Shoulder joint proprioceptive sensation evaluation system and method based on mobile terminal and inertial sensor

Abstract

The invention discloses a shoulder joint proprioceptive assessment system and method based on a mobile terminal and an inertial sensor, and relates to the technical field of sports medicine and rehabilitation assessment, and the steps are as follows: the system comprises an inertial measurement unit, namely an IMU module, used for collecting real-time motion data of a shoulder joint in a three-dimensional space; the fixing device is used for fixing the IMU module on the arm of a user; and the processing unit is in communication connection with the IMU module. According to the shoulder joint proprioceptive assessment system and method based on the mobile terminal and the inertial sensor, through cooperative measurement of three IMUs and real-time data calculation, isolated measurement of glenohumeral joint movement is achieved in proprioceptive assessment for the first time, pollution of scapular thoracic wall joints and trunk compensatory movement to angle measurement is thoroughly eliminated, and the accuracy of proprioceptive assessment is improved. The definition of the target position and the sensing position is accurate to the anatomical responsible joint, and the obtained AUC value can more truly and specifically reflect the proprioceptive function of the glenohumeral joint.

Description

Technical Field

[0001] This invention relates to the field of sports medicine and rehabilitation assessment technology, specifically to a shoulder joint proprioceptive assessment system and method based on a mobile terminal and inertial sensors. Background Technology

[0002] In the fields of sports medicine, rehabilitation assessment, and sports science, accurate quantitative assessment of proprioceptive function in human joints is crucial for injury prevention, guiding rehabilitation training, and improving athletic performance. The shoulder joint, as the joint with the largest range of motion in the human body, relies heavily on good proprioceptive input for stability. However, due to the complex structure and high degree of freedom of movement of the shoulder joint, reliable, effective, and standardized proprioceptive assessment has always been a significant challenge.

[0003] Traditional methods for assessing joint proprioception, such as the Joint Position Reset Test (JPR) and the Passive Movement Detection Threshold (TTDPM), have significant limitations when applied to the shoulder joint. The JPR method relies heavily on the subject's memory and attention, is prone to subjective bias, and is difficult to simulate functional movements. The TTDPM method typically requires expensive and bulky isokinetic muscle strength testing systems, limiting its application in routine clinical settings, and its passive movement pattern is inconsistent with the ecological validity of most active human activities.

[0004] In recent years, the Active Motor Discrimination Assessment (AMEDA) paradigm has attracted attention due to its higher ecological validity. This method requires subjects to actively move to multiple physical block locations and identify them. However, existing AMEA devices are mostly customized devices designed for the lower limbs (such as the ankle and knee), and their application to the shoulder joint faces many difficulties: the devices are usually bulky and difficult to adjust to accommodate multi-angle shoulder movements; the setting of physical blocks cannot accurately control the subject's perception time (i.e., exposure time to location, PET) at the target location, and PET is a key variable affecting sensory information encoding and memory consolidation; in addition, the high cost of customized devices also hinders its widespread adoption.

[0005] Furthermore, existing assessment methods rely on a limited range of data analysis dimensions, often depending on simple angle error calculations. They fail to fully utilize more robust statistical methods, such as signal detection theory, to calculate discrimination acuity, which may result in a lack of comprehensive and sensitive reflection of subtle changes in proprioceptive function. To address this, we propose a shoulder joint proprioceptive assessment system and method based on a mobile terminal and inertial sensors. Summary of the Invention

[0006] The purpose of this invention is to provide a shoulder joint proprioceptive assessment system and method based on a mobile terminal and an inertial sensor, in order to solve the problem that the existing assessment methods mentioned in the background art have a relatively simple data analysis dimension, rely heavily on simple angle error calculation, and fail to make full use of more robust statistical methods such as signal detection theory to calculate discrimination acuity, thus failing to fully and sensitively reflect subtle changes in proprioceptive function.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a shoulder joint proprioceptive assessment system based on a mobile terminal and an inertial sensor, comprising:

[0008] An inertial measurement unit, or IMU module, is used to collect real-time motion data of the shoulder joint in three-dimensional space.

