Parkinson's disease gait disorder training method, device, equipment and medium

Abstract

The invention relates to a Parkinson's disease gait disorder training method, device and equipment and a medium. The training method comprises the following steps: a data acquisition step: acquiring gait data of left and right feet of a patient; step height calculation: calculating the step heights of the left and right feet of the patient according to the gait data; and a prompt generation step, wherein the patient is prompted according to the step height data obtained through calculation. Based on the height of the left and right feet of the patient, the vibration prompt is generated, the vibration prompt normal form set is constructed, the vibration prompt is dynamically adjusted according to the performance of the patient in the training process, and precise and personalized rehabilitation training is achieved.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method, apparatus, device, and medium for training gait disorder in Parkinson's disease. Background Technology

[0002] Parkinson's disease (PD) is the second leading cause of neurodegenerative disease. China has over 5 million PD patients, accounting for 43.14% of the global total, with a higher incidence rate than the global average. Deaths due to PD in China account for 23.71% of global related deaths, indicating a heavy disease burden. PD not only severely impacts the physical health and quality of life of individual patients but also imposes a significant economic and medical burden on Chinese society. As one of the countries with the largest number of patients, China urgently needs to strengthen investment in early diagnosis, precision treatment, and rehabilitation care. During the progression of PD, patients' motor symptoms continuously worsen, leading to falls, disability, and even death. Developing effective intervention strategies targeting motor symptoms can improve patients' motor abilities, thereby reducing mortality, increasing independence, and improving quality of life for PD patients. Clinical symptom treatment for PD patients mainly includes medication, rehabilitation training, and surgery. Furthermore, recent studies and clinical evidence have shown that vibration cues have a significant effect on improving gait performance in PD patients. Vibrational cues mechanically stimulate tactile receptors, activating nerve endings in the skin and muscles and transmitting signals to the cerebral cortex. This stimulation may improve gait performance by promoting the reconnection of the patient's motor control network through neuroplasticity mechanisms.

[0003] The Netherlands has developed a vibrating sock to explore the effect of tactile cues on improving frozen gait, finding that vibration cues can reduce the percentage of frozen gait time by more than 10%. Portugal has developed a vibrating belt that significantly reduces the occurrence of frozen gait by providing vibrational tactile stimulation with a frequency range of 60–300Hz and an amplitude of 0.2–2.8g.

[0004] Existing vibration cues focus on improving walking speed in PD patients and addressing gait initiation issues in mid-to-late stage patients. However, for early-stage PD patients, increasing walking speed and initiation speed has little impact on improving motor symptoms and lacks improvement for gait dragging. For early-stage PD patients, improving dragging gait is more important for enhancing their quality of life.

[0005] There is currently no effective solution to the above problems. Summary of the Invention

[0006] Therefore, it is necessary to provide a training method, device, equipment, and medium for gait disorder in Parkinson's disease to address the aforementioned technical problems. For the dribble gait symptom, a personalized training method is proposed. Based on the patient's left and right foot heights, vibration cues are generated, a set of vibration cues patterns is constructed, and the vibration cues are dynamically adjusted according to the patient's performance during training, achieving precise and personalized rehabilitation training.

[0007] According to a first aspect of the present invention, a method for training gait disorder in Parkinson's disease is provided, comprising: The data collection step involves collecting gait data for the patient's left and right feet; The step height calculation step involves calculating the height of the patient's left and right feet based on the gait data. The prompt generation process provides guidance to the patient based on the calculated step height data.

[0008] In some embodiments, the calculation of the patient's left and right foot heights includes: The gait data is processed to obtain the gait period, and the step height is calculated based on the gait period.

[0009] In some embodiments, the step height calculation includes: Obtain the angular velocity ω and acceleration a; Construct differential equations for quaternions: ; in, To represent quaternion multiplication, It is the quaternion extended form of the angular velocity vector, where q is the quaternion used to represent the attitude in three-dimensional space, denoted as q=[q0,q1,q2,q3]. T ; The attitude change per unit time is estimated using the following formula: ; The quaternion q is corrected by the acceleration a, and the updated formula is: ; Where β is the fusion coefficient, used to adjust the weights of gyroscope prediction and acceleration correction; ∇f(q,a) is the gradient of the constructed error function with respect to the quaternion; Convert the corrected quaternion q to Euler angles: ; The step height is obtained by pitch calculation.

