Lower limb rehabilitation walking aid system

Abstract

The embodiment of the invention discloses a lower limb rehabilitation walking aid system. The system comprises a lower limb rehabilitation walking aid. The lower limb rehabilitation walking aid comprises a movable device, a first adjusting device, a second adjusting device, a human body fixing device and a main control device, wherein the main control device comprises a pressure acquisition module, and the pressure acquisition module is used for acquiring pressure applied to the human body fixing device by a target object which carries out lower limb rehabilitation training by wearing the human body fixing device through a force feedback motor; the target weight reduction obtaining module is used for obtaining target weight reduction of the target object; the motor output adjustment parameter obtaining module is used for carrying out proportional integral differential control according to the error between the pressure and the target weight reduction to obtain a motor output adjustment parameter; and the torque motor output adjusting module is used for adjusting the output of the first torque motor and / or the second torque motor according to the motor output adjusting parameters. According to the technical scheme, accurate weight reduction can be carried out in the lower limb rehabilitation training process.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of physical therapy technology, and in particular to a lower limb rehabilitation walking aid system. Background Art

[0002] Patients with stroke or cerebral infarction, patients recovering from trauma, patients with neuromuscular diseases and the elderly need rehabilitation training to improve their motor skills due to changes in muscle strength or trauma.

[0003] According to the muscle strength classification, the Medical Research Council (MRC) scoring standard is usually used, which can be divided into 0 to 5 levels, among which 0 means no muscle contraction at all; 1 means slight muscle contraction, but no joint movement; 2 means joint movement without resisting gravity; 3 means joint movement can be completed against gravity, but cannot resist external force; 4 means joint movement can resist a certain external force; 5 means normal muscle strength. Levels 0 to 3 have weak mobility and poor resistance to external intervention, so external force is needed to assist movement.

[0004] In particular, for lower limb rehabilitation tasks (which require voluntary joint movement), patients with level 2 strength are the main targets of weight loss technology because these patients cannot stand or fight against gravity on their own, and weight loss can help them resume sports and rehabilitation training. Although patients with level 3 to 4 strength can fight against gravity, they are still limited in the recovery process, and weight loss can help them increase muscle strength and improve the quality of movement.

[0005] However, it is currently impossible to achieve accurate weight loss during lower limb rehabilitation training, which needs to be urgently addressed. Summary of the invention

[0006] The embodiment of the present invention provides a lower limb rehabilitation walking aid system, which solves the problem that accurate weight loss cannot be performed during lower limb rehabilitation training.

[0007] According to one aspect of the present invention, a lower limb rehabilitation walking aid system is provided, which may include: a lower limb rehabilitation walking aid; wherein,

[0008] The lower limb rehabilitation walker comprises a movable device movable on the ground, a first adjusting device, a second adjusting device, a human body fixing device and a main control device, one end of the movable device is connected to the first adjusting device in a V-shaped rotation and the other end is connected to the second adjusting device in a V-shaped rotation, the first adjusting device is connected to the second adjusting device in an X-shaped rotation, the first adjusting device is provided with a first torque motor and a force feedback motor, the force feedback motor is rigidly connected to the human body fixing device, and the second adjusting device is provided with a second torque motor;

[0009] The main control device includes a pressure acquisition module, a target weight loss acquisition module, a motor output adjustment parameter acquisition module and a torque motor output adjustment module; wherein,

[0010] A pressure acquisition module, used for acquiring, through a force feedback motor, the pressure exerted on the human body fixation device by a target subject who is wearing the human body fixation device for lower limb rehabilitation training;

[0011] A target weight loss obtaining module is used to obtain the target weight loss of the target object;

[0012] The motor output adjustment parameter obtaining module is used to perform proportional integral differential control according to the error between the pressure and the target weight loss to obtain the motor output adjustment parameter;

[0013] The torque motor output adjustment module is used to adjust the output of the first torque motor and / or the second torque motor according to the motor output adjustment parameters to adjust the opening and closing angle between the first adjustment device and the second adjustment device, wherein the opening and closing angle is negatively correlated with the supporting force provided to the target object through the human body fixing device, and the supporting force is used to resist the gravity of the target object.