[0009] A fixing device for securing the IMU module to the user's arm;

[0010] The processing unit, which is communicatively connected to the IMU module, is configured as follows:

[0011] a) Receive and process data from the IMU module to calculate the real-time angles of the shoulder joint in the abduction and flexion motion planes;

[0012] b) The control prompting unit generates multimodal prompting signals to guide the user to actively move the shoulder joint to a randomly specified target position;

[0013] c) When the real-time angle enters the preset target angle tolerance range, start timing and control the prompting unit to generate a prompt signal indicating the maintenance state, which lasts for a preset position exposure time;

[0014] d) Record the actual angle value of the target position;

[0015] The user input interface is used to receive the user's subjective judgment information on the reached position after each movement is completed;

[0016] The analysis unit is configured to calculate the user's shoulder joint position discrimination acuity index based on the actual target position recorded in multiple trials and the user's subjective judgment information.

[0017] Furthermore, the processing unit is further configured to: if the real-time angle deviates from the target angle tolerance range during the location exposure time, control the prompting unit to stop the prompting signal indicating the maintenance state until the real-time angle re-enters the tolerance range.

[0018] Furthermore, the prompting unit includes at least two of the following: an auditory prompting unit, a visual prompting unit, and a tactile prompting unit.

[0019] Furthermore, the auditory prompting unit uses different tones or speech segments to respectively represent the start of movement, reaching the target position, and maintaining the state.

[0020] Furthermore, the analysis unit, based on the principle of signal detection theory, constructs a confusion matrix according to the actual target position and the user's subjective judgment information, and calculates the area under the receiver's operation feature curve as an indicator of the shoulder joint position discrimination sensitivity.

[0021] Furthermore, the analysis unit is also configured to calculate the test-retest reliability index of the system under different test scenarios, the test-retest reliability index including one or more of the following: within-group correlation coefficient, measurement standard error, and minimum detectable change value.

[0022] Furthermore, the IMU module is a smartphone or smartwatch, and its built-in gyroscope and accelerometer constitute the inertial measurement unit; the processing unit and the analysis unit are applications running on the smartphone or smartwatch.

[0023] Furthermore, the IMU module is an independent wireless sensor node that communicates with a mobile terminal containing the processing unit and the analysis unit via Bluetooth or Wi-Fi.

[0024] Furthermore, the method using the aforementioned shoulder joint proprioceptive assessment system based on a mobile terminal and inertial sensors includes the following steps:

[0025] The IMU module is fixed to the user's arm using the fixing device;

[0026] The processing unit randomly specifies a target location;

[0027] The prompting unit generates a first prompting signal to guide the user to begin shoulder abduction or flexion movements.

[0028] The real-time angle is calculated based on the data from the IMU module, and when the real-time angle enters the target angle tolerance range, a second prompt signal is generated through the prompt unit, and the timing of a preset position exposure time is started.

[0029] At the end of the PET procedure, a third prompting signal is generated by the prompting unit to prompt the user to return the arm to the initial position;

[0030] The user's subjective judgment of the location reached during this movement is received through the user input interface;

[0031] Repeat the above steps multiple times;

[0032] The analysis unit calculates and outputs the user's shoulder joint position discrimination acuity assessment result based on the actual target position recorded in multiple tests and the user's subjective judgment information.

[0033] Furthermore, the location exposure time (PET) is adjustable, ranging from 0.1 seconds to 5 seconds.