[0010] In some embodiments, prompting the patient based on the calculated step height data includes: Based on the obtained step height, the higher side is set as the normal side and the lower side is set as the dragging side. When the dragging side lifts its foot, vibration begins. When the step height reaches 70% of the normal side, the vibration decreases, indicating that the leg should step forward.

[0011] In some embodiments, if a patient’s dragging-side step height increases by more than 5% compared to the initial step height within a training cycle, the target dragging-side step height is increased by 5% until the dragging-side step height reaches the level of the normal side.

[0012] In some embodiments, prompting the patient based on the calculated step height data includes: Based on the obtained step height parameters, the higher side is set as the normal side and the lower side is set as the dragging side. When the step height of the dragging side reaches the calculated step height, vibration begins, prompting the user to continue raising the step height.

[0013] In some embodiments, the gait data is acquired by a device placed on the patient's ankle.

[0014] According to a second aspect of the present invention, a gait disorder training device for Parkinson's disease is provided, comprising: The data acquisition module is used to collect gait data of the patient's left and right feet; The step height calculation module is used to calculate the left and right step heights of the patient based on the gait data. The prompt generation module is used to provide prompts to patients based on the calculated step height data.

[0015] According to a third aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of any of the methods described above.

[0016] According to a fourth aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the methods of any of the above embodiments.

[0017] Existing vibration cues focus on improving walking speed in PD patients and addressing gait initiation issues in mid-to-late stage patients. For early-stage PD patients, increasing walking speed and initiation speed has little impact on improving motor symptoms and lacks improvement for gait dragging. For early-stage PD patients, improving dragging gait and increasing stride height are more important for improving quality of life. This invention proposes a personalized training method for dragging gait symptoms. It accurately obtains the patient's stride height through specific data processing methods. Based on this stride height data, vibration cues stimulate the patient to increase the stride height on the dragging side. Through a closed-loop process of "detection-cue generation-re-detection," it promotes the gradual convergence of the dragging side's gait performance towards the normal side, thereby improving dragging gait. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the implementation system of the Parkinson's disease gait disorder training method of the present invention.

[0019] Figure 2 This is a flowchart of some embodiments of the Parkinson's disease gait disorder training method of the present invention.

[0020] Figure 3 These are schematic diagrams of some embodiments of the Parkinson's disease gait disorder training device of the present invention.

[0021] Figure 4 This is an internal structural diagram of a computer device used to implement some embodiments of the present invention. Detailed Implementation

[0022] Embodiments of the invention will now be described more fully with reference to the accompanying drawings, in which embodiments of the invention are illustrated. However, the invention may be practiced in many different forms, and should not be construed as limited to the embodiments set forth herein.

[0023] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. As used herein, the singular forms “a” and “this” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that, when used herein, the term “comprising” specifies the presence of the stated features, integrals, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof.

[0024] Unless otherwise defined, the terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. Terms used herein shall be interpreted as having the same meaning as they have in the context of this specification and in the relevant field, and shall not be interpreted in an idealized or overly formal sense, unless specifically defined herein.

[0025] Gait cycle: The process of walking from when the same foot leaves the ground to when it touches the ground again.

[0026] This invention provides a training method for gait disorder in Parkinson's disease. The method is implemented through a system that includes: two IMUs (placed at the patient's left and right ankles to acquire gait data of the left and right feet), two vibration units (capable of generating vibrations of 10-200 Hz, placed at the patient's ankles to generate vibrations), and operating software (processing gait data and generating vibrations). Figure 1 A schematic diagram of the implementation system of the Parkinson's disease gait disorder training method of the present invention is shown. Figure 1 As shown, the gait cycle and step height are first calculated based on accelerometer and gyroscope data acquired by IMUs placed at the patient's left and right ankles. Then, based on the patient's gait cycle and step height, vibration cues that match the motor performance are generated. Simultaneously, the foot lift height during the patient's current walking process is detected, and the vibration cues are dynamically adjusted to improve the real-time performance and effectiveness of the intervention. This invention mainly includes two key components: left and right step height calculation and vibration generation and iteration.

[0027] Figure 2 This is a flowchart of some embodiments of the Parkinson's disease gait disorder training method of the present invention.

