A motion and cognitive function integrated evaluation system under data fusion

Abstract

The application relates to a motion and cognitive function integrated evaluation system under data fusion, and belongs to the technical field of motion detection devices. The evaluation system comprises a server and an evaluation platform in communication connection with the server. An interactive unit of the evaluation platform sends instructions to a user according to an evaluation rule, a lower limb detection unit collects action data of the user on a bearing platform, an upper limb detection unit collects action data of the user through a top guide rail and a detection ball, a communication unit is responsible for data interaction with the server, and a control unit controls the upper limb detection unit to execute the instructions. The evaluation system analyzes the action data of the user based on the evaluation rule to evaluate the motion and cognitive ability of the user. The evaluation rule comprises selecting a rule suitable for the user from multiple rules by the server and generating a final rule, and further comprises analyzing the action data of the user by the server to generate real-time evaluation data and subsequent evaluation rules, so that comprehensive and dynamic evaluation of the user function is realized.

Description

Technical Field

[0001] This invention belongs to the field of motion detection device technology, and more specifically, relates to an integrated evaluation system for motion and cognitive functions based on data fusion. Background Technology

[0002] In modern medical rehabilitation, sports training, and cognitive science research, accurate assessment of individual motor and cognitive abilities is of great significance. Traditional methods of motor function assessment often focus on single-dimensional testing, such as analyzing only lower limb motor abilities or focusing only on simple upper limb motor responses. Cognitive ability assessments are also mostly conducted through independent tests, such as memory tests and attention tests, lacking a system that integrates motor and cognitive functions for comprehensive evaluation.

[0003] As research into the overall interaction mechanisms between the brain and body deepens, people have gradually realized the close connection between motor and cognitive functions. For example, when performing complex motor tasks, such as navigating a maze or operating complex machinery, cognitive resources need to be mobilized simultaneously to plan paths and solve potential problems. Conversely, a decline in cognitive ability can also affect an individual's motor performance. For instance, in the elderly, cognitive impairment is often accompanied by a higher risk of falls, reflecting that their motor abilities are also impaired to varying degrees.

[0004] A review of relevant publicly available technologies reveals several key solutions. One proposed system, WO2020176420A1, proposes a sports training system combining cognitive tasks and physical training. This system utilizes multiple input devices to generate ergonomically designed training programs that integrate cognitive and motor abilities, thereby improving the trainee's cognitive and motor coordination. Another proposed system, WO2015057471A3, provides a remote rehabilitation platform for restoring patients' cognitive and motor abilities. This platform allows therapists to interact remotely with patients, providing suitable programs and devices for interactive activities, facilitating convenient remote treatment. Finally, CN109688926B proposes a method for evaluating cognitive and motor disorders or impairments in suspected patients. This method involves running a detection program on a mobile device and having the test subject interact with it. The detection program's methods are adjusted in real-time to analyze the test subject's cognitive and fine motor abilities.

[0005] The above technical solutions all propose using various devices to combine the detection and training of patients' motor and cognitive abilities, but there are currently few efficient and simple integrated assessment systems that can specifically target the motor and cognitive abilities of the elderly.

[0006] The foregoing description of the background art is intended only to facilitate understanding of the invention. This description does not endorse or acknowledge any common general knowledge in the materials mentioned. Summary of the Invention

[0007] The purpose of this invention is to provide an integrated assessment system for motor and cognitive functions based on data fusion, belonging to the field of motion monitoring technology. The assessment system includes a server and an assessment platform connected to it. The interactive unit of the assessment platform issues instructions to the user according to assessment rules. The lower limb detection unit collects the user's movement data (A) on the platform, and the upper limb detection unit collects the user's movement data (B) through a top guide rail and a detection ball. The communication unit is responsible for data interaction with the server, and the control unit controls the upper limb detection unit to execute instructions. The assessment system analyzes the user's movement data based on assessment rules to evaluate the user's motor and cognitive abilities. The assessment rules include the server selecting suitable rules from multiple rules and generating final rules, as well as the server analyzing the user's movement data to generate real-time assessment data and subsequent assessment rules, achieving a comprehensive and dynamic assessment of the user's functions.

