318 results about "Head movements" patented technology

The invention relates to the technical field of medical rehabilitation, and discloses a vestibular function and cognitive function rehabilitation training system and method based on virtual reality, and the rehabilitation training system comprises a hardware platform, a software platform and a server. The hardware platform comprises VR interaction equipment, a head motion tracking sensor and calculation and display equipment; the software platform is integrated with a user management module, a visual stimulation module, a vestibular rehabilitation training module, a cognitive evaluation and training module, a dynamic visual acuity evaluation module and a data management and analysis module. By combining black and white chess grid visual stimulation, standardized vestibular rehabilitation tasks, spatial cognitive testing and DVA objective monitoring, synchronous evaluation and personalized collaborative intervention of vestibular functions and cognitive functions of dizzy patients are realized. According to the method, the problems of boring traditional rehabilitation means, subjective evaluation and lack of quantitative feedback are solved, and the scientificity, interestingness and curative effect testability of rehabilitation training are remarkably improved.

The invention relates to the technical field of auxiliary training, and discloses an AR auxiliary training system for improving the diagnosis and treatment capability of general practitioners on undifferentiated diseases, and an immersive training environment is constructed by adopting an augmented reality technology. The system comprises an environment sensing module, a space positioning module, a case data module, a virtual rendering module, an interactive acquisition module, an intelligent response module, a state control module and an evaluation calculation module. The environment sensing module adopts an RGB-D camera and an inertial measurement unit to collect environment and head movement data of a user; the spatial positioning module determines a virtual patient placement position based on an SLAM algorithm; the virtual rendering module renders a three-dimensional virtual patient in a real environment; the interaction acquisition module supports voice and gesture multi-mode interaction; the intelligent response module generates an intelligent patient answer; the evaluation calculation module carries out comprehensive evaluation from three dimensions. The invention provides a highly immersive and intelligent training environment, and has the advantages of low cost, reusability and high standardization degree.

The invention discloses an eye movement tracking method and system based on multi-modal fusion, and particularly relates to the technical field of eye movement tracking, and the method comprises the steps: collecting a face image, an eye image and a head movement parameter of a user through an RGB camera, an infrared camera and an IMU which are synchronously arranged; the signals are processed in parallel, sight line direction vectors based on the face and the eyes and reliability measurement of the sight line direction vectors are extracted respectively, and the head space posture is calculated; dynamically selecting high-confidence cooperation, master-slave compensation or conflict arbitration strategies according to reliability measurement, and fusing to generate an initial sight direction; and mapping the direction to a display plane to obtain an initial fixation coordinate, performing optimization calibration in combination with visual saliency analysis of screen content, and outputting a final fixation point coordinate. The system comprises a signal acquisition and processing module, a parallel computing module, a multi-strategy fusion decision-making module and an output optimization module. According to the invention, through multi-modal information fusion and dynamic strategy selection, the precision and robustness of eye movement tracking are significantly improved.

The invention discloses a piezoelectric film partition dynamic focusing system and method for intelligent glasses. The piezoelectric film partition dynamic focusing system comprises an optical modulation layer, a sensing layer, a control engine, a hybrid driving layer and a closed loop verification module. The optical modulation layer is integrated with an N * M piezoelectric film array, each subarea is provided with an independent electrode and a gradient thickness structure, and intervals are filled with low-modulus insulating polymers. The sensing layer is used for acquiring fixation point, diopter, temperature and head movement information of a wearer; and the control engine executes voltage mapping, temperature drift compensation and resonance suppression according to the sensing data, and drives the hybrid driving layer to complete deformation and displacement compensation. And the closed-loop verification module outputs a defocusing error in real time and feeds back a correction voltage. According to the invention, high-response, low-power-consumption and stable dynamic focusing is realized, and the visual adaptability is improved.

A method for motion synchronization-based head pose estimation, by a head mounted display (HMD) device and an HMD device for performing the same are provided. The method includes receiving, by the HMD device, motion data from a plurality of motion sensors of the HMD device, receiving, by the HMD device, a plurality of image frames from at least one simultaneous localization and mapping SLAM camera of the HMD device, estimating, by the HMD device, a plurality of motion parameters of head movements of a user from the plurality of image frames received from memory, generating, by the HMD device, a filtered subset of the motion data received from the plurality of motion sensors based on the plurality of motion parameters of the head movements, synchronizing, by the HMD device, the plurality of image frames received from the memory and filtered subset of motion data, and estimating, by the HMD device, the head pose based on the synchronized plurality of image frames and motion data.

