55 results about "Patient Motion" patented technology

The invention discloses a patient rehabilitation training data acquisition method and system based on visual identification, and relates to the technical field of rehabilitation training data acquisition, and the method comprises the steps: carrying out the image segmentation of a patient rehabilitation training video through a deep learning model, and separating a patient motion feature region from the patient rehabilitation training video; marking key skeleton nodes in the patient motion feature region, and establishing a three-dimensional coordinate system of the key skeleton nodes; calculating a motion angle and displacement data between adjacent skeleton nodes according to the three-dimensional coordinates of the key skeleton nodes; and performing matching degree analysis on the motion angle and displacement data and a preset rehabilitation standard to generate a rehabilitation training score. According to the method, the deep learning model is adopted to perform image segmentation on the rehabilitation training video, the motion feature region of the patient is accurately extracted from the image, and key skeleton nodes are marked and analyzed in combination with the three-dimensional coordinate system, so that accurate acquisition of rehabilitation training data of the patient is realized.

Techniques for adjusting radiotherapy treatment for a patient in real time are provided. The techniques include operations comprising: obtaining, during delivery of a radiotherapy treatment fraction to a patient, one or more images of the patient at a first rate; generating patient motion information at a second rate based on the one or more images obtained at the first rate; receiving, during delivery of the radiotherapy treatment fraction, radiotherapy treatment device settings at a third rate; computing, during delivery of the radiotherapy treatment fraction, dose delivered to the patient with a first level of accuracy based on the generated patient motion information and the radiotherapy treatment device settings; and determining, during delivery of the radiotherapy treatment fraction, a real-time measure of accumulated dose delivered to the patient with a second greater level of accuracy than the first level of accuracy using one or more prior dose computations.

The invention discloses a patient state intelligent monitoring system and method, and relates to the technical field of medical data processing. Comprising the steps that physiological data and microenvironment parameters of a patient are collected through a multi-mode sensor, and an initial data set is formed; performing environmental error correction on the physiological data of the patient by using a dynamic compensation algorithm to generate a preliminary correction data set; calculating motion state characteristic parameters of the patient, and judging whether significant motion artifacts exist or not; for the detected artifact interference signal, correcting the physiological data in the preliminary correction data set by adopting a dynamic artifact removing algorithm to obtain a correction data set; and determining the priority of each physiological data, and combining the correction data set to form real-time output. The method can overcome monitoring data distortion caused by environmental noise, motion artifacts and other problems, improves the precision and reliability of a monitoring result, and has dynamic adaptability and convenience.

An imaging system is for capturing images of a patient during a medical scan. A set of one or more cameras captures images of the patient such that, after applying distortion and perspective correction steps, pixel rows correspond to locations along an axis parallel to the direction of patient support movement and pixel columns correspond to locations along an axis perpendicular to the patient support. Patient motion of interest can then be identified based on image movements in the pixel column direction between sequential captured images. A measure of patient motion can then be derived.

An implantable cardiovascular pressure sensing system can be used to measure blood pressure accurately and safely without any patient intervention. It can include a pressure sensor that makes blood pressure measurements, circuitry for processing and storing the blood pressure measurements, and an antenna for transmitting the processed measurements to an external device (i.e., a device not implanted in the patient). The circuitry can average blood pressure measurements and / or remove artefacts caused by patient motion that is sensed with an accelerometer integrated into implantable cardiovascular pressure sensing system. A multilayer ceramic / polymer coating forms a hermetic seal around the components, preventing leakage or contamination. The implantable cardiovascular pressure sensing system is very versatile: it can be implanted in a blood vessel, next to a blood vessel, in an aneurysm sac, or integrated with another medical implant, such as an Amplatzer septal occluder, and implanted into or next to another vascular structure.

The invention provides a posture analysis and risk assessment method and device based on kinematics feature extraction, and relates to the technical field of medical diagnosis assessment, and the technical scheme is characterized in that the method comprises the steps: collecting the angle data of key joints in the movement process of a patient, and forming a joint angle time sequence; calculating the deviation between each joint angle of the patient and a corresponding joint angle in a predefined standard action template; performing weighted summation on the deviations of the corresponding joint angles to obtain a weighted Euclidean distance; a time window is set, the weighted Euclidean distances in the time window are averaged, a dynamic deviation value is obtained, and the dynamic deviation value reflects the deviation degree between the patient actions in the time window and the standard action template; and dividing the dynamic deviation value into different risk levels according to a preset risk threshold. The attitude analysis and risk assessment method and device based on kinematics feature extraction have the advantages of being high in portability, easy and convenient to operate, rapid in assessment and visual in result.

The invention relates to the technical field of human motion prediction, and discloses an action standardization evaluation method and system based on a human motion prediction algorithm. Specifically, a historical patient motion image sequence and a corresponding real future patient motion image sequence are respectively input into a preset human body posture estimation algorithm to obtain a historical patient motion posture and a real future patient motion posture, a wearable device is not needed, the convenience and the universality are improved, and the cost is reduced. And inputting the historical patient movement postures into a pre-trained human body movement prediction model to obtain a plurality of predicted future patient movement postures. And performing average joint error on each frame of the predicted future patient movement posture and each frame of the real future patient movement posture, and judging whether the patient movement accords with the specification or not according to the error. The motion posture of each patient is predicted through the human body motion prediction model and compared with the real future motion posture of the patient, and accurate capture and personalized evaluation of the motion of the patient are achieved.

The disclosure relates to MRI reconstruction of multiple MRI measurement datasets acquired throughout a measurement time duration. Patient motion can occur during the measurement time duration. Warping operators, sometimes also referred to as motion field, are incorporated into an iterative optimization of the MRI reconstruction.

An ambulatory medical device is provided. The ambulatory medical device includes at least one sensor configured to acquire sensor data descriptive of patient motion and at least one processor coupled to the at least one sensor. The at least one processor is configured to detect the patient motion from the sensor data, and to classify the patient motion.

Devices, systems, and methods used to register medical image data with anatomical positions are disclosed. The image data is captured by an imaging system over a period of time. The positions are determined by one or more modalities over the period of time. The positions are collected into position data, and determinations are made as to which position data is best for registering the image data with patient anatomy and for reconstructing 3D images of the patient anatomy.

This invention relates to the interdisciplinary field of image recognition and intelligent medical technology, specifically disclosing a method for orthopedic rehabilitation movement recognition and assessment based on image recognition. This method acquires patient motion images using a non-invasive multi-view visual sensor, extracts the three-dimensional coordinates of key skeletal points, and constructs a parametric biomechanical digital twin model integrating joint range of motion, muscle force lines, and ligament tension mechanisms. The key point data is input into a graph neural network for posture recognition, and the digital twin model is simultaneously invoked for physical feasibility verification and posture correction. Finally, the spatiotemporal trajectory similarity is calculated using a standard rehabilitation movement template, generating a comprehensive assessment result including movement completion, safety level, and injury risk. This invention, through the above technical solution, improves the robustness, physiological rationality, and clinical safety of movement recognition.

A magnetic resonance imaging system includes a bore, a table configured to support a patient being imaged and movable to move the patient in and out of the bore, a motion sensor, a controller configured to detect patient motion based on changes in an RF signal from the motion sensor. The motion sensor includes a self-resonant spiral (SRS) coil excited by a drive signal to radiate a magnetic field having a predefined resonant frequency and a driver-receiver coupled to the SRS coil and configured to generate the drive signal to excite the SRS coil and to receive the RF signal from the SRS coil. The motion sensor is located such that a portion of the patient is within the magnetic field while the patient is being imaged in the bore.

Devices, systems, and techniques for analyzing video information to objectively identify patient behavior are disclosed. A system may analyze obtained video information of patient motion during a period of time to track one or more anatomical regions through a plurality of frames of the video information and calculate one or more movement parameters of the one or more anatomical regions. The system may also compare the one or more movement parameters to respective criteria for each of a plurality of predetermined patient behaviors and identify the patient behaviors that occurred during the period of time. In some examples, a device may control therapy delivery according to the identified patient behaviors and / or sensed parameters previously calibrated based on the identified patient behaviors.

Systems and techniques can be used to estimate patient state during radiotherapy treatment. For example, a method can include generating, with a preliminary motion model, an extended dictionary of potential patient measurements and corresponding potential patient states. The method can include training, with a machine learning technique, a correspondence motion model that associates input patient measurements with output patient states using the dictionary. The method can include estimating, with a processor, a patient state corresponding to an input image using the correspondence motion model.

The control circuitry is able to access 400 patient-specific multidimensional information and subsequently, at least in part, automatically determine 406 supplementary boundaries for at least a portion of the patient (such as treatment targets and / or one or more organs at risk) based on the multidimensional information. The latter may include determining margins added to the boundaries of at least a portion of the patient. The control circuitry can then, for example, determine 407 the planned treatment volume based at least in part on the supplementary boundaries. These teachings will then allow for the optimization 408 of a patient-specific, radiotherapy-based treatment plan, for example, based on various motion dimensions derived at least in part from the aforementioned multidimensional information.

The application discloses a kind of neural patient rehabilitation training methods based on task training and brain-computer interaction, belong to rehabilitation training technical field, specifically include: based on the motion decoding model corresponding to the training task machine;Real-time acquisition data signal in current rehabilitation training of patient and carry out segmented processing, obtain several independent data blocks, carry out frequency domain conversion to independent data block, extract time-frequency feature and calculate the KL divergence between adjacent data blocks;If the KL divergence of any adjacent independent data block exists is greater than or equal to preset threshold, then obtain historical data signal and modify the motion decoding model, according to the motion decoding model after modification to the patient motion decoding, according to this to patient carries out rehabilitation training, the present application is selected corresponding model according to current rehabilitation training task, dynamic adjustment is combined with real-time signal characteristics, ensure that decoding result and training target are highly matched, improve the rehabilitation training effect of patient.

Devices, systems, and methods used to register medical image data with anatomical positions are disclosed. The image data is captured by an imaging system over a period of time. The positions are determined by one or more modalities over the period of time. The positions are collected into position data, and determinations are made as to which position data is best for registering the image data with patient anatomy and for reconstructing 3D images of the patient anatomy.

The invention provides an upper limb rehabilitation dynamic control method based on three-dimensional visual intention recognition, which comprises the following steps: synchronously acquiring three-dimensional visual observation data of upper limbs of a patient and pose data of an execution mechanism of a rehabilitation mechanical arm, constructing an upper limb pose vector containing an upper limb kinematics state, and associating the upper limb pose vector with an external traction displacement increment; based on the upper limb attitude vector and the external drafting displacement increment, generating a passive attitude reference vector representing the theoretical upper limb attitude under the pure passive drafting condition; calculating a residual error between the actually observed upper limb attitude vector and the passive attitude reference vector, and separating an active movement contribution amount of the patient from the residual error; generating a patient motion intention vector containing direction and intensity information based on the active motion contribution; according to the motion intention vector of the patient, an instruction used for controlling the auxiliary torque of the rehabilitation mechanical arm is generated, the real active intention of the patient can be accurately separated and extracted, and stable and accurate dynamic auxiliary control is achieved accordingly.

Methods and systems related to planning and delivering radiation treatment by modalities that move a radiation source along a trajectory relative to a subject while delivering radiation to the subject are provided. An artificial intelligence (AI) agent trained using reinforcement learning (and / or some other suitable form of machine learning) is used to control radiation delivery parameters in an effort to achieve a desired delivery of radiation therapy. In some embodiments, the AI agent selects appropriate control steps (e.g., radiation delivery parameters for a particular time step) while taking into account patient motion, difference(s) in patient anatomical geometry, etc.

A patient monitoring system and method, using an image acquisition device to acquire video data containing a patient, analyzing the video data to obtain activity information of the patient, and displaying on a display unit the monitoring result and the activity information corresponding to the same patient and generated in the same preset time interval, or calculating the activity correlation result of the monitoring result and the patient motion amplitude, and displaying on the display unit the monitoring result and the activity correlation result corresponding to the same patient and in time, which can effectively assist medical staff in objectively analyzing and evaluating the activity of the patient during diagnosis and treatment.

Disclosed is a bore based medical system comprising a camera carrier configured to be mounted in the bore based medical system and configured to monitor and / or track patient motion within said bore based medical system during radiotherapy, the bore based medical system comprising a rotatable ring-gantry configured to emit a radiotherapy beam focused at an iso-center of the bore based medical system, wherein the ring-gantry is configured to rotate at least partly around a through-going bore having a front side and a back side, configured to receive from said front side, a movable couch configured to be moved into and out from the through-going bore, wherein further the through-going bore comprises an inner side facing an inside of the bore, and wherein the camera carrier is configured to be mounted inside the bore in connection with the inner side of the through-going bore.

An example method is performed by a computing device executing instructions stored in data storage, and includes receiving physiologic monitoring data from a plurality of sensors coupled to a patient, receiving information indicating a measurement of patient motion during the patient care event, determining whether the measurement of patient motion is above a threshold, based on determining whether the measurement of patient motion is above the threshold, generating, for the physiologic monitoring data, a respective quality indicator, analyzing, by the computing device, (i) a combination of the physiologic monitoring data from the plurality of sensors and (ii) the respective quality indicator for the physiologic monitoring data to generate a response dependent upon the combination of the physiologic monitoring data as weighted by the respective quality indicator, and based on analyzing, outputting caregiver feedback by the computing device according to the response.

Provided herein are systems for treating a paralysis patient in need of controlled motion to improve quality of life, and related methods. The systems comprise an implantable system formed from a hub, various electrodes, such as spinal cord (upstream) electrode, periphery nerve (downstream) electrode and an external system formed of communication pod implanted just under the skin, a computing core, and a plurality of motion sensors. A software system, providing AI compatibility are used to supply the computing core, and thereby implanted electrodes, with signal. In this manner, the specially positioned electrodes, upstream of the spinal cord injury and downstream of the spinal cord injury, can provide safe and reliable patient motion.

A system and method for providing and managing a remote patient monitoring (RPM) system. The method is implemented by a central server, an RPM client, and a networked monitoring device. The RPM client is a software program that is executed by a computing device that is connected to the server via a network. The networked monitoring device is implemented as a locator or a smart mobile cart. More specifically, the RPM system can provide a tele-monitor with the ability to remotely monitor multiple patients, control remote cameras, and address abnormal patient situations. The RPM system can enhance tele-monitor effectiveness by detecting patient motion and tracking tele-monitor alertness.

Methods and systems for medical imaging systems are provided. In one embodiment, a method for a medical imaging system includes: acquiring emission data during a positron emission tomography (PET) scan of a patient; reconstructing a series of live PET images while the emission data is being acquired; and tracking motion of the patient during the acquisition based on the series of live PET images. In this way, patient motion during a scan can be identified and compensated for via scan acquisition and / or data processing adjustments, resulting in diagnostic PET images that are reduced in motion artifacts and improved in diagnostic quality.

Visualization and robotic systems and methods utilize preoperative three dimensional (3D) images of patient motion and intraoperative, real-time patient motion information to show a target moving relative to medical tool or to control a robotic medical tool in real-time to track the target while the target is biopsied or treated. The systems and methods involve receiving preoperative 3D images of patient motion, displaying guidance for or controlling a robotic tool for navigating a medical tool near the target based on information from a position sensor disposed on the medical tool, tracking intraoperative 3D patient motion using motion sensors disposed on the patient, determining 3D target motion based on the preoperative 3D images and the tracked patient motion, and controlling the medical tool with the robotic tool to track the 3D target motion or displaying the 3D target motion relative to the medical tool.

A method comprises generating, by a control system, a measured model of an elongate instrument based on a measured state of the elongate instrument. The method further comprises generating, by the control system, a predicted model of the elongate instrument based on a reference state of the elongate instrument and a user command. The method further comprises comparing, by the control system, the measured model with the predicted model. The method further comprises determining, by the control system, whether a patient has moved relative to the elongate instrument based on the comparison.

An apparatus (10), system, method and computer program product for detecting movement of an object in a diagnostic imaging examination are disclosed. The apparatus comprises a camera / 3D surface scanning system (11) and an input (14) for receiving a trigger indicating that a current spatial configuration of the object is to be maintained for inspection. The device comprises a processor (12) and an output (13), where the processor (12) is adapted to acquire reference data of the object using the camera / 3D system upon receipt of said trigger and to acquire further data of the object using the camera / 3D system after acquisition of said reference data. The processor is adapted to compare reference data representing a reference state of the object substantially upon receipt of the trigger with additional data representing an updated near state of the object. The processor is adapted to provide output data via said output (13), where the output data represents a comparison of further data with reference data in order to indicate a movement of the object relative to a reference state of the object.

Methods of monitoring a medical instrument are provided. The methods may include receiving state information from a control system in communication with the medical instrument; detecting motion of at least a portion of the medical instrument and comparing the motion of the portion of the medical instrument with a threshold motion value that is based on the state information received from the control system. The methods may further include generating a communication message for presentation to an operator of the medical instrument based on the comparison of the motion with the threshold motion value. Corresponding systems are also provided.

Systems and methods may be used for estimating instantaneous patient motion (a patient state). The patient state may be estimated based on a 3D reference volume and a stream of images, for example from an image acquisition device. The stream of images may be received in real-time, for example during a radiation therapy treatment. An example method may include encoding the 3D reference volume using a 3D encoder branch of a patient state generator network, encoding the stream of images using a 2D encoder branch of the patient state generator network, and combining the encoded 3D reference volume and the encoded real-time stream of images. The method may include estimating a 3D spatial transform that maps the 3D reference volume to a current patient state by decoding the combined encoding using a 3D decoder branch of the patient state generator network.