[0008] The present invention adopts the following technical solution: an integrated evaluation system for motor and cognitive functions based on data fusion, the evaluation system comprising: a server, and an evaluation platform communicatively connected to the server;

[0009] The evaluation platform includes:

[0010] The interaction unit is configured to send behavioral instructions to the user based on the evaluation rules;

[0011] The lower limb detection unit, installed on the central platform of the evaluation platform, is used to collect data on the user's nails during the evaluation process on the platform. Action data ;

[0012] An upper limb detection unit is located on the upper part of the evaluation platform, including a top guide rail and two or more detection balls suspended from the top guide rail to the front of the user; the detection balls include data collection of the user's action when touching the detection balls;

[0013] The communication unit is configured to submit the A to the server. Action data and B's action data, and receives the data specified by the server. Evaluation Rules ;

[0014] The control unit is configured to receive control instructions generated by the server according to the evaluation rules, so as to control the upper limb detection unit to execute the control instructions;

[0015] The evaluation system, based on the evaluation rules, combines and analyzes the data from Action A and Action B to evaluate the user's athletic and cognitive abilities.

[0016] Preferably, the lower limb detection unit includes a support platform and a sensor layer;

[0017] The support platform is made of a material that can absorb external impacts and is non-slip.

[0018] The sensor layer includes multiple sensors, at least used to detect the user's foot placement and foot pressure, in order to obtain the sensor layer. Action data .

[0019] Preferably, each of the detection balls is equipped with a B sensor group for detecting the timing of the user touching the detection ball and the movement state of the detection ball itself, and generating B action data.

[0020] Preferably, the detection ball is movably connected to the top guide rail by a drive unit; and the drive unit includes executing control commands to pull the suspended detection ball to change the position and / or height of the detection ball.

[0021] Preferably, the detection ball further includes an acoustic-optical unit, configured to emit a specified sound and / or a specified color of light at a specified time and / or frequency according to the control command of the control unit.

[0022] Preferably, the server includes one or more evaluation sub-rules selected from multiple existing evaluation sub-rules that are suitable for the current user's motor and cognitive abilities, and the evaluation rules are ultimately formed from multiple evaluation sub-rules.

[0023] Preferably, the server further includes generating real-time action data of the user by analyzing the action data of A and action data of B in real time, and generating subsequent evaluation rules based on the real-time action data and the personal information.

[0024] The beneficial effects achieved by this invention are:

[0025] 1. The evaluation system of this technical solution can organically combine the evaluation of motor ability and cognitive ability. Traditional evaluations often focus on either motor or cognitive function alone, while this system collects cognitive data from the user's touch of the detection ball and motor data from the lower limb detection unit, and analyzes the data based on unified evaluation rules. This allows for a comprehensive assessment of the user's cognitive performance during exercise and the impact of cognition on motor function, thus more accurately reflecting the user's overall ability status.

[0026] 2. The evaluation system of this technical solution possesses high flexibility and personalization. The server can select suitable rules from multiple evaluation sub-rules based on the user's personal information to form evaluation rules. Furthermore, during the evaluation process, it can dynamically generate subsequent evaluation rules based on real-time evaluation data obtained from analyzing action data of user A and action data of user B. This adaptive mechanism can adjust the difficulty and tasks for different users at different evaluation stages, ensuring the validity and accuracy of the evaluation results and better adapting to individual differences.

[0027] 3. The evaluation platform of this technical solution adopts diverse interactive units and data acquisition methods. Interactive units send behavioral instructions to users based on evaluation rules, guiding them to complete corresponding actions. The mat and sensor layer of the lower limb detection unit can accurately collect information such as stepping position and force. The multiple detection balls of the upper limb detection unit can not only collect the timing of touch and their own movement state through internal sensor groups, but also change position and height under the control of the drive unit. Furthermore, with the help of the audio-visual unit, it provides various forms of stimulus feedback, enriching the dimensions of data acquisition and improving the richness and accuracy of the evaluation data.