The invention relates to the technical field of intelligent glasses, and discloses an intelligent glasses wearing identification method based on multi-modal perception, and the method comprises the steps: collecting the capacitance change rate, the facial contour matching degree, the body surface temperature, the vital signs, the head attitude angle and other multi-source feature data in real time, generating five groups of feature data, and carrying out the standardization processing and weight fusion, forming a comprehensive feature vector; calculating a preliminary confidence score by combining a dynamic weight adjustment mechanism and a rule engine, and correcting a deviation caused by head movement; judging a wearing state according to the corrected confidence score, outputting a label, and realizing function control in linkage with a gesture interaction module; the abnormal state triggers local or cloud alarm; the sampling frequency of the sensor is dynamically adjusted according to the wearing state, the frequency is reduced to 1Hz when the sensor is not worn, the frequency is improved to 10Hz when the sensor is worn so as to enhance the response precision, and the decision process is only triggered when the feature is suddenly changed in combination with an event-driven strategy. According to the invention, the precision and the reliability can be improved, and low-power-consumption design is realized.

The invention discloses a landscape object identification and explanation method and system, a medium and a product, and relates to the technical field of augmented reality. The method comprises the following steps: when the head motion state of a user is stable, triggering a camera to collect and recognize a single-frame image, matching a recognition result with a regional knowledge base, and generating a candidate object list and coarse-grained poses which are sorted according to spatial probability and historical popularity; performing feature point matching on a current frame and an ideal frame in the video stream, and calculating a fine-grained pose of a target landscape in the candidate object list relative to a camera coordinate system according to a matched target feature point; according to the fine-grained pose and the real-time eye movement data, determining a drop point part of the sight line of the user on the target landscape, forming a multi-dimensional query vector according to the drop point part, the intention of the user and the environment context parameters, and generating multimedia explanation content; and carrying out fusion rendering on the multimedia explanation content and the real-time video stream, and outputting and displaying. By implementing the technical scheme, the personalized multimedia explanation content can be generated.

The invention provides a virtual data transmission flow control system for an MR head-mounted display. The virtual data transmission flow control system comprises a dynamic key area identification module, a self-adaptive flow scheduling module, a low-delay transmission optimization module and a cross-layer collaborative optimization module, wherein the dynamic key region recognition module is used for recognizing a complex key region in an MR environment in real time based on a user fixation point, a head movement track and scene semantic analysis, and the complex key region comprises a high-dynamic interaction object, a visual focus region and a real-time changing virtual scene element; the dynamic key region identification module obtains user behavior data through multi-modal sensor fusion, predicts the change trend of a user concerned region in combination with a deep learning model, and outputs the priority weight of a key region; the adaptive traffic scheduling module comprises a hierarchical coding unit, a dynamic bandwidth allocation unit and a redundancy control unit; and the self-adaptive flow scheduling module is connected with the dynamic key area identification module.

The invention discloses an optical and neural feedback multi-modal data analysis method for a nerve regulation target, and belongs to the technical field of cranial nerve treatment, and the method specifically comprises the steps: receiving a head movement instruction of a patient through an interactive interface, pausing transcranial magnetic stimulation after receiving the instruction, and switching to a head movement monitoring state; an infrared optical navigation device is combined with a magnetic resonance image to construct an individualized brain three-dimensional model, head position changes are tracked in real time, and autonomic nerve feedback signals are collected at the same time; synchronously aligning the head coordinates with the neural feedback signals to generate a multi-modal data set, and analyzing relevance to obtain real-time regulation and control parameters; the positioning and stimulation intensity of the transcranial magnetic stimulation coil are adaptively adjusted according to the parameters, and related information is displayed on a treatment interface; after the head of the patient finishes moving and is stable, a rapid re-calibration process is automatically triggered, high-precision monitoring is recovered, and magnetic stimulation output is reactivated; according to the invention, the treatment stability and adaptability are improved.

In some embodiments, a method comprises executing, by a head-tracked audio system, a first algorithm configured to dynamically update a forward head angle and a spatial orientation in response to a detected head movement, and a second algorithm configured to adjust a recentering filter based on the detected head movements, and maintaining, by the head-tracked audio system through execution of the first algorithm and the second algorithm, a spatial audio placement relative to a wearer during the detected head movements.