[0034] This invention provides a shoulder joint proprioceptive assessment system and method based on a mobile terminal and inertial sensors, which has the following beneficial effects: This invention, through three IMUs coordinated measurement and real-time data processing, achieves, for the first time, isolated measurement of glenohumeral joint motion in proprioceptive assessment, completely eliminating the contamination of angle measurement by compensatory movements of the scapulothoracic joint and trunk. This allows the definition of "target position" and "perceived position" to be precise down to the anatomically responsible joint, and the obtained AUC value can more realistically and specifically reflect the proprioceptive function of the glenohumeral joint itself. For patients with compensatory movements (such as rotator cuff tears and frozen shoulder), this invention provides a key technical tool for differential diagnosis by providing pure glenohumeral joint angles, which has significant clinical implications. It ensures that all subjects are assessed in the pure glenohumeral joint motion dimension, greatly improving the comparability of data between different individuals and studies and the standardization of assessment. While achieving laboratory-level measurement accuracy, the entire system is still based on wireless wearable technology, maintaining good portability and clinical usability. Attached Figure Description

[0035] Figure 1 This is a framework diagram of the shoulder joint proprioception assessment method of the present invention;

[0036] Figure 2 This is a flowchart of a single test for the present invention. Detailed Implementation

[0037] The embodiments of the present invention will be described in further detail below with reference to examples. These examples are for illustrative purposes only and should not be construed as limiting the scope of the invention.

[0038] A shoulder joint proprioceptive assessment system based on a mobile terminal and inertial sensors, comprising:

[0039] An inertial measurement unit, or IMU module, is used to collect real-time motion data of the shoulder joint in three-dimensional space.

[0040] A fixing device for securing the IMU module to the user's arm;

[0041] The processing unit, which communicates with the IMU module, is configured as follows:

[0042] a) Receive and process data from the IMU module to calculate the real-time angles of the shoulder joint in the abduction and flexion motion planes. The IMU module is a smartphone or smartwatch, whose built-in gyroscope and accelerometer constitute an inertial measurement unit. The processing unit and analysis unit are applications running on the smartphone or smartwatch. The IMU module is an independent wireless sensor node that communicates with the mobile terminal containing the processing unit and analysis unit via Bluetooth or Wi-Fi.

[0043] b) The control prompting unit generates multimodal prompting signals to guide the user to actively move the shoulder joint to a randomly specified target position. The prompting unit includes at least two of the following: auditory prompting unit, visual prompting unit, and tactile prompting unit. The auditory prompting unit uses different tones or speech segments to indicate the start of movement, arrival at the target position, and maintenance state, respectively.

[0044] c) When the real-time angle enters the preset target angle tolerance range, start timing and control the prompting unit to generate a prompt signal indicating the maintenance state, which lasts for a preset position exposure time;

[0045] d) Record the actual angle value of the target position;

[0046] The processing unit is further configured to: if the real-time angle deviates from the target angle tolerance range during the location exposure time, the control prompt unit stops the prompt signal indicating the maintenance state until the real-time angle re-enters the tolerance range.

[0047] The user input interface is used to receive the user's subjective judgment information on the reached position after each movement is completed;

[0048] The analysis unit is configured to calculate the user's shoulder joint position discrimination sensitivity index based on the actual target position recorded in multiple trials and the user's subjective judgment information. Based on the principle of signal detection theory, the analysis unit constructs a confusion matrix based on the actual target position and the user's subjective judgment information, and calculates the area under the receiver operating characteristic curve as the shoulder joint position discrimination sensitivity index. The analysis unit is also configured to calculate the test-retest reliability index of the system in different test scenarios. The test-retest reliability index includes one or more of the following: within-group correlation coefficient, measurement standard error, and minimum detectable change value.

[0049] A method using a shoulder joint proprioceptive assessment system based on a mobile terminal and inertial sensors includes the following steps:

[0050] The IMU module is secured to the user's arm using a fixing device;

[0051] A target location is randomly assigned by the processing unit;

[0052] The prompting unit generates a first prompting signal to guide the user to begin shoulder abduction or flexion movements.

[0053] The real-time angle is calculated based on the data from the IMU module. When the real-time angle enters the target angle tolerance range, a second prompt signal is generated through the prompt unit, and a preset position exposure time (PET) is started. The position exposure time (PET) is adjustable and its value ranges from 0.1 seconds to 5 seconds.