[0028] 4. The software and hardware components of the evaluation system in this technical solution adopt a modular design. Each working module and component of the hardware component, as well as the instructions, parameters, and algorithms of the software component, can be easily replaced and / or upgraded later, thereby reducing the construction and maintenance costs of this system. Attached Figure Description

[0029] The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the drawings are not necessarily drawn to scale, but rather the emphasis is on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0030] Reference numerals: 100-Evaluation System; 200-Server; 300-Evaluation Platform; 210-Controller; 211-Personal Information Input Unit; 212-Information Processing Unit; 213-Evaluation Platform Control Unit; 214-Evaluation Result Storage Unit; 215-Evaluation Result Output Unit; 216-Database; 400-Evaluation Platform; 410-Lower Limb Detection Unit; 411-Supporting Platform; 420-Upper Limb Detection Unit; 421-Circular Guide Rail; 422-Suspension Mechanism; 423-Detection Ball; 430-Interaction Unit; 440-Control Unit; 450-Communication Unit; 500-Computer System; 502-Bus; 504-Processor; 506-Main Memory; 508-Read-Only Memory; 510-Storage Device; 512-Display; 514-Input Device; 516-Cursor Control Device; 518-Network Device;

[0031] Figure 1This is a schematic diagram of the layout of the evaluation system described in this invention;

[0032] Figure 2 This is a schematic diagram of the architecture of the evaluation system described in this embodiment of the invention;

[0033] Figure 3 This is a schematic diagram illustrating the working steps of the evaluation system described in this embodiment of the invention;

[0034] Figure 4 This is a schematic diagram of the evaluation platform described in an embodiment of the present invention;

[0035] Figure 5 This is a schematic diagram of the computer system framework used by the server in an embodiment of the present invention. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to its embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention. Other systems, methods, and / or features of this embodiment will become apparent to those skilled in the art after reviewing the following detailed description. All such additional systems, methods, features, and advantages are intended to be included within this specification, within the scope of the invention, and protected by the appended claims. Further features of the disclosed embodiments are described in the following detailed description, and these features will become apparent from the following detailed description.

[0037] In the accompanying drawings of this invention, the same or similar reference numerals correspond to the same or similar components. In the description of this invention, it should be understood that if terms such as "upper," "lower," "left," and "right" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or component referred to must have a specific orientation. Because the invention is constructed and operated in a specific orientation, the terms describing positional relationships in the drawings are for illustrative purposes only and should not be construed as limiting this patent. Those skilled in the art can understand the specific meaning of the above terms according to the specific circumstances.

[0038] Example 1: Exemplary, a data fusion-based integrated assessment system for motor and cognitive functions, the assessment system comprising: a server, and an assessment platform communicatively connected to the server;

[0039] The evaluation platform includes:

[0040] The interaction unit is configured to send behavioral instructions to the user based on the evaluation rules;

[0041] The lower limb detection unit, installed on the central platform of the evaluation platform, is used to collect data on the user's nails during the evaluation process on the platform. Action data ;

[0042] An upper limb detection unit is located on the upper part of the evaluation platform, including a top guide rail and two or more detection balls suspended from the top guide rail to the front of the user; the detection balls include data collection of the user's action when touching the detection balls;

[0043] The communication unit is configured to submit the A to the server. Action data and B's action data, and receives the data specified by the server. Evaluation Rules ;

[0044] The control unit is configured to receive control instructions generated by the server according to the evaluation rules, so as to control the upper limb detection unit to execute the control instructions;

[0045] The evaluation system, based on the evaluation rules, combines and analyzes the data from Action A and Action B to evaluate the user's athletic and cognitive abilities.

[0046] Preferably, the lower limb detection unit includes a support platform and a sensor layer;

[0047] The support platform is made of a material that can absorb external impacts and is non-slip.

[0048] The sensor layer includes multiple sensors, at least used to detect the user's foot placement and foot pressure, in order to obtain the sensor layer. Action data .

[0049] Preferably, each of the detection balls is equipped with a B sensor group for detecting the timing of the user touching the detection ball and the movement state of the detection ball itself, and generating B action data.

[0050] Preferably, the detection ball is movably connected to the top guide rail by a drive unit; and the drive unit includes executing control commands to pull the suspended detection ball to change the position and / or height of the detection ball.