[0014] The lower limb rehabilitation walker described in the embodiment of the present invention performs PID control through the error between the target weight loss and the actual support force provided for the target object, thereby adjusting the output of the torque motor, thereby ensuring the accuracy of the torque motor output, and further achieving the effect of precise weight loss during lower limb rehabilitation training.

[0015] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 is a structural block diagram of a lower limb rehabilitation walking aid system provided according to an embodiment of the present invention;

[0018] Figure 2 is a schematic diagram of a lower limb rehabilitation walking aid in a lower limb rehabilitation walking aid system provided according to an embodiment of the present invention;

[0019] Figure 3 is a structural block diagram of another lower limb rehabilitation walking aid system provided according to an embodiment of the present invention;

[0020] Figure 4 is a structural block diagram of another lower limb rehabilitation walking aid system provided according to an embodiment of the present invention;

[0021] Figure 5a is a schematic diagram of an IMU sensor C and a sEMG acquisition module in another lower limb rehabilitation walking aid system provided according to an embodiment of the present invention;

[0022] Figure 5b is a schematic diagram of a plantar pressure measurement module in another lower limb rehabilitation walking aid system provided according to an embodiment of the present invention;

[0023] Figure 6a is a schematic diagram of multimodal data collection in another lower limb rehabilitation walking aid system provided in an embodiment of the present invention;

[0024] Figure 6b Another lower limb rehabilitation walking aid system provided by the embodiment of the present invention is Figure 6a The structural block diagram of the corresponding electromyography acquisition module;

[0025] Figure 6c Another lower limb rehabilitation walking aid system provided by the embodiment of the present invention is Figure 6a The structural block diagram of the corresponding IMU acquisition module;

[0026] Figure 6d Another lower limb rehabilitation walking aid system provided by the embodiment of the present invention is Figure 6a The structural block diagram of the corresponding plantar pressure measurement module;

[0027] Figure 7 is a structural block diagram of another lower limb rehabilitation walking aid system provided according to an embodiment of the present invention;

[0028] Figure 8 This is a workflow diagram of another lower limb rehabilitation walking aid system provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. The situations of "target", "original", etc. are similar and will not be repeated here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Figure 1 1 is a structural block diagram of a lower limb rehabilitation walking aid system provided by an embodiment of the present invention. This embodiment is applicable to the case of weight loss during lower limb rehabilitation training.

[0032] See also Figure 1 The lower limb rehabilitation walking aid system described in the embodiment of the present invention comprises: a lower limb rehabilitation walking aid A; wherein,

[0033] The lower limb rehabilitation walker A comprises a movable device A1 movable on the ground, a first adjustment device A2, a second adjustment device A3, a human body fixing device A4 and a main control device A5, one end of the movable device A1 is connected to the first adjustment device A2 in a V-shaped rotation and the other end is connected to the second adjustment device A3 in a V-shaped rotation, the first adjustment device A2 is connected to the second adjustment device A3 in an X-shaped rotation, the first adjustment device A2 is provided with a first torque motor and a force feedback motor, the force feedback motor is rigidly connected to the human body fixing device A4, and the second adjustment device A3 is provided with a second torque motor;

[0034] The main control device A5 includes a pressure acquisition module A51, a target weight loss acquisition module A52, a motor output adjustment parameter acquisition module A53 and a torque motor output adjustment module A54; wherein,

[0035] A pressure acquisition module A51, used to acquire, through a force feedback motor, the pressure applied on the human body fixture A4 by a target subject who is wearing the human body fixture A4 for lower limb rehabilitation training;

[0036] A target weight loss obtaining module A52 is used to obtain a target weight loss of a target object;

[0037] The motor output adjustment parameter obtaining module A53 is used to perform proportional integral differential control according to the error between the pressure and the target weight loss to obtain the motor output adjustment parameter;

[0038] The torque motor output adjustment module A54 is used to adjust the output of the first torque motor and / or the second torque motor according to the motor output adjustment parameters to adjust the opening and closing angle between the first adjustment device A2 and the second adjustment device A3, wherein the opening and closing angle is negatively correlated with the supporting force provided to the target object through the human body fixing device A4, and the supporting force is used to resist the gravity of the target object.