To provide a coating system that can improve the property of discharging air bubbles and foreign matter from inside a coating head unit.SOLUTION: A painting robot 10 comprises: a painting head unit 50 comprising a painting head 53; a robot arm R1, which moves the painting head unit 50 to a desired position; a head control unit 90, which controls operation of the painting head 53; and a control unit comprising a robot arm control unit 70, which controls operation of the robot arm R1. The robot arm control unit 70 is configured to perform: head movement control to move the painting head unit 50 to shift a posture of the painting head unit 50 from an ejection position of ejecting droplets, so as to move air bubbles B1 present in the painting head 53; and posture return control to return the posture of the painting head unit 50 to the ejection position. The head control unit 90 is configured to perform droplet ejection control to eject droplets from a nozzle 54 during or immediately after the posture return control.SELECTED DRAWING: Figure 2

The invention provides a virtual reality display method and system, a computer and a storage medium. The method comprises the following steps: collecting sight movement data and head movement data of a user; predicting a fixation point area at the next moment based on the historical movement track of the fixation point area; according to the scene depth information, the sight line moving speed and the head motion data of the fixation point area at the next moment, predicting the predicted focal plane depth at the next moment, and dynamically adjusting the configuration of the micro-lens array in the optical assembly to match the predicted focal plane depth. The depth of a focal plane is predicted through fusion data of eye movement tracking and an inertial measurement unit, the configuration of a micro-lens array is dynamically adjusted, meanwhile, a display picture is divided into a fixation point area, a fuzzy display area and an atmosphere rendering area, and based on differentiation rendering processing, the convergence adjustment conflicts of vision are remarkably relieved, the graphic calculation load is reduced, and the display quality is improved. And a self-adaptive high-definition display effect is realized.

The invention discloses a multifunctional automatic comprehensive optometry combined operation table and a use method thereof. The operating platform comprises a mechanical main body structure, a posture sensing system and a central processing and control unit. The mechanical main body structure comprises an optometry chair driven by a rotating disc, a lifting mechanism and an electric rotating shaft, and the posture sensing system is composed of a sitting and leaning posture recognition mechanism used for recognizing body postures and a head posture recognition mechanism used for capturing head movement. The central processing and control unit judges the posture of the optometry person according to the sensing data, and if the posture does not meet the preset standard, the seat height, the backrest angle and the horizontal position are adjusted through voice prompt and an automatic driving mechanism; when the posture reaches the standard, the optometry equipment is automatically controlled to complete operation, automatic and accurate correction of the posture before optometry and intelligentization of the optometry process are achieved, and the accuracy and efficiency of optometry results are effectively improved.

The invention discloses a forehead flexible sensing method and system, and relates to the technical field of flexible sensing, and the method comprises the following steps: S1, obtaining microenvironment sensing data; s2, generating an original data frame; s3, performing invalid frame inducement classification on the original data frames; s4, distinguishing valid frames from invalid frames; s5, performing directional remining and parameter correction of remining-mining linkage on the judged invalid frames; and S6, dynamically adjusting the regulation and control parameters. According to the invention, through multi-dimensional microenvironment perception grading, invalid frame inducement classification and discrimination and threshold value weighting dynamic linkage fine tuning, in combination with a steaming-sampling linkage directional resampling mode, microenvironment dynamic change characteristics such as conductivity, temperature, contact impedance and the like caused by skin sweat secretion, environment temperature and humidity conduction and head actions in a wearing process can be captured; and adaptive acquisition parameters are dynamically matched according to an actual grading result of the microenvironment, so that the problem of gradual distortion of core physiological signals such as electroencephalogram and PPG caused by microenvironment change is avoided.

The invention discloses a dynamic privacy mosaic generation system based on intelligent glasses, and relates to the field of privacy protection of wearable equipment, and the dynamic privacy mosaic generation system comprises a head motion sensing module which is used for collecting inertial measurement data of the intelligent glasses; the visual field prediction module is used for calculating the head movement trend of the user based on the inertial measurement data and determining a predicted fixation area; the privacy target identification module is used for identifying a privacy target in the predicted fixation area and acquiring a privacy score; the fuzzy control module is used for calculating the fuzzy intensity of each pixel point according to the head movement trend, the angle difference between the target position and the fixation center and the privacy score; the image synthesis module is used for generating a fuzzy mask and fusing the fuzzy mask with the image frame; and the image output module is used for outputting the image frame superposed with the fuzzy mask to display equipment or a storage medium. According to the method, the problem of short-time exposure of privacy information in an image identification delay process is solved.