[0051] Preferably, the detection ball further includes an acoustic-optical unit, configured to emit a specified sound and / or a specified color of light at a specified time and / or frequency according to the control command of the control unit.

[0052] Preferably, the server includes one or more evaluation sub-rules selected from multiple existing evaluation sub-rules that are suitable for the current user's motor and cognitive abilities, and the evaluation rules are ultimately formed from multiple evaluation sub-rules.

[0053] Preferably, the server further includes generating real-time action data of the user by analyzing the action data of A and action data of B in real time, and generating subsequent evaluation rules based on the real-time action data and the personal information.

[0054] Specifically, in conjunction with the appendix Figure 1 and attached Figure 2 An exemplary embodiment of the evaluation system is described. (The appendix is ​​missing from the original text.) Figure 1 An exemplary layout diagram of the evaluation system is shown below. Figure 2 This is an exemplary architectural diagram of the evaluation system. The evaluation system includes a server 200 and an evaluation platform 300. The user stands on the evaluation platform 300 and performs actions and operations according to the instructions of the evaluation platform 300. The evaluation platform 300 collects a series of data from the user during the evaluation process and sends the collected data to the server 200, which generates a result based on an integrated evaluation of the user's current movement and cognition.

[0055] For example, functionally speaking, the server 200 may include a controller 210. The controller 210 may include a personal information input unit 211, an information processing unit 212, an evaluation platform control unit 213, an evaluation result storage unit 214, an evaluation result output unit 215, and a database 216.

[0056] The following is a combination of the above. Figure 3 The evaluation steps shown illustrate the workflow of the evaluation system.

[0057] In a preferred embodiment, the appendix is ​​executed. Figure 3 In step S100 of the workflow, the personal information input unit 211 provides a user interface to receive personal information input from the user. Personal information may include name, age, gender, and health status.

[0058] Preferably, the health status may include the user's mental state assessment results, the user's cognitive function information, the user's daily life adaptability measurement, the user's fall risk level, the user's brain age, and the user's happiness index.

[0059] Preferably, the personal information received by the personal information input unit 211 is stored in the database 216 so that it can be retrieved and used at any time.

[0060] Preferably, the user's personal information can be updated periodically, and the evaluation results can be updated to the user's personal information after the user completes the motor and cognitive function evaluation provided by the evaluation system.

[0061] In a preferred embodiment, the information processing unit 212 receives the user's personal information and evaluation results, wherein the evaluation results are related to the user's actions performed on the evaluation platform 300 based on the... Evaluation Rules of Action data Related. Based on personal information and evaluation results, the information processing unit 212 analyzes and assesses the user's motor and cognitive function status, thereby generating or updating the user's motor and cognitive function information, and providing optimized [measures] based on the user's motor and cognitive function. Evaluation Rules .

[0062] Preferably, the information processing unit 212 further includes performing the above based on the user's personal information and evaluation results. Evaluation Rules The formation of.

[0063] In the initial stage, step S200 is executed, where the information processing unit 212 first generates an initial [database name] based on the user's personal information. Evaluation rules.

[0064] Among them, the Evaluation Rules It can be one of multiple existing sets of rules, or one or more sub-rules. Existing rules can be detection rules that are optimized based on historical evaluations and summaries, and then statistically verified by relevant technical personnel. Existing rules can be stored in the database 216 for later retrieval.

[0065] and Evaluation Rules It can also be generated in real time by the information processing unit 212 according to a predetermined program, and the real-time generated data will be processed. Evaluation Rules This information is used in subsequent evaluation processes to obtain user feedback in a cyclical manner.

[0066] Furthermore, in step S300, the evaluation system executes the step S300, whereby the evaluation platform control unit 213 obtains the confirmed result. Evaluation rules but It reads each evaluation sub-rule of the evaluation rules and generates the rules that the evaluation platform needs to execute. Operation instructions This includes controlling the upper limb detection unit 420 to perform actions according to the descriptions in each evaluation sub-rule, such as controlling the height, position, color change, and sound emission of the detection ball; and also includes generating the interactive units in the evaluation platform that need to send messages to the user. Behavioral instructions .