[0054] At the end of the PET scan, a third prompting signal is generated by the prompting unit to prompt the user to return the arm to the initial position;

[0055] Receive the user's subjective judgment information on the location reached during this movement through the user input interface;

[0056] Repeat the above steps multiple times;

[0057] The analysis unit calculates and outputs the user's shoulder joint position discrimination acuity assessment results based on the actual target position recorded in multiple tests and the user's subjective judgment information.

[0058] In this application, a high-performance IMU module with six or more axes is used, which integrates a 3-axis gyroscope and a 3-axis accelerometer. The fused high-precision attitude quaternion is directly output through the built-in digital motion processor (DMP), which greatly reduces the computational burden on the main device.

[0059] Gyroscope: range at least ±1000dps, noise density less than 4mdps / √Hz.

[0060] Accelerometer: measuring range of at least ±8g, noise density of less than 100μg / √Hz.

[0061] Wireless communication: All support Bluetooth 5.0 and above protocols to ensure low power consumption, low latency and stable synchronous data transmission across multiple devices.

[0062] Power supply: Each sensor node has a built-in rechargeable lithium battery (e.g., 3.7V, 200mAh), which can be charged via a magnetic pin interface. The battery life on a single charge should be greater than 8 hours.

[0063] Fixing method:

[0064] Sternal manubrium and acromion: Use disposable medical-grade double-sided adhesive tape to directly attach to the corresponding bony landmarks after skin cleansing.

[0065] Humeral joint: It is secured to the upper 1 / 3 of the humerus with a lightweight, adjustable Velcro strap. The inner side of the strap is equipped with a silicone anti-slip pad to ensure no wobbling during movement.

[0066] Host device: A smartphone or tablet running Android 10.0 or above or iOS 14.0 or above, used to run custom-developed applications and serve as a wireless data receiving hub and user interface.

[0067] Software Implementation

[0068] Development Environment: The application is developed using the Unity3d engine (C# language) to enable deployment on both Android and iOS platforms. Sensor data communication is achieved through the BluetoothLEOSX plugin.

[0069] Sensor data synchronization:

[0070] The host device acts as the central device and simultaneously establishes Bluetooth connections with three sensor nodes (peripheral mode).

[0071] The synchronization mechanism employs a "command broadcast synchronization method": the host broadcasts a synchronization command packet containing a timestamp to all sensor nodes at a frequency of 100Hz. Upon receiving the command, each node immediately adds the unified timestamp to its local IMU data buffer and then sends it back to the host. This method can control the data synchronization error between the three nodes to within 5ms, meeting the accuracy requirements of motion capture.

[0072] Sensor fusion and attitude calculation:

[0073] Although the sensor nodes can output quaternions, a secondary fusion is still performed at the host end to obtain higher precision relative angles. The algorithm employs a strategy combining complementary filtering and gradient descent to calculate...

[0074] The formula is as follows:

[0075] First, the initial attitude is calculated using accelerometer data to correct gyroscope drift, and then the pitch and roll angles are corrected using accelerometer data.

[0076] An iterative optimization algorithm based on gradient descent is employed to solve for the optimal quaternion.

[0077] The core of the algorithm is as follows:

[0078] Define the objective function f(q, b a) represents the estimated value of the gravity vector in the body coordinate system under the current quaternion q, and the accelerometer measurement. b The difference between 'a' and 'a'.

[0079] Calculate the gradient of the objective function:

[0080]

[0081] Correct the angular velocity measured by the gyroscope:

[0082]

[0083] Update quaternions:

[0084]

[0085] Where q is a quaternion. b 'a' represents the measured acceleration value in the body coordinate system. b ω is the gyroscope measurement, β is the filter coefficient (weight controlling the accelerometer calibration), Δt is the sampling period, and J is the Jacobian matrix. Specific steps of the calibration process:

[0086] The subject stands upright with both arms hanging naturally at his sides (anatomical zero position).

[0087] The tester clicked the "Calibration Start" button on the application.