[0039] In order to understand the lower limb rehabilitation walker A described above more vividly, Figure 2 The lower limb rehabilitation walker A shown is used as an example for illustrative explanation.

[0040] Exemplarily, from the perspective of hardware devices, the lower limb rehabilitation walker A includes a movable device A1, a first adjustment device A2, a second adjustment device A3, a human body fixing device A4, two torque motors (i.e., the first torque motor described above) A6 arranged on the first adjustment device A2, and two torque motors (i.e., the second torque motor described above) A6 and a force feedback motor A7 arranged on the second adjustment device A2. On this basis, the main control device A5 can be understood as a software device in the lower limb rehabilitation walker A, which can be implemented by a micro control unit (MCU) embedded in the lower limb rehabilitation walker A.

[0041] On this basis, the target object can be understood as an object wearing the human body fixture A4, and the lower limb rehabilitation walker A is mainly responsible for providing auxiliary support to the target object and driving the target object to walk, thereby performing lower limb rehabilitation training. The pressure applied by the target object on the human body fixture A4 can be obtained through the force feedback motor A7. Since the pressure and the support force actually provided to the target object by the human body fixture A4 are interactive forces, the support force can be characterized by the pressure.

[0042] The target weight loss can be understood as the weight that is expected to be reduced for the target object during the lower limb rehabilitation training, that is, the support force expected to be provided for the target object. The target weight loss can be calculated by the lower limb rehabilitation walker A, or by other equipment (such as a host computer, etc.) used in conjunction with the lower limb rehabilitation walker A. This can be set according to actual needs and is not specifically limited here.

[0043] It should be noted that the lower limb rehabilitation walker A provides support for the target object through the torque motor A6, but because there may be a difference between the actual output of the torque motor A6 and the expected output, this will cause the lower limb rehabilitation walker A to provide the target object with a difference between the actual support and the expected support (i.e., the target weight loss), which may result in the inability to achieve accurate weight loss during the rehabilitation training process.

[0044] In order to solve the above technical problems, the embodiment of the present invention performs proportional-integral-derivative (PID) control according to the error between the pressure and the target weight loss, and obtains the motor output adjustment parameter, which can be understood as a parameter for adjusting the output of the torque motor A6, and can further be understood as a parameter for adjusting the output of the force feedback motor A7. On this basis, illustratively, PID control can be composed of the following three parts: Proportional (P) control: providing an output proportional to the error, for rapid response to the state change of the target object; Integral (I) control: for eliminating cumulative errors, by integrating the error, compensating for long-term deviations, and ensuring long-term accuracy; Derivative (D) control: predictive adjustment of the rate of change of the error, suppressing oscillations, providing smoother weight loss adjustment, and ensuring the stability of the target object training.

[0045] Further, the output of the first torque motor A6 and / or the second torque motor A6 can be adjusted according to the motor output adjustment parameters to adjust the opening and closing angle Angle between the first adjustment device A2 and the second adjustment device A3, and then adjust the opening and closing height Height between the movable device A1 and the second adjustment device A3. It should be noted that the smaller the opening and closing angle Angle, the higher the opening and closing height Height, so that the upward support force provided to the target object by the human body fixing device A4 is greater, that is, the target object resists more gravity; and the larger the opening and closing angle Angle, the lower the opening and closing height Height, so that the upward support force provided to the target object by the human body fixing device A4 is smaller, that is, the target object resists less gravity. In other words, the human body fixing device A4 plays a role in protecting the target object and providing support to achieve weight reduction when the opening and closing angle Angle and the opening and closing height Height are changed, and there is a negative correlation between the opening and closing angle Angle and the support force provided.