[0028] like Figure 2 As shown, the method includes: In the data acquisition step S102, gait data of the patient's left and right feet are collected. Step height calculation step S104: Calculate the patient's left and right step heights based on the gait data; In some embodiments, the gait data is processed to obtain a gait period, and step height is calculated based on the gait period; Based on the defined gait period, preprocessed data for that gait period is obtained, including angular velocity and acceleration. The angular velocity is denoted as: Acceleration is denoted as: Prediction updates are based on angular velocity, which can be used to construct quaternion differential equations: ; in, To represent quaternion multiplication, This is the quaternion extended form of the angular velocity vector. Then, the attitude change per unit time is estimated through numerical integration: ; To reduce the bias error of the gyroscope, correction is performed using acceleration, and the quaternion derivative is updated as follows: ; Here, β is the fusion coefficient, which controls the weights of gyroscope prediction and acceleration correction. ∇f(q,a) is the gradient of the constructed error function with respect to the quaternion, whose analytical form can be derived from the deviation between the direction cosine matrix and the acceleration direction. This gradient term guides the quaternion estimate to adjust in a direction that satisfies the acceleration observation constraints, thereby suppressing attitude drift.

[0029] After obtaining a stable quaternion attitude estimate (i.e., q), the attitude can be further converted into Euler angle representation, with the following transformation relationships, corresponding to rotations about the x, y, and z axes respectively:

[0030] Pitch is used as the primary angular component reflecting foot lift height, representing the forward and backward swing of the body relative to the vertical direction. Step height is calculated based on pitch. To enable customized adjustment of walking height and gait cycle using the generated visual cues, the reconstructed left and right foot skeletal points are associated with step height parameters and step height smoothing curves, respectively. This allows for natural adjustment of gait performance based on gait parameters during walking. Step height is obtained from pitch through the following methods: acquiring the current foot position and performing ground detection, using the ground detection results as a reference for the foot's initial height; calculating the current gait stage based on the current gait motion curve value and the target gait cycle; determining the step height within this stage based on the step height parameters; and superimposing the lift effect controlled by the motion curve onto the foot's Y-axis coordinate to obtain the final foot position.

[0031] Step S106 prompts the patient by providing prompts based on the calculated step height data.

[0032] In some embodiments, two vibration alert modes are included: Continuous stimulation paradigm: Based on the acquired step height parameters, the higher side is designated as the normal side and the lower side as the dragging side. When a step is detected on the dragging side, vibration begins. When the step height reaches 70% of the normal side's step height, the vibration decreases, indicating a forward step. If the patient's dragging side step height increases by more than 5% compared to the initial step height within a training cycle (40 seconds), the target step height for reduced dragging side vibration is increased by 5% until it reaches the level of the normal side.

[0033] Event-driven paradigm: Based on the acquired step height parameters, the higher side is designated as the normal side and the lower side as the dragging side. When the step height on the dragging side reaches the calculated step height, vibration begins, prompting the patient to continue raising their foot. If the patient's dragging side step height increases by more than 5% compared to the initial step height within a training cycle (40 seconds), the target step height on the dragging side (i.e., the step height at which vibration begins) is increased by 5% until it reaches the level of the normal side.

[0034] Based on the generated vibration cues, patients with early-stage PD can undergo rehabilitation training. PD patients can perform 10-meter round-trip walking training, and continue training according to the vibration cues during the process.

[0035] This invention generates vibration cues based on the height of the patient's left and right feet, constructs a set of vibration cues models, and dynamically adjusts the vibration cues according to the patient's performance during training, thus achieving precise and personalized rehabilitation training.

[0036] To analyze the improvement of gait by vibration cues, this invention first focuses on the bilateral limb differences caused by dragging gait. It compares and analyzes the changes in gait consistency between patients without intervention and with vibration cues. Higher gait consistency indicates that the patient's bilateral limbs are more consistent, and dragging gait is improved. The training effect of this method on gait consistency is shown in Table 1. Gait consistency is calculated based on left and right foot speed, stride length, stride frequency, swing phase, stance phase, and double stance phase, as follows: ; in, n The number of spatiotemporal parameters, L i and R i The first i The values ​​of the left and right feet of each variable.

[0037] Table 1. Gait Consistency Variation Analysis

[0039] Furthermore, since bradykinesia is a major problem in early-stage PD patients, this invention further compared and analyzed the differences in gait improvement across different paradigms based on the affected side of the patient. After one training session, all participating patients showed an improvement in gait speed and gait performance. The training effect of this method on gait improvement is shown in Table 2. The formula for calculating gait improvement is as follows: ; in, This represents the dragging side step speed before training. This represents the dragging side gait speed after training.

[0040] Table 2 Analysis of the improvement in gait speed on the affected side

[0041] As can be seen from the data in Tables 1 and 2 (P1-P4 represent different patients), the training method of the present invention can significantly improve patients' gait consistency and gait speed.