[0088] The application records the pose data of the three nodes for 3 seconds (sampling at 100Hz), calculates the average value, and sets this pose as the initial pose of each node's coordinate system.

[0089] qchest0,qscapula0,qhumerus0.

[0090] Define the glenohumeral joint rotation axis and motion plane. For abduction, the glenohumeral joint rotation axis is initialized to a direction passing through the center of the humeral head and parallel to the sagittal axis of the trunk. The motion plane is the coronal plane. Real-time calculation of pure glenohumeral joint angles:

[0091] At each time t during the evaluation, obtain the current pose quaternion of each node.

[0092] q chest(t) ,q scapula(t) ,q humerus(t) .

[0093] Calculate the rotation of the scapula relative to the torso:

[0094]

[0095] Calculate the rotation of the humerus relative to the initial scapular coordinate system:

[0096]

[0097] The pure glenohumeral joint angle is the current posture of the humeral joint.

[0098] q_humerus_relative_to_scapula0(t) is decomposed into the rotation axis and motion plane defined by the initial calibration, and its projection angles are calculated. For example, the abduction angle θ_GH(t) in the coronal plane.

[0099] It can be extracted using the conversion formula from quaternions to Euler angles.

[0100] Through this mathematical transformation, the final θ is obtained GH(t) The effects of scapular and trunk movements have been removed.

[0101] Evaluation control parameters:

[0102] Target angles: set to abduction 23.1–24.9°, 25.1–26.9°, 27.1–28.9°, 29.1°.

[0103] –30.9°; forward flexion 171.8–173.6°, 173.6–175.4°, 175.4–177.2

[0104] °, 177.2–179.0°

[0105] PET: Offers four options: 0.25s, 0.5s, 0.75s, and 1.0s, with 0.5s being the default.

[0106] Number of trials: 10 random occurrences at each target location, for a total of 40 trials per side per PET condition.

[0107] A nonparametric analysis method based on signal detection theory is used to quantify position discrimination sensitivity. The specific process is as follows:

[0108] First, the subjects' response data were organized into a confusion matrix based on actual and reported locations. Then, a binary classification analysis was performed on each pair of adjacent target locations. For any pair of adjacent locations (e.g., location i and location i+1), location i+1 was considered a "signal," and location i was considered "noise." Using the Wilcoxon rank-sum test, the probability that the response value of a sample in the "signal" distribution is greater than the response value of a sample in the "noise" distribution was calculated. This probability value is the area under the receiver operating characteristic curve (AUC) for distinguishing the pair of locations. The formula for AUC is:

[0109] AUC ivsi+1 =[R i+1 -n i+1 (n i+1 +1) / 2] / (n i *n i+1 )

[0110] in:

[0111] R i+1 This represents the sum of the ranks of the response values ​​of all trials with actual positions i and i+1, after mixing and sorting them from smallest to largest.

[0112] n i and n i+1 These represent the number of trials at actual positions i and i+1, respectively.

[0113] The statistical meaning of the AUC value is: the probability that a response value randomly drawn from the "signal" (position i+1) is greater than a response value randomly drawn from the "noise" (position i), with a value ranging from 0.5 (completely indistinguishable) to 1.0 (perfectly discernible). Finally, the arithmetic mean of the AUC values ​​of all adjacent position pairs (e.g., 1-2, 2-3, 3-4) is calculated as a comprehensive index of the subject's proprioceptive acuity.

[0114] The embodiments of the present invention are given for illustrative and descriptive purposes only, and are not intended to be exhaustive or to limit the invention to the forms disclosed. Many modifications and variations will be apparent to those skilled in the art. The embodiments were chosen and described in order to better illustrate the principles and practical application of the invention, and to enable those skilled in the art to understand the invention and to design various embodiments with various modifications suitable for a particular purpose.