A media system and a method of using the media system to reproduce spatial audio based on head-to-torso orientation, are described. The method includes determining a head-to-source orientation and a head-to-torso orientation based on head orientation data generated by a head tracking device. Determining the head-to-torso orientation includes determining torso movements based on movements of the head. The torso can be determined to move when the head movements meet a head movement condition, such as a predetermined angle of movement or pattern of movement. A binaural audio filter that is based on a head-related transfer function corresponding to both the head-to-source orientation and the head-to-torso orientation is applied to an audio input signal to generate an audio output signal. The audio output signal is played to accurately recreate spatial audio having sounds emitted to the user by a sound source. Other aspects are also described and claimed.

The invention discloses a virtual reality dynamic field angle adjusting system and method, and relates to the technical field of virtual reality, and the system comprises a multi-source signal collection module which is used for collecting eye movement tracking data and head movement data of a user in a virtual reality environment in real time, and the head movement data comprises head angular velocity and angular acceleration information; the nystagmus signal extraction module is connected with the multi-source signal acquisition module; the vestibular mismatch index calculation engine is connected with the nystagmus signal extraction module and is used for calculating the nystagmus strength index; the self-adaptive field angle controller is connected with the vestibular mismatch index calculation engine; and the rendering pipeline adaptation module is connected with the adaptive field angle controller. By mining neglected nystagmus physiological signals in eye movement tracking data and combining multi-dimensional information fusion and personalized parameter adaptation, dynamic adjustment of a field angle is realized, and the problem of dizziness and individual difference adaptation caused by a fixed field angle in an existing virtual reality system are solved.

The invention discloses a heart rate measurement method and system based on time-frequency fusion and dynamic gating attention, and the method comprises the steps: firstly carrying out the preprocessing of an acquired face video sequence, and obtaining a stable input image sequence; thirdly, extracting a three-dimensional feature map and time sequence features which change along with time through a time-frequency convolutional network; a time-frequency fusion module is constructed, complementary time-frequency features are obtained through time-domain convolution and frequency-domain wavelet decomposition, and feature adaptive fusion is realized by using a dynamic gating mechanism; and the local time relevance of the features is enhanced through a local sliding window attention module. And inputting the three-dimensional convolution features into a prediction module, performing regression to generate a remote photoelectric volume pulse wave signal, and performing frequency domain analysis on the signal to estimate the heart rate. According to the method, pulse related signals can be stably extracted under the conditions of illumination variation and slight head movement, and the method has high heart rate estimation precision and environment robustness and can be used for non-contact vital sign monitoring application.

The invention relates to the technical field of man-machine interaction, and discloses an eye movement tracking method, intelligent glasses, a mobile terminal and an eye movement tracking system.The method comprises the steps that current head movement data of a wearer is collected and sent to the mobile terminal; receiving the current gazing direction of the wearing user fed back by the mobile terminal, and tracking the eye movement of the wearing user according to the current gazing direction; wherein the current gazing direction is obtained through the mobile terminal according to the current head movement data and a current eyeball image of the wearing user, and the current eyeball image is obtained by shooting eyeballs of the wearing user through a camera. Since the mobile terminal with the camera arranged outside is utilized to complete eyeball collection and fixation direction determination of the wearing user, an independent camera and an independent computing power unit do not need to be arranged in the intelligent glasses, and the size of the intelligent glasses is reduced.

The invention relates to the technical field of early screening of child autism, in particular to a child autism recognition method and system based on fNIRS signals and wearable equipment, and the method comprises the steps: collecting forehead multi-band cerebral blood flow signals and head movement data of a child through an fNIRS intelligent helmet; the method comprises the following steps: eliminating motion artifacts by using an edge computing chip, obtaining a noise-reduced fNIRS signal through adaptive filtering, extracting a time-domain signal slope, a frequency-domain wavelet energy entropy and an inter-channel function connection matrix, and processing time-frequency features and topological features by using a 1D convolution branch and a graph convolution branch by means of a double-current neural network, thereby obtaining a noise-reduced fNIRS signal. After features are fused, an autism risk probability value is output through channel attention weighting, a screening grade report is generated and transmitted to a mobile terminal, the system comprises a signal acquisition unit, an edge processing unit, an intelligent analysis unit and an interactive output unit, the system is adaptive to daily scenes of children, and the screening precision is improved.