[0067] Preferably, the evaluation rules can be divided into one or more detection stages, and each detection stage includes one or more evaluation sub-rules. The evaluation system can analyze the user's detection results after completing one detection stage and dynamically generate evaluation sub-rules for the next detection stage.

[0068] Furthermore, in step S400, the evaluation system executes a step where the interaction unit 430 of the evaluation platform continues to send instructions to the user that need to be executed. Behavioral instructions The Behavioral instructions For example: Touch the yellow detection ball with your left hand. Then, wait for the user to execute the action command.

[0069] Furthermore, in step S500, the evaluation system executes the evaluation platform, such as the lower limb detection unit 410 and the upper limb detection unit 420, which begins to collect the user's action data, including but not limited to: the moment the user begins to move, the distance moved, the speed of foot movement, whether the user touches any of the detection balls, and a series of other data.

[0070] Furthermore, in step S600 of the evaluation system, the information processing unit 212 records and analyzes the action data of the user executing one or more behavioral instructions in order to analyze the user's motor ability and cognitive ability reflected by one or more evaluation sub-rules.

[0071] Furthermore, in step S700 of the evaluation system, the information processing unit 212 updates the subsequent evaluation sub-rules based on the user's current action data or the motor and cognitive abilities reflected by a series of user action data.

[0072] After completing all evaluation rules, the evaluation system executes step S800, outputting the final analysis results of the user's motor and cognitive abilities.

[0073] Further details are attached. Figure 4 The diagram illustrates the construction of the evaluation platform. (See attached diagram.) Figure 2 and attached Figure 4 The evaluation platform 300 is described below. For example, the evaluation platform 300 includes a lower limb detection unit 410, an upper limb detection unit 420, and an interaction unit 430; preferably, the communication unit 450 and the control unit 440 are disposed within the internal structure of the lower limb detection unit 410 and are not shown in the figures.

[0074] In a preferred embodiment, the lower limb detection unit 410 includes a support platform 411; the support platform 411 can be disc-shaped or rectangular, has an aluminum alloy frame, and its surface is covered with a thick silicone buffer layer, which not only achieves a certain buffering effect, but also reduces the vibration and noise generated when the user moves on its surface.

[0075] Preferably, a sensor layer is provided in the interlayer of the support platform. Preferably, the sensor layer is formed by a sensor matrix composed of multiple piezoresistive or piezoresistive sensors. Preferably, the sampling frequency of the sensor layer can be 60Hz or 120Hz, or higher; a higher sampling frequency can obtain more analysis data, but it will also consume more computing resources, and needs to be further determined by relevant technical personnel according to actual needs.

[0076] Preferably, sensor-based data can enable dynamic analysis of a user's stride length, cadence, gait cycle, and other parameters.

[0077] In some implementations, the user's lower limb symmetry index G is calculated using the following formula. By analyzing the comparison of the pressure on the left and right soles of the user, it is possible to analyze whether the pressure on the user's two legs is balanced.

[0078]

[0079] Among them, P L and P R These are the average single-foot pressure values ​​for the user's left and right feet, respectively.

[0080] In some implementations, the stability area of ​​the user's center of gravity projection point (COP) can be calculated using the following formula, and the stability of the COP can be analyzed to infer the user's balance ability and reflect the range of the human body's ability to maintain static or dynamic stability on the support surface. The COP (Center of Pressure) trajectory refers to the path of the center of pressure on the support surface during standing or movement.

[0081]

[0082] Where a and b are the lengths of the major and minor axes of the envelope ellipse of the COP trajectory, respectively.

[0083] In some implementations, the system also includes COP-based analysis of the user's motion coordination, including pressure migration rate V. cop :

[0084]

[0085] In the above formula, xt and yt are the coordinates of the user's center of gravity projection point COP on the bearing platform 411 at time t, respectively, and Δt is the detection step size, which can optionally be 0.1s or shorter.

[0086] In a preferred embodiment, the upper limb detection unit 420 is composed of a ring-shaped modular architecture, including a ring-shaped guide rail 421, a suspension mechanism 422, and a detection ball 423.