[0046] The lower limb rehabilitation walker described in the embodiment of the present invention performs PID control through the error between the target weight loss and the actual support force provided for the target object, thereby adjusting the output of the torque motor, thereby ensuring the accuracy of the torque motor output, and further achieving the effect of precise weight loss during lower limb rehabilitation training.

[0047] In an optional technical solution, the main control device further includes a force feedback motor output adjustment module: wherein,

[0048] The force feedback motor output adjustment module is used to adjust the output of the force feedback motor according to the motor output adjustment parameters to control the human body fixing device to rotate around the target object.

[0049] Among them, when the supporting force provided to the target object is reduced, the target object may lean forward; and when the supporting force provided to the target object is increased, the target object may lean backward. On this basis, in order to ensure the stability of the center of gravity of the target object, when the force feedback motor is rigidly connected to the human body fixture, the output of the force feedback motor can be adjusted according to the motor output adjustment parameters, so that the human body fixture can be rotated around the target object to ensure that the target object is in an upright state. Exemplarily, if the supporting force is reduced, the human body fixture is controlled to rotate to the back of the target object to pull up the target object; otherwise, the human body fixture is controlled to rotate to the back of the target object to prop up the target object.

[0050] The above technical solution, on the one hand, can maintain the stability of the center of gravity of the target object by adjusting the output of the force feedback motor, thereby ensuring the safety of the target object during the lower limb rehabilitation training.

[0051] On the other hand, the coordinated work between the torque motor and the force feedback motor ensures that the target object is always properly supported throughout the lower limb rehabilitation training process, effectively improving safety and comfort.

[0052] Figure 3 It is a structural block diagram of another lower limb rehabilitation walking aid system provided by an embodiment of the present invention. This embodiment is optimized based on the above-mentioned technical solutions. In this embodiment, optionally, the above-mentioned system also includes: a host computer; wherein the host computer includes: a control instruction sending module; wherein the control instruction sending module is used to send control instructions to the lower limb rehabilitation walking aid; a target weight loss obtaining module, which is specifically used to respond to the received control instructions, analyze the control instructions, and obtain the target weight loss of the target object. Among them, the explanations of the terms that are the same or corresponding to the above-mentioned embodiments are not repeated here.

[0053] For details, see Figure 3 The lower limb rehabilitation walking aid system described in this embodiment includes: a lower limb rehabilitation walking aid A and a host computer B; wherein,

[0054] The lower limb rehabilitation walker A comprises a movable device A1 movable on the ground, a first adjustment device A2, a second adjustment device A3, a human body fixing device A4 and a main control device A5, one end of the movable device A1 is connected to the first adjustment device A2 in a V-shaped rotation and the other end is connected to the second adjustment device A3 in a V-shaped rotation, the first adjustment device A2 is connected to the second adjustment device A3 in an X-shaped rotation, the first adjustment device A2 is provided with a first torque motor and a force feedback motor, the force feedback motor is rigidly connected to the human body fixing device A4, and the second adjustment device A3 is provided with a second torque motor;

[0055] The main control device A5 includes a pressure acquisition module A51, a target weight loss acquisition module A52, a motor output adjustment parameter acquisition module A53 and a torque motor output adjustment module A54;

[0056] The host computer B includes: a control instruction sending module B1; wherein,

[0057] A control instruction sending module B1 is used to send control instructions to the lower limb rehabilitation walker A;

[0058] A pressure acquisition module A51, used to acquire, through a force feedback motor, the pressure applied on the human body fixture A4 by a target subject who is wearing the human body fixture A4 for lower limb rehabilitation training;

[0059] The target weight loss obtaining module A52 is used to analyze the control instruction in response to the received control instruction to obtain the target weight loss of the target object;

[0060] The motor output adjustment parameter obtaining module A53 is used to perform proportional integral differential control according to the error between the pressure and the target weight loss to obtain the motor output adjustment parameter;

[0061] The torque motor output adjustment module A54 is used to adjust the output of the first torque motor and / or the second torque motor according to the motor output adjustment parameters to adjust the opening and closing angle between the first adjustment device A2 and the second adjustment device A3, wherein the opening and closing angle is negatively correlated with the supporting force provided to the target object through the human body fixing device A4, and the supporting force is used to resist the gravity of the target object.