To provide a balance function management system for balance function state information generation and a balance function rehabilitation program.SOLUTION: A memory configured to store at least one processor and at least one artificial neural network model that stores instructions executable by the processor and is executed on a computing device, wherein the at least one processor is configured to input frame images of n (where n is a natural number) videos obtained by photographing a subject through n cameras to the at least one artificial neural network model, At least one of information related to the coordinates of the head, the coordinates of the center of the pupil, and the phase change of the eyeball of the subject according to the order of the frame images of the m-th (m is a natural number from 1 to n) moving image may be acquired, and information related to the movement of the head and the movement of the eyeball for generating the balance state information or performing the balance rehabilitation program may be generated using the acquired information.SELECTED DRAWING: Figure 1

The invention discloses an intelligent cooperative control system and method for vestibular function inspection. The invention discloses an intelligent cooperative control system and method for vestibular function examination, and belongs to the technical field of medical instruments. The system comprises a cold and hot air perfusion module, a dynamic visual target module, a head posture detection module, a sight distance detection module, an eye movement acquisition module, a voice interaction module, an adjustable examination chair and a central controller. The central controller realizes closed-loop control based on multi-source sensing data: during a cold and hot test, if the elevation angle of the head deviates from 30 degrees + / -2 degrees, stimulation is paused and voice prompt is performed; during visual target testing, visual target parameters are automatically compensated according to the actually measured sight distance of 1.5 m + / -0.1 m so as to maintain a constant visual angle, and the upright state (90 degrees + / -2 degrees) of the head is verified; abnormities such as eye closing more than or equal to 2 seconds or head movement more than or equal to 5 degrees per second are monitored in the whole process, graded voice intervention is implemented, and the abnormities are paused. Body position conversion is guided by voice, multi-source data are synchronously stored, and peripheral and central function correlation analysis is supported. According to the invention, the accuracy and compliance of inspection can be improved.

The invention relates to the technical field of brain-computer interfaces, in particular to a wearable helmet brain-computer control system and a wearable helmet brain-computer control method. The wearable helmet brain-computer control system comprises a multi-mode sensor assembly, an inertial measurement unit, an inertial measurement unit, an inertial measurement unit and a brain-computer interface control module, and the multi-mode sensor assembly is used for synchronously collecting electroencephalogram, electrocardiogram and electromyogram physiological signals and head movement data of the inertial measurement unit; the motion artifact removing module is used for predicting motion artifacts through a Hammerstein-Wiener model on the basis of IMU (Inertial Measurement Unit) data, separating artifact components in mixed electroencephalogram signals by combining an independent component analysis model, and reconstructing pure electroencephalogram signals; the central processor is used for carrying out feature extraction and decoding on the pure electroencephalogram signal and generating a control instruction; the control instruction interface is used for outputting the control instruction to external equipment; the storage module is used for storing an original signal and a processing result; the wireless transmission module is used for realizing data interaction with a terminal; the core problems that a traditional device is poor in signal quality and unstable in control in a dynamic environment are effectively solved.

The invention provides a smokeless intelligent accurate control method for prevention and control of juvenile myopia. The smokeless intelligent accurate control method comprises the steps of eye movement and facial muscle multi-mode acquisition and noise filtering, dynamic graph convolutional network and spatial-temporal feature fusion analysis, blink and head movement prediction and intelligent moxibustion path adjustment. By constructing a resting state eye movement behavior mode library, coupling face and head dynamic data, utilizing multi-mode feature fusion and AI hierarchical control, accurately recognizing blinking and head disturbance, and generating an avoidance track and a dynamic moxibustion therapy power regulation strategy in advance, the method can effectively avoid periorbital sensitive areas, keep the temperature in the moxibustion therapy process constant, and improve the moxibustion therapy effect. The response speed and path stability are improved, and moxibustion safety and continuity are guaranteed.

The invention discloses an intelligent safety helmet management method and device based on the Internet of Things, and belongs to the technical field of wireless communication, and the method comprises the steps: obtaining head motion data collected by an inertial measurement unit in an intelligent safety helmet, and environment state data broadcasted by a wireless beacon deployed in an operation environment; analyzing the head movement data based on a preset dynamic model, generating physiological state features of the person, analyzing the environment state data, and identifying environment risk features; fusing the human physiological state features and the environmental risk features to generate a dynamic coupling risk level; and triggering a corresponding closed-loop safety intervention action based on the dynamic coupling risk level. According to the method, personnel physiological state features and position-based environment risk features are obtained, fusion operation is performed on the two features to generate a dynamic coupling risk level, and then a closed-loop safety intervention action is triggered, so that accurate identification and active intervention of personnel and environment coupling risks can be realized.

