in the time state that the breathing movement is small can be determined, and at the moment, due to the fact that the breathing movement of the patient is small, the target blood vessel can be accurately searched. Therefore, the center line of the contrast agent in the reconstructed image does not have motion artifacts, so that the center line of the target blood vessel is determined based on the center line of the contrast agent, and the accuracy of determining the center line of the target blood vessel can be improved.

This invention discloses a portable oxygen generator and method powered by human kinetic energy, relating to portable pressure swing adsorption (PSA) oxygen generation technology. The device includes a main energy-gathering module, a main unit module, an auxiliary energy-gathering module, and a control module. The main energy-gathering module generates a first gas source by directly compressing air through the impact of human limbs, while the auxiliary energy-gathering module recovers the kinetic energy of exhalation to generate a second gas source. The main unit generates oxygen through PSA in an adsorption tower, with no electrically powered booster components. The control module utilizes the dual rhythms of breathing and movement to achieve pulsed, on-demand oxygen production, with high-pressure gas generation during inhalation and low-pressure standby during exhalation. The main energy-gathering module employs a decoupled support-work structure, combining the rigid support of a walking stick with the pumping function. This invention requires no external power supply, has high energy utilization, and weighs ≤1.1kg. At an altitude of 5500m and a walking frequency of 30 steps / minute, it stably outputs 2L / min of 90% oxygen, suitable for various scenarios such as high-altitude mountaineering and wilderness emergencies.

The invention discloses a real-time image guiding method and system for organ motion compensation in tumor radiotherapy, and the method comprises the steps: constructing a respiratory motion model through the synchronous collection of the three-dimensional position of a gold mark and the motion track of a body surface LED mark point, and obtaining an atrophy compensation component through the combination of the volume atrophy proportion and the gravity center displacement of the gold mark in the radiotherapy process; and then carrying out weighted fusion on historical radiotherapy data, a gold label vector and a position relationship to obtain an accurate rotation compensation component, inputting the current position of the gold label into the model to update parameters in real time, predicting the position of the gold label at the next moment by combining the two types of compensation components, and meanwhile, carrying out model loop optimization through comparison of actual positions. According to the invention, the positioning accuracy of the target region in tumor radiotherapy is greatly improved, it is ensured that radioactive rays can accurately irradiate the tumor target region, the tumor local control rate is further improved, and the life quality of a patient is improved.

The invention belongs to the technical field of image processing, and discloses a 4D-CBCT dynamic reconstruction method which comprises the following steps: constructing a priori motion model based on principal component analysis in an off-line manner for describing a main mode of organ respiratory motion; designing and training a deep learning network fusing a convolutional long short-term memory network and a double attention mechanism, wherein the network can learn nonlinear mapping from a two-dimensional projection image sequence to a PCA coefficient representing three-dimensional motion; in the online reconstruction stage, real-time projection is input into a network to predict a PCA coefficient, and a high-quality 4D-CBCT image sequence is quickly reconstructed through PCA inverse transformation and image deformation. According to the invention, the CBAM module enhances local features and inhibits noise in an encoder, and the SPA module carries out global context compensation after ConvLSTM. According to the method, the precision and robustness of 4D-CBCT dynamic reconstruction are improved, and complex respiratory movement can be accurately captured.

The application discloses a device for CPD dummy breathing movement, and relates to the technical field of in-vehicle living body detection targets, which is arranged in a chest cavity of a CPD dummy and comprises a driving motor, a driving gear, a driving rack, a sliding shaft mounting seat, a linear motion bearing, a sliding shaft and a breathing push plate. The driving motor is fixed with the driving gear through a driving shaft thereof, the driving rack is fixed on the sliding shaft in an axial direction, the driving gear is engaged with the driving rack, the sliding shaft is slidably connected with the sliding shaft mounting seat through the linear motion bearing, and the breathing push plate is fixed on one side of the sliding shaft. The driving motor drives the driving gear to rotate clockwise or counterclockwise, and drives the sliding shaft to move linearly through the meshing transmission of the gear and the rack, so that the breathing movement of the dummy is realized. The technical scheme of the application adopts the motor driving and gear and rack transmission mode to realize the breathing movement simulation, has small operation difficulty and good flexible adjustment, and can be applied to application scenes with high requirements on breathing frequency and amplitude.

A method and system for reconstructing motion compensated nuclear images of an object and an arrangement for acquiring nuclear images and a computer program for performing the method are provided. The reconstruction method comprises receiving nuclear image data for a plurality of motion states, reconstructing the data into images for each motion state and computing a deformation vector field for each state for mapping the images onto a reference motion state. Computing the deformation vector field comprises providing an initial vector field, defining at least one rigid region of the object, incorporating the rigid region into the initial deformation vector field and computing the deformation vector field with the incorporated rigid region. The method further comprises mapping the reconstructed images of each motion state onto the reference state using the deformation vector field and combining the mapped nuclear images into a motion compensated nuclear image.

The invention relates to the technical field of artificial intelligence and image recognition, and discloses a garment quality intelligent detection method in a garment processing process. The method comprises the following steps: acquiring three-dimensional point cloud data of a target human body and constructing a parameterized human body grid model; obtaining a two-dimensional garment cutting piece digital template, and generating an initial three-dimensional garment model through virtual stitching; simulating dynamic deformation under excitation of gravity, inertia force and respiratory movement in a physical simulation engine to obtain a final clothing model in a steady wearing state; calculating a local gap distribution field with the human body model, and extracting gap mean values, variances and gradient features of key areas such as shoulders, a chest and a waist; and inputting the features into a pre-trained multi-layer perceptron model, and outputting a 0-100-score stereo fit degree quantitative score. According to the method, real person try-on is not needed, high-precision, automatic and repeatable fit degree evaluation is realized, and the garment quality inspection efficiency and the model optimization capability are remarkably improved.

Various methods and systems for x-ray imaging are provided. In one embodiment, a method includes: acquiring a plurality of fluoroscopic images depicting an interventional tool positioned relative to an anatomical structure of interest of a patient; segmenting the interventional tool in the plurality of fluoroscopic images; measuring motion of the patient in the plurality of fluoroscopic images; correcting the plurality of fluoroscopic images to remove the motion of the patient; registering the segmented interventional tool to the anatomical structure of interest in the corrected plurality of fluoroscopic images; and displaying an image with the segmented interventional tool registered to the anatomical structure of interest. In this way, a physician can view the position and movement of an interventional tool located within a patient's body relative to a static image of the anatomical structure without motion artifacts or errors caused by patient motion such as respiratory motion or cardiac motion.