[0062] The technical solution of the embodiment of the present invention calculates the target weight loss by the upper computer and generates corresponding control instructions, and then sends the control instructions to the lower limb rehabilitation walker, so that the lower limb rehabilitation walker analyzes the target weight loss based on the control instructions. Compared with the lower limb rehabilitation walker calculating the target weight loss, this can reduce the calculation pressure of the lower limb rehabilitation walker, thereby focusing more on PID control and further realizing precise weight loss.

[0063] Figure 4 It is a structural block diagram of another lower limb rehabilitation walking aid system provided by an embodiment of the present invention. This embodiment is optimized based on the above-mentioned technical solutions. In this embodiment, optionally, the host computer also includes: a data acquisition module and a control instruction generation module; wherein the data acquisition module is used to acquire the training data of the target object; the control instruction generation module is used to determine the motion state of the target object according to the training data, and generate control instructions according to the motion state. Among them, the explanations of the terms that are the same as or corresponding to the above-mentioned embodiments are not repeated here.

[0064] For details, see Figure 4The lower limb rehabilitation walking aid system described in this embodiment includes: a lower limb rehabilitation walking aid A and a host computer B; wherein,

[0065] The lower limb rehabilitation walker A comprises a movable device A1 movable on the ground, a first adjustment device A2, a second adjustment device A3, a human body fixing device A4 and a main control device A5, one end of the movable device A1 is connected to the first adjustment device A2 in a V-shaped rotation and the other end is connected to the second adjustment device A3 in a V-shaped rotation, the first adjustment device A2 is connected to the second adjustment device A3 in an X-shaped rotation, the first adjustment device A2 is provided with a first torque motor and a force feedback motor, the force feedback motor is rigidly connected to the human body fixing device A4, and the second adjustment device A3 is provided with a second torque motor;

[0066] The main control device A5 includes a pressure acquisition module A51, a target weight loss acquisition module A52, a motor output adjustment parameter acquisition module A53 and a torque motor output adjustment module A54;

[0067] The host computer B includes a data acquisition module B3, a control instruction generation module B2 and a control instruction sending module B1; wherein,

[0068] Data acquisition module B3, used to acquire training data of the target object;

[0069] The control instruction generation module B2 is used to determine the motion state of the target object according to the training data, and generate a control instruction according to the motion state;

[0070] A control instruction sending module B1 is used to send control instructions to the lower limb rehabilitation walker A;

[0071] A pressure acquisition module A51, used to acquire, through a force feedback motor, the pressure applied on the human body fixture A4 by a target subject who is wearing the human body fixture A4 for lower limb rehabilitation training;

[0072] The target weight loss obtaining module A52 is used to analyze the control instruction in response to the received control instruction to obtain the target weight loss of the target object;

[0073] The motor output adjustment parameter obtaining module A53 is used to perform proportional integral differential control according to the error between the pressure and the target weight loss to obtain the motor output adjustment parameter;

[0074] The torque motor output adjustment module A54 is used to adjust the output of the first torque motor and / or the second torque motor according to the motor output adjustment parameters to adjust the opening and closing angle between the first adjustment device A2 and the second adjustment device A3, wherein the opening and closing angle is negatively correlated with the supporting force provided to the target object through the human body fixing device A4, and the supporting force is used to resist the gravity of the target object.