The invention relates to a personalized virtual makeup trying system and method based on multi-modal interaction and three-dimensional reconstruction, and the method comprises the steps: collecting a face video stream through a mobile terminal by a camera capture module, and generating multi-modal sensing data through space-time alignment; the three-dimensional reconstruction module fuses the expression change and the head motion trail to construct a dynamic face model; the sensor fusion module analyzes a reference makeup image, a voice instruction and an environment illumination parameter uploaded by a user, and generates a makeup volume measuring scheme through cross-modal semantic fusion; the interface synchronization module simulates the physical interaction effect of skin and cosmetics on the dynamic face model to generate an environment-adaptive virtual makeup trying effect, so that the problems of dynamic distortion, multi-mode intention splitting, poor environment adaptability, insufficient makeup effect physical restoration and the like in the traditional makeup trying technology are solved; makeup fitting, complex intention analysis, illumination change real-time adaptation and real restoration of cosmetic materials during large-angle rotation of the head are achieved, and the device can be widely applied to the fields of beauty makeup retail, medical beauty rehabilitation and the like.

The present disclosure relates to a face data generation method and device, computer equipment and a storage medium, and belongs to the technical field of computers. The method comprises: generating lower half face movement features, upper half face movement features and head movement features of a virtual object when the virtual object emits input audio based on audio features of the input audio and face features of standard face data of the virtual object; generating a face offset of the virtual object when the virtual object emits the input audio based on the lower half face movement features, the upper half face movement features and the head movement features; and generating predicted face data of the virtual object when the virtual object emits the input audio based on the face offset and the standard face data. The present disclosure takes into account different reflection modes of different regions of the face for the input audio, and the movement features of each region have better sensitivity and adaptability to the input audio, thereby ensuring that the expression changes of the virtual object in the face animation generated by the multiple frames of predicted face data are coherent and natural.

The present application belongs to the technical field of intelligent wearable devices, and provides a balance risk early warning method for wearable glasses, which comprises: collecting real-time head movement data of a current period by a head inertia sensor arranged in a glasses leg, and performing step frequency availability determination based on a reference benchmark constructed based on historical head movement data. Through multi-dimensional consistency evaluation and in combination with a dynamic reference benchmark established based on personal historical data of a user, stable periodic gait and a mobile state with weakened step frequency characteristics can be accurately distinguished, and through a three-level collaborative analysis system of rapid screening, deep compensation and fine review, balance risk early warning is realized, which is especially suitable for daily life monitoring of middle-aged and elderly groups and people with decreased balance function, and can still maintain effective risk identification ability in complex scenes such as slow walking, turning, standing and daily activities, which are prone to failure in traditional methods, and can realize daily health monitoring and reminding, thereby providing a solution for preventing falls and ensuring user safety.

A system adapted to interact with a user by monitoring activity of a user's eye gaze, the system comprising: a user web camera configured to determine a location at which the user's eyes gaze on a user display configured to display digital content to the user; an operator display configured to view the live interaction of the eye gaze of the user from a movement of the eye gaze controlled cursor projected in the operator display; a processor having a gaze estimation module for receiving eye movement and head movement signals from the user web camera as calibration data for estimating eye gaze, the processor configured to: generate an interactive stimulus to the user display; stimulating an interaction with the interaction via a user's gaze-based interaction or blink-based interaction; and analyzing and determining a user focus based on eye tracking of the interaction from the interaction stimulus.

This invention discloses a multi-position adjustable rehabilitation treatment bed, belonging to the field of medical device technology, including a support platform; a tray is provided on the support platform; a lifting adjustment mechanism is provided on the support platform to tilt the tray upwards; a head adjustment mechanism is provided on the front side of the tray to adjust the height of the patient's head; and a lower limb adjustment mechanism is provided on the rear side of the tray to adjust the patient's lower limbs in multiple positions. This invention enables rehabilitation movements such as standing up, leg raising, knee flexion, and head movement without requiring medical staff to manually lift and support the patient's limbs. It changes the traditional situation where rehabilitation exercises require multiple medical staff to operate together, effectively reducing the physical exertion of medical staff, saving the human resource cost of clinical rehabilitation, and solving the problems of high human resource input and high operational difficulty in traditional manual rehabilitation.