[0087] Preferably, the maximum outer diameter of the annular guide rail 421 is slightly larger than that of the support platform 411, and its diameter can be 2.2 meters or 2 meters, which is basically equivalent to or slightly larger than the user's arm span. The annular guide rail 421 is preferably made of a lightweight alloy such as aluminum alloy, and it consists of a main rail, a trolley module that can slide on the main rail by electric drive, and a deceleration drive system that drives the trolley module to move.

[0088] Furthermore, each trolley module is connected to a detection ball 423 via a carbon fiber cable, suspending the detection ball 423 around the user. Only two detection balls 423 are shown in the figure; in actual implementation, four or six detection balls 423 can be configured, increasing the versatility of detection combinations.

[0089] Preferably, the end of the trolley module can be equipped with a force sensor to detect the force acting on the detection ball, such as the tension generated by the carbon fiber cable when the user pulls the detection ball 423. The end of the trolley module can also be equipped with a quick connector to enable quick loading, unloading, and replacement of the detection ball 423.

[0090] Preferably, the detection ball 423 is further equipped with a second sensor, and the data generated by the second sensors of multiple detection balls 423 are packaged into a second sensor dataset for synchronous transmission to the server 200. The second sensor may include a 9-axis IMU capable of simultaneously sensing the acceleration and angular velocity of the detection ball 423 itself; the second sensor may also include a capacitive haptic array to sense the specific time and location at which the user touches the detection ball 423.

[0091] Preferably, LEDs are provided on the surface of the detection ball 423 so that the detection ball 423 displays the desired light color.

[0092] Preferably, a speaker is provided inside the detection ball 423; the speaker of each detection ball 423 can be connected to the control unit via wired or wireless connection, and the control unit can control one or more designated speakers to emit sound, and the control unit can determine that different detection balls 423 emit designated sounds, and control the sound volume, frequency and other parameters.

[0093] In other embodiments, the upper limb detection unit 420 may also be equipped with an image acquisition unit to obtain the user's dynamic posture during the evaluation, so as to obtain more analysis data.

[0094] Example 2: This example should be understood as including at least all the features of any of the foregoing examples, and further improving upon them.

[0095] In a preferred embodiment, the evaluation rules include determining the positional layout of a plurality of test balls 423.

[0096] Taking the circular annular guide rail 421 as an example, in this step, the initial distribution angle of each detection ball 423 is first defined:

[0097]

[0098] Where n = 1, 2, ..., N, N is the number of detection balls, and φ is the offset angle, which can be selected from 0° to 30°.

[0099] Furthermore, the motion of the detection ball 423 can be in linear oscillation mode, random walk mode, or static fixed-point mode, etc., to meet different detection needs and detection difficulties.

[0100] Furthermore, in the initial stage of the evaluation rules, the information processing unit 212 first extracts the user's basic information to determine the user's basic motor and cognitive abilities.

[0101] The user information that can be extracted includes height, upper limb length, lower limb length, body fat percentage, etc.

[0102] Preferably, the assessment of athletic ability also includes the user's static balance stability index, grip strength, hand strength, hand movement speed, and lower limb movement speed. Furthermore, the user's heart rate, blood pressure, and respiratory rate can be obtained through a monitoring device worn by the user.

[0103] Regarding cognitive abilities, an optional approach could be to perform a basic Stroop color-word conflict test, calculating the user's cognitive flexibility and the interference effect by detecting the degree of conflict between the LED color instructions of the ball and the voice prompts. Alternatively, an N-back working memory test could be conducted on the user to construct a spatial memory load using the emission sequence of the ball.

[0104] Preferably, in an exemplary embodiment, the following calculation formula can be used to update the difficulty coefficient D of the next detection sub-rule or multiple detection sub-rules in the next detection stage. next :

[0105]

[0106] In the above formula, D current A represents the difficulty level of the current detection sub-rule or the current detection phase. actual The actual score for the user executing the evaluation sub-rule; A expectedThe evaluation system predicts the expected score of the current user when executing an evaluation sub-rule; α is the difficulty adjustment sensitivity coefficient, which can be set by technical personnel based on the user's personal information, for example, 0.3 for healthy people and 0.15 for patients who have just recovered.