[0075] Among them, the training data of the target object is obtained, and the training data can be understood as data related to the lower limb rehabilitation training process of the target object. On this basis, combined with the application scenarios that may be involved in the embodiments of the present invention, optionally, the training data can be multimodal data, and the multimodal data may include at least two of the lower limb surface electromyography signals, lower limb inertial measurement signals, plantar pressure signals and actual body weight. Of course, the training data can also be unimodal data, which can be selected according to actual needs and is not specifically limited here.

[0076] On this basis, combined with the application scenarios that may be involved in the embodiments of the present invention, optionally, when the training data is multimodal data, the above system may further include: at least one of an inertial measurement unit (IMU) sensor (or IMU acquisition module), a surface electromyography (sEMG) acquisition module, and a plantar pressure measurement module;

[0077] The data acquisition module is specifically used to acquire multimodal data of the target object through at least the following two steps:

[0078] Obtaining inertial measurement signals of the lower limbs of the target object through an inertial measurement unit sensor;

[0079] The surface electromyography signal of the lower limbs of the target object is obtained through the surface electromyography acquisition module;

[0080] Acquiring a plantar pressure signal of a target object through a plantar pressure measurement module; and,

[0081] The actual weight of the target object is obtained, wherein the actual weight can be directly measured by a weight scale and then input into the host computer.

[0082] For example, Figure 5a The IMU sensor C and sEMG acquisition module D are shown. Figure 5b The plantar pressure measurement module is shown. Figure 6a-6d The multimodal data collection process is shown. Specifically,

[0083] (1) sEMG acquisition module: see Figure 6a and Figure 6b ,The MCU processes the signal amplified by the operational ,amplifier, and uploads the corresponding signal to the host computer through Bluetooth ,serial communication for subsequent processing.

[0084] (2) IMU acquisition module: see Figure 6a and Figure 6cThe changes in lower limb joint angles and lower limb motion trajectories obtained by the IMU sensor are transmitted via serial communication and Bluetooth, and the corresponding signals are uploaded to the host computer for subsequent processing. It may also include filtering circuits and calibration circuits (such as calibrating temperature differences and zero drift).

[0085] (3) Foot pressure measurement module: see Figure 6a and Figure 6d , through the pressure sensor, and through the multi-channel data acquisition circuit and analog to digital converter (ADC) array sampling to obtain the plantar pressure signal, and then through the serial communication and Bluetooth transmission, the corresponding signal is uploaded to the host computer for subsequent processing. It can also include a filtering circuit and an operational amplifier circuit.

[0086] Among them, the power module may include a 3.3V voltage stabilizing circuit and a lithium battery charging and discharging circuit.

[0087] The signal amplification circuit can use a three-op-amp differential amplifier circuit to amplify the electrical signal.

[0088] The signal filtering circuit performs filtering based on the characteristics of the collected electrical signals to obtain high-quality signals.

[0089] The Bluetooth module can upload the corresponding signal to the host computer through transparent transmission, using the slave mode.

[0090] The electromyographic acquisition electrodes may be dry electrodes. Each electromyographic acquisition module requires a pair of dry electrodes. The electrode pairs are worn on the rectus femoris, sartorius, vastus medialis and vastus lateralis of the left and right legs of the target subject.

[0091] Multi-channel data acquisition circuit, the commonly used multiplexer (MUX) can switch between multiple sensors, or use a multi-channel ADC to collect data from multiple sensors at one time.

[0092] In practical applications, the host computer may optionally perform data preprocessing after collecting multimodal data. Exemplarily, data preprocessing mainly includes:

[0093] De-noising processing, such as filtering and wavelet transform, uses high-pass filters to remove low-frequency noise, such as sensor drift or slow changes, which is suitable for extracting the dynamic part of lower limb IMU signals; uses bandpass filters to process sEMG signals and extract muscle activity characteristics; uses moving average filtering to smooth signals and reduce random noise in the signals, which is suitable for smoothing pressure sensors; and uses wavelet transform to analyze non-stationary signals, such as sEMG signals and lower limb IMU signals. Wavelet transform can effectively separate noise and useful signals and is suitable for processing complex signals with multiple frequency components.