Claims

1. A shoulder joint proprioceptive assessment system based on a mobile terminal and inertial sensors, characterized in that, include: An inertial measurement unit, or IMU module, is used to collect real-time motion data of the shoulder joint in three-dimensional space. A fixing device for securing the IMU module to the user's arm; The processing unit, which is communicatively connected to the IMU module, is configured as follows: a) Receive and process data from the IMU module to calculate the real-time angles of the shoulder joint in the abduction and flexion motion planes; b) The control prompting unit generates multimodal prompting signals to guide the user to actively move the shoulder joint to a randomly specified target position; c) When the real-time angle enters the preset target angle tolerance range, start timing and control the prompting unit to generate a prompt signal indicating the maintenance state, which lasts for a preset position exposure time; d) Record the actual angle value of the target position; The user input interface is used to receive the user's subjective judgment information on the reached position after each movement is completed; The analysis unit is configured to calculate the user's shoulder joint position discrimination acuity index based on the actual target position recorded in multiple trials and the user's subjective judgment information.

2. The shoulder joint proprioceptive assessment system based on a mobile terminal and inertial sensors according to claim 1, characterized in that, The processing unit is further configured to: if the real-time angle deviates from the target angle tolerance range during the location exposure time, control the prompting unit to stop the prompting signal indicating the maintenance state until the real-time angle re-enters the tolerance range.

3. The shoulder joint proprioceptive assessment system based on a mobile terminal and inertial sensors according to claim 2, characterized in that, The prompting unit includes at least two of the following: auditory prompting unit, visual prompting unit, and tactile prompting unit.

4. The shoulder joint proprioceptive assessment system based on a mobile terminal and inertial sensors according to claim 3, characterized in that, The auditory prompting unit uses different tones or speech segments to indicate the start of movement, arrival at the target position, and maintenance state, respectively.

5. The shoulder joint proprioceptive assessment system based on a mobile terminal and inertial sensors according to claim 4, characterized in that, The analysis unit is based on the principle of signal detection theory. It constructs a confusion matrix based on the actual target position and the user's subjective judgment information, and calculates the area under the receiver's operation feature curve as an indicator of the shoulder joint position discrimination sensitivity.

6. The shoulder joint proprioceptive assessment system based on a mobile terminal and inertial sensors according to claim 5, characterized in that, The analysis unit is also configured to calculate the test-retest reliability index of the system under different test conditions, the test-retest reliability index including one or more of the following: within-group correlation coefficient, measurement standard error, and minimum detectable change value.

7. The shoulder joint proprioceptive assessment system based on a mobile terminal and inertial sensors according to claim 6, characterized in that, The IMU module is a smartphone or smartwatch, and its built-in gyroscope and accelerometer constitute the inertial measurement unit; the processing unit and analysis unit are applications running on the smartphone or smartwatch.

8. The shoulder joint proprioceptive assessment system based on a mobile terminal and inertial sensors according to claim 7, characterized in that, The IMU module is an independent wireless sensor node that communicates with a mobile terminal containing the processing unit and the analysis unit via Bluetooth or Wi-Fi.

9. A method using the shoulder joint proprioceptive assessment system based on a mobile terminal and inertial sensors as described in claim 8, characterized in that, Includes the following steps: The IMU module is fixed to the user's arm using a fixing device; A target location is randomly assigned by the processing unit; The prompting unit generates a first prompting signal to guide the user to begin shoulder abduction or flexion movements. The real-time angle is calculated based on the data from the IMU module, and when the real-time angle enters the target angle tolerance range, a second prompt signal is generated through the prompt unit, and the timing of a preset position exposure time is started. At the end of the PET procedure, a third prompting signal is generated by the prompting unit to prompt the user to return the arm to the initial position; The user's subjective judgment of the location reached during this movement is received through the user input interface; Repeat the above steps multiple times; The analysis unit calculates and outputs the user's shoulder joint position discrimination acuity assessment results based on the actual target position recorded in multiple tests and the user's subjective judgment information.

10. The method for a shoulder joint proprioceptive assessment system based on a mobile terminal and inertial sensors according to claim 9, characterized in that, The exposure time to location (PET) is adjustable, ranging from 0.1 seconds to 5 seconds.

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