[0107] The actual score of a user executing an evaluation sub-rule can be determined independently for each evaluation sub-rule. For example, an evaluation sub-rule may specify that the user's reaction time, action speed, and touch accuracy (e.g., needing to touch the detection ball multiple times) in the action data need to be calculated, or it may also include consideration of the user's dynamic pulse, blood pressure, and other physical data.

[0108] In addition, B t To assess the baseline abilities of users' motor and cognitive functions in real time; P t β represents the user's maximum potential for real-time evaluation; β is the learning factor.

[0109] For example, a user's average reaction time might be 0.8 seconds, corresponding to an absolute reaction time score of 4, but the user's possible extreme reaction time might be 0.4 seconds, corresponding to an absolute reaction time score of 8; therefore, B can be simply set. t =4, P t =8. The above example is only for the convenience of understanding this technical solution. In actual settings, B... t and P t When setting a specific value, it needs to be determined by relevant technical personnel through a comprehensive evaluation of various user data based on an automated evaluation program.

[0110] Among them, B t The initial value B0 can be a comprehensive baseline value of ability calculated based on the user's basic physical condition, such as average blood pressure, respiratory rate, and pulse, obtained through preliminary simple tests, such as static standing and basic reaction tests; P t The initial value is P0, which is determined based on the user's age, medical history, and postural data (such as joint range of motion) to predict the potential limit of ability.

[0111] And the initial difficulty level D initial It can be set to: D initial =0.7B0+0.3P0.

[0112] D next The calculation formula includes an adaptive adjustment term in the first part, which reflects the dynamic adjustment of difficulty. The second part considers the comparison between the user's limit ability and the baseline ability. When the user is close to the limit, the degree of difficulty variation is reduced.

[0113] Among them, the learning factor β can be used to smooth out possible unexpected scores, thereby making the process of difficulty adjustment and change more gradual.

[0114] Example 3: This example should be understood as including at least all the features of any of the foregoing examples, and further improving upon them.

[0115] For example, as shown in the appendix Figure 5 The following diagram illustrates the implementation of the computer system 500 used by the server 200; the computer system 500 can be applied to the data storage, calculation, and result output processes of each working module in the identification and judgment system.

[0116] For example, computer system 500 includes bus 502 or other communication mechanism for transmitting information, and one or more processors 504 coupled to bus 502 for processing information; processor 504 may be, for example, one or more general-purpose microprocessors.

[0117] Computer system 500 also includes main memory 506, such as random access memory (RAM), cache and / or other dynamic storage devices, coupled to bus 502 for storing information and instructions to be executed by processor 504; main memory 506 may also be used to store temporary variables or other intermediate information during the execution of instructions executed by processor 504; when these instructions are stored in storage media accessible to processor 504, they present computer system 500 as a dedicated machine customized to perform the operations specified in the instructions.

[0118] The computer system 500 may also include a read-only memory (ROM) 508 or other static storage device coupled to the bus 502 for storing static information and instructions of the processor 504; among which, storage devices 510 such as disks, optical discs or USB drives (flash drives) will be coupled to the bus 502 for storing information and instructions.

[0119] Furthermore, the bus 502 may also include a display 512 for displaying various information, data, media, etc., and an input device 514 for allowing users of the computer system 500 to control, manipulate, and / or interact with the computer system 500.

[0120] A preferred method of interacting with the management system may be through a cursor control device 516, such as a computer mouse or a similar control / navigation mechanism.

[0121] Furthermore, the computer system 500 may also include a network device 518 coupled to the bus 502; wherein the network device 518 may include components such as wired network cards, wireless network cards, switching chips, routers, switches, etc.

[0122] Generally speaking, the terms “engine,” “component,” “system,” and “database” used in this article can refer to the logic embodied in hardware or firmware, or to a collection of software instructions that may have entries and exit points, written in programming languages ​​such as Java, C, or C++; software components can be compiled and linked into executable programs, installed in dynamic link libraries, or written in interpreted programming languages ​​such as BASIC, Perl, or Python; it should be understood that software components can be called from other components or from themselves, and / or can be called in response to detected events or interrupts.