[0042] Figure 3 A schematic diagram of the structure of some embodiments of the Parkinson's disease gait disorder training device of the present invention is shown.

[0043] like Figure 3 As shown, the Parkinson's disease gait disorder training device in this embodiment includes: The data acquisition module 100 is used to collect gait data of the patient's left and right feet; Step height calculation module 200 is used to calculate the left and right step heights of the patient based on the gait data; The prompt generation module 300 is used to provide prompts to the patient based on the calculated step height data.

[0044] For specific limitations regarding a gait disorder training device for Parkinson's disease, please refer to the limitations of a gait disorder training method for Parkinson's disease described above, which will not be repeated here. Each module in the aforementioned gait disorder training device for Parkinson's disease can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0045] The present invention also provides a computer device, which may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown. The computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements the aforementioned training method for Parkinson's disease gait disorder. The display screen can be a liquid crystal display (LCD) or an e-ink display. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse. Those skilled in the art will understand that… Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device to which the present invention is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0046] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described training method for gait impairment in Parkinson's disease.

[0047] Those skilled in the art will understand that implementing all or part of the processes in the above method embodiments can be accomplished by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), memory bus (RAMbus), direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0048] The embodiments of the present invention have now been described in detail. To avoid obscuring the concept of the invention, some details known in the art have not been described. Those skilled in the art will fully understand how to implement the technical solutions disclosed herein based on the above description.

[0049] While specific embodiments of the present invention have been described in detail by way of examples, those skilled in the art should understand that the above examples are for illustrative purposes only and are not intended to limit the scope of the invention. Those skilled in the art should understand that modifications can be made to the above embodiments or equivalent substitutions can be made to some technical features without departing from the scope and spirit of the invention. The scope of the invention is defined by the appended claims.

Claims

1. A training method for gait disorder in Parkinson's disease, characterized in that, include: The data collection step involves collecting gait data for the patient's left and right feet; The step height calculation step involves calculating the height of the patient's left and right feet based on the gait data. The prompt generation process provides guidance to the patient based on the calculated step height data.

2. The training method for gait impairment in Parkinson's disease according to claim 1, characterized in that, The calculation of the patient's left and right foot heights includes: The gait data is processed to obtain the gait period, and the step height is calculated based on the gait period.

3. The training method for gait impairment in Parkinson's disease according to claim 1, characterized in that, The step height calculation includes: Obtain the angular velocity ω and acceleration a; Construct differential equations for quaternions: ； in, To represent quaternion multiplication, It is the quaternion extended form of the angular velocity vector, where q is the quaternion used to represent the attitude in three-dimensional space, denoted as q=[q0,q1,q2,q3]. T ; The attitude change per unit time is estimated using the following formula: ； The quaternion q is corrected by the acceleration a, and the updated formula is: ； Where β is the fusion coefficient, used to adjust the weights of gyroscope prediction and acceleration correction; ∇f(q,a) is the gradient of the constructed error function with respect to the quaternion; Convert the corrected quaternion q to Euler angles: ； The step height is obtained by pitch calculation.

4. The training method for gait impairment in Parkinson's disease according to claim 1, characterized in that, The step height data obtained through calculation is used to provide prompts to the patient, including: Based on the obtained step height, the higher side is set as the normal side and the lower side is set as the dragging side. When the dragging side lifts its foot, vibration begins. When the step height reaches 70% of the normal side, the vibration decreases, indicating that the leg should step forward.

5. The training method for gait impairment in Parkinson's disease according to claim 4, characterized in that, If a patient's dragging side step height increases by more than 5% compared to the initial step height within a training cycle, the target dragging side step height is increased by 5% until the dragging side step height reaches the level of the normal side.

6. The training method for gait impairment in Parkinson's disease according to claim 1, characterized in that, The step height data obtained through calculation is used to provide prompts to the patient, including: Based on the obtained step height parameters, the higher side is set as the normal side and the lower side is set as the dragging side. When the step height of the dragging side reaches the calculated step height, vibration begins, prompting the user to continue raising the step height.

7. The training method for gait impairment in Parkinson's disease according to claim 1, characterized in that, The gait data was acquired using a device placed on the patient's ankle.

8. A gait disorder training device for Parkinson's disease, characterized in that, include: The data acquisition module is used to collect gait data of the patient's left and right feet; The step height calculation module is used to calculate the left and right step heights of the patient based on the gait data. The prompt generation module is used to provide prompts to patients based on the calculated step height data.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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