[0094] Data cleaning can detect and process abnormal signals, remove or replace them, and process missing signals, including deletion and interpolation.

[0095] Furthermore, the motion state of the target object is determined based on the training data, and then a control instruction is generated based on the motion state. In an embodiment of the present invention, optionally, the motion state may include at least one of gait stability, muscle fatigue, and center of gravity change, so as to adjust the weight loss support of the lower limb rehabilitation walker.

[0096] The technical solution of the embodiment of the present invention can achieve adaptive weight loss by determining the target weight loss that matches the motion state, thereby ensuring that the target object can obtain appropriate support strength under different motion states, avoiding excessive or insufficient weight loss; in particular, the above-mentioned adaptive weight loss process can be carried out in real time, thereby better ensuring that the target object is always at the optimal weight, effectively improving the training effect.

[0097] An optional technical solution, when the motion state indicates that the target object has a tendency to fall, the control instruction includes a weight adjustment sub-instruction and a support force adjustment sub-instruction, and the main control device also includes a support force adjustment module; wherein,

[0098] The target weight loss obtaining module is further used to analyze the weight adjustment sub-instruction in response to the received weight adjustment sub-instruction to obtain the target weight loss of the target object;

[0099] The support force adjustment module is used to adjust the output of the force feedback motor in response to the received support force adjustment sub-instruction to realize the rotation of the human body fixing device around the target object.

[0100] The above technical solution, when it is judged that the target object has a tendency to fall through the degree of muscle fatigue and gait stability, can provide additional support force for the target object by adjusting the output of the force feedback motor, thereby ensuring the safety of the target object during lower limb rehabilitation training and avoiding accidental injuries.

[0101] Another optional technical solution is that the host computer also includes a personalized training program acquisition module; wherein,

[0102] A personalized training program acquisition module is used to acquire a personalized training program for a target object;

[0103] The control instruction generation module is specifically used to determine the motion state of the target object according to the fusion result, and generate control instructions according to the motion state and the personalized training plan.

[0104] The above technical solution determines the target weight loss by combining a personalized training plan. This personalized weight loss process ensures the personalization of the lower limb rehabilitation training of the target object, thereby improving the training effect.

[0105] On this basis, optionally, the host computer further includes: a rehabilitation training record acquisition module and a personalized training program generation module;

[0106] A rehabilitation training record acquisition module is used to acquire the rehabilitation training record of the target subject during the rehabilitation training process using the lower limb rehabilitation walker;

[0107] The personalized training program generation module is used to generate a personalized training program based on the rehabilitation training records.

[0108] The above technical solution can generate personalized training plans using rehabilitation training records. On this basis, the personalized training plans can be adjusted in combination with multimodal data, thereby adapting to the different training progress and training needs of the target objects, so that the target objects can obtain the rehabilitation training that best suits their own situation, thereby improving the training effect.

[0109] Figure 7 It is a structural block diagram of another lower limb rehabilitation walking aid system provided by an embodiment of the present invention. This embodiment is optimized based on the above-mentioned technical solutions. In this embodiment, optionally, the training data is multimodal data, and the multimodal data includes at least two unimodal data; the control instruction generation module includes a fusion submodule and a control instruction generation submodule; wherein the fusion submodule is used to perform fusion related to at least two unimodal data to obtain a fusion result; the control instruction generation submodule can be used to determine the motion state of the target object according to the fusion result, and generate control instructions according to the motion state. Among them, the explanations of the terms that are the same as or corresponding to the above-mentioned embodiments are not repeated here.

[0110] For details, see Figure 7 The lower limb rehabilitation walking aid system described in this embodiment includes: a lower limb rehabilitation walking aid A and a host computer B; wherein,

[0111] The lower limb rehabilitation walker A comprises a movable device A1 movable on the ground, a first adjustment device A2, a second adjustment device A3, a human body fixing device A4 and a main control device A5, one end of the movable device A1 is connected to the first adjustment device A2 in a V-shaped rotation and the other end is connected to the second adjustment device A3 in a V-shaped rotation, the first adjustment device A2 is connected to the second adjustment device A3 in an X-shaped rotation, the first adjustment device A2 is provided with a first torque motor and a force feedback motor, the force feedback motor is rigidly connected to the human body fixing device A4, and the second adjustment device A3 is provided with a second torque motor;

[0112] The main control device A5 includes a pressure acquisition module A51, a target weight loss acquisition module A52, a motor output adjustment parameter acquisition module A53 and a torque motor output adjustment module A54;

[0113] The host computer B includes a data acquisition module B3, a control instruction generation module B2 and a control instruction sending module B1. The control instruction generation module B2 includes a fusion submodule B21 and a control instruction generation submodule B22.

[0114] A data acquisition module B3 is used to acquire multimodal data of a target object, wherein the multimodal data includes at least two types of unimodal data;

[0115] A fusion submodule B21 is used to perform fusion related to at least two single-modal data to obtain a fusion result;

[0116] A control instruction generation submodule B22 is used to determine the motion state of the target object according to the fusion result, and generate a control instruction according to the motion state;

[0117] A control instruction sending module B1 is used to send control instructions to the lower limb rehabilitation walker A;

[0118] A pressure acquisition module A51, used to acquire, through a force feedback motor, the pressure applied on the human body fixture A4 by a target subject who is wearing the human body fixture A4 for lower limb rehabilitation training;

[0119] The target weight loss obtaining module A52 is used to analyze the control instruction in response to the received control instruction to obtain the target weight loss of the target object;

[0120] The motor output adjustment parameter obtaining module A53 is used to perform proportional integral differential control according to the error between the pressure and the target weight loss to obtain the motor output adjustment parameter;

[0121] The torque motor output adjustment module A54 is used to adjust the output of the first torque motor and / or the second torque motor according to the motor output adjustment parameters to adjust the opening and closing angle between the first adjustment device A2 and the second adjustment device A3, wherein the opening and closing angle is negatively correlated with the supporting force provided to the target object through the human body fixing device A4, and the supporting force is used to resist the gravity of the target object.

[0122] Therein, fusion related to at least two single-modal data is performed to obtain a fusion result, and then the motion state is determined according to the fusion result. The fusion result is helpful for a more comprehensive evaluation of the motion state.

[0123] On this basis, combined with the application scenarios that may be involved in the embodiments of the present invention, the optional fusion solutions include data-level fusion solution, feature-level fusion solution and decision-level fusion solution.

[0124] The data-level fusion scheme can be understood as directly fusing the original signal after the sensor collects the original signal, for example, the features of the plantar pressure signal, sEMG signal and lower limb IMU signal are unified into a feature vector for analysis. This fusion scheme can retain all information, but is susceptible to noise and signal redundancy. The feature-level fusion scheme is to extract features from each sensor first, and then fuse the features of each sensor. This fusion scheme can reduce noise while maintaining signal diversity. For example, the muscle activity features of sEMG, the acceleration features of IMU and the gait features of plantar pressure can be combined to evaluate the athletic ability of the target object. The decision-level fusion scheme is that each sensor analyzes and makes decisions independently, and then fuses the decision results of each sensor. This fusion scheme is suitable for distributed decision-making in multi-sensor systems.

[0125] Optional fusion solutions include machine learning algorithms and deep learning models. The machine learning algorithm can be, for example, a decision tree, a support vector machine (SVM), and a random forest, which can perform classification or regression analysis based on multimodal features to determine the motion state and weight requirements of the target object in real time; the deep learning model can be, for example, a convolutional neural network (CNN) and a recurrent neural network (RNN), which can automatically extract high-dimensional features from multimodal data to achieve more accurate state recognition and weight adjustment.

[0126] Optional fusion solutions include Kalman filtering, which can be used to fuse lower limb IMU signals and plantar pressure signals to improve the accuracy of gait analysis and posture analysis; there