[0123] Software components configured to execute on a computing device may be provided on a computer-readable medium, such as an optical disc, digital video disc, flash drive, magnetic disk, or any other tangible medium, or as a digital download (and may be initially stored in a compressed or installable format that requires installation, decompression, or decryption prior to execution); such software code may be stored, in part or in whole, on a memory device executing the computing device; software instructions may be embedded in firmware, such as an EPROM; it should also be understood that hardware components may consist of connected logic units (e.g., gates and flip-flops), and / or may consist of programmable units (e.g., programmable gate arrays or processors).

[0124] Computer system 500 includes technologies described herein that can be implemented using custom hardwired logic, one or more ASICs or FPGAs, firmware and / or program logic, which, when combined with the computer system, enables computer system 500 to become a dedicated computing device.

[0125] According to one or more embodiments, the techniques described herein are executed by computer system 500 in response to processor 504 executing one or more sequences of one or more instructions contained in main memory 506; such instructions may be read into main memory 506 from another storage medium such as storage device 510; execution of the sequence of instructions contained in main memory 506 causes processor 504 to perform the processing steps described herein; in alternative embodiments, hardwired circuitry may be used in place of or in combination with software instructions.

[0126] As used herein, the term "non-transitory medium" and similar terms refer to any medium that stores data and / or instructions that enable a machine to operate in a particular manner; such non-transitory medium may include non-volatile medium and / or volatile medium; non-volatile medium includes, for example, optical discs or magnetic disks, such as storage device 510; volatile medium includes dynamic memory, such as main memory 506.

[0127] Common forms of non-transitory media include, for example, floppy disks, hard disks, solid-state drives, magnetic tapes or any other magnetic data storage media, CD-ROMs, any other optical data storage media, any physical media with a hole pattern, RAM, PROMs and EPROMs, FLASH-EPROMs, NVRAMs, any other memory chips or cartridges and their network versions.

[0128] Non-transient media are different from transmission media, but can be used in conjunction with transmission media; transmission media participate in information transmission between non-transient media; for example, transmission media include coaxial cables, copper wires and optical fibers, including the wires that constitute bus 502; transmission media can also take the form of sound waves or light waves, such as radio waves and infrared data communication.

Claims

1. A system for integrated evaluation of motor and cognitive functions under data fusion, characterized in that, The evaluation system comprises a server and an evaluation platform connected with the server; The evaluation platform comprises: An interaction unit configured to send behavior instructions based on evaluation rules to a user; A lower limb detection unit laid on a central platform of the evaluation platform, used to collect action data of a user when the user is performing evaluation on the evaluation platform; An upper limb detection unit arranged on an upper part of the evaluation platform, comprising a top rail and two or more detection balls suspended from the top rail to the front of the user; the detection balls comprise collecting action data generated by the user when touching the detection balls; A communication unit configured to submit the action data and the action data to the server, and receive evaluation rules formulated by the server; A control unit configured to receive control instructions generated by the server according to the evaluation rules, to control the upper limb detection unit to execute the control instructions; The evaluation system evaluates the user's motor ability and cognitive ability based on the evaluation rules, combined with analyzing the action data and the action data; The lower limb detection unit comprises a bearing platform and a sensor layer; The bearing platform is made of a material capable of absorbing external impact and preventing slipping; The sensor layer comprises a plurality of sensor devices, at least for detecting the stepping position and the stepping force of the user to obtain the action data; Each of the detection balls is internally provided with a group of beta sensors for detecting the timing of the user touching the detection balls and the motion state of the detection balls themselves, and generating the action data; The detection balls are movably connected to the top rail by a driving unit; and the driving unit comprises an execution control unit for pulling the suspended detection balls to change the position and / or height of the detection balls; The server comprises selecting one or more evaluation sub-rules suitable for the current user's motor and cognitive ability from a plurality of existing evaluation sub-rules, and finally forming the evaluation rules from a plurality of evaluation sub-rules; The server further comprises generating real-time action data of the user by instantaneously analyzing the action data and the action data, and generating subsequent evaluation rules based on the real-time action data and personal information. The detection balls further comprise an audible and light unit configured to emit specified sound and / or light of specified color at specified timing and / or frequency according to the control instructions of the control unit. ​ ​ 2. The evaluation system of claim 1, wherein ​

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