42 results about "Patient Motion" patented technology

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.

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.

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.

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.

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.

One or more new metrics are introduced into the treatment planning process. More specifically, a correcting factor / metric referred to herein as the critical / repair ratio index is introduced, and / or a correcting factor / metric referred to herein as the spatial periodicity of critical isodose value is introduced. By using these metrics, the expected sparing from the spatial distribution of dose is better accounted for in treatment modalities including spatially fractionated radiation therapy (SFRT) in general and SFRT with ultra-high dose rates in particular. According to a treatment planning strategy, the target can be covered by a Spread-Out Bragg Peak, to optimize and / or homogenize the dose distribution at the target level but still benefit from the sparing effect of SFRT at the healthy tissue level. Delivery techniques include a dynamic focusing technique and a magnetic beam steering technique. Enhancing dose rate enables maximizing the peak-to-valley dose distribution with SFRT despite patient motion.

The invention discloses a human motion monitoring system, method and device and a storage medium. In the human motion monitoring system, an image acquisition module acquires N continuous frames of images of a human body on a diagnostic bed through multiple cameras. The image processing module extracts each frame of human body ROI, determines a single frame and integrates ROI area features. And the state recognition module judges the shielding state of each camera based on the characteristics. The motion detection module dynamically determines a human body motion energy value for an unshielded or semi-shielded camera. And the alarm module gives an alarm when a preset condition is met by combining the shielding state and the human body motion energy value. The scheme adopts pure visual analysis, does not depend on internal data of SPECT equipment, has the advantages of flexible deployment and strong compatibility, can effectively identify the occlusion state and accurately detect the motion of the patient, is beneficial to reducing motion artifacts in SPECT imaging, and ensures the imaging quality.

Disclosed herein are systems and methods for applying a stimulus to a target object based on sensed physiological data relating to the target object. A stimulation threshold for when to trigger stimulation of the target object based on a baseline indicating a need for stimulation can be continually adjusted based on the sensed data to more accurately activate stimulation at the appropriate time. To further enhance accuracy, the system can incorporate data from additional sensors, such as an accelerometer, to distinguish between true physiological changes and artifacts caused by patient motion or other bodily activities. This allows for a more robust and reliable calculation of the dynamic baseline.

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.

The utility model relates to the field of walking tests, in particular to a footpath mark monitoring device for a six-minute walking test, which comprises a test footpath and a movable guide rail, distance marks are arranged on the surface of the test footpath, the movable guide rail is arranged on one side of the test footpath, and a mark area is arranged on the other side of the test footpath. A moving seat is arranged at the upper end of the movable guide rail, guide sliding seats are fixedly mounted on the two sides of the lower end face of the moving seat and slidably connected with the upper end of the movable guide rail, and moving wheels are arranged on the two sides of the driving box; the non-invasive cardiac output monitor is additionally arranged, so that the motion state of a patient is synchronously recorded, hemodynamic parameters of the human body are continuously monitored in real time, the change of central functions in the resting, moving and motion processes is evaluated from the angle of hemodynamics, the test effect is improved, the movable guide rail is used for guiding, the movable seat synchronously follows to move, and the test efficiency is improved. And when the patient moves, the noninvasive cardiac output monitor is driven to move synchronously, so that the use of the monitor is facilitated.

The application discloses a Parkinson quantitative early diagnosis system based on behavior feature recognition and belongs to the technical field of Parkinson diagnosis. The system comprises an intelligent acquisition device, a quantitative diagnosis platform and an intelligent control treatment device. The intelligent acquisition device is used for collecting patient motion data, patient voice data, patient writing data and patient facial data, determining patient behavior real-time data based on the Internet of Things, and transmitting the patient behavior real-time data based on the Internet of Things to the quantitative diagnosis platform based on a wireless network. The quantitative diagnosis platform is used for pre-processing and analyzing the patient behavior real-time data based on the Internet of Things, performing Parkinson quantitative early diagnosis on the patient, and performing intelligent control treatment on the patient according to the patient diagnosis result. The application solves the problem that the existing Parkinson quantitative early diagnosis on the patient cannot be performed based on behavior feature recognition, and the diagnosis effect on Parkinson patients is poor. The application can perform Parkinson quantitative early diagnosis on the patient based on behavior feature recognition, and can improve the diagnosis effect on Parkinson patients.

The invention discloses a digital standardized patient action feedback method and device, equipment and a medium, and relates to the technical field of medical simulation teaching and artificial intelligence, and the method comprises the steps: obtaining current question and answer information issued by a user based on an inquiry training task through a preset interaction interface; determining a target action feedback instruction corresponding to the current question and answer information, and searching a target action video clip matched with the target action feedback instruction in a preset video library; the preset video library is used for storing preset action video clips corresponding to the action feedback instructions; generating a target lip animation corresponding to target voice feedback content corresponding to the current question and answer information; and synthesizing the target action video clip and the target lip animation to obtain a target feedback video of the digital standardized patient, and displaying the target feedback video of the digital standardized patient on a display interface. And the authenticity and the system operation efficiency of digital standardized patient feedback are improved in an inquiry training scene.

A wearable electronic device includes a light sensor configured to sense ambient light, a timer providing a time indicator, a motion sensing unit that senses motion and outputs motion data in dependence on the sensed motion, and a data storage that receives and stores the motion data or other data derived therefrom in association with the time indicator. The timer starts providing the time indicator and the motion sensing unit starts sensing motion after ambient light is sensed by the light sensor.

The invention discloses a motion information monitoring device for a chronic kidney disease patient. The motion information monitoring device comprises a monitor, a mobile phone terminal APP and a medical data receiving terminal. The monitor comprises an MCU control module, and the MCU control module is connected with a multi-dimensional sensor group, an internal fistula protection module, a communication module, a display and early warning module and a power supply and endurance management module. The multi-dimensional sensor group comprises a basic motion sensor, a nephropathy exclusive physiological sensor and an environment adaptive sensor; the MCU control module is internally provided with a CKD patient motion risk algorithm model, and motion threshold values and early warning rules can be customized according to the kidney function stages of patients. The communication module supports two-way transmission of data to a patient mobile phone terminal APP and a medical data receiving terminal, the internal fistula protection module is used for protecting internal fistula of a patient, and the display and early warning module is used for displaying monitored data and giving out early warning when the data are abnormal; and the power supply and endurance management module is used for supplying power to the monitor.

A device (10), system, method and computer-program product are disclosed for detecting movement of a subject in a diagnostic imaging examination. The device comprises a camera / 3D surface scanning system (11) and an input (14) for receiving a trigger to indicate that a current spatial configuration of the subject is to be maintained for the examination. The device comprises a processor (12) and an output (13), in which the processor (12) is adapted for acquiring reference data of the subject using the camera / 3D system when said trigger is received, and for acquiring further data of the subject using the camera / 3D system after acquiring said reference data. The processor is adapted to compare the reference data, which represents a reference state of the subject at substantially the time that the trigger was received, to the further data, which represents a more recent state of the subject. The processor is adapted to provide output data via said output (13), in which this output data is representative of the comparison of the further data to the reference data so as to indicate movement of the subject with respect to the reference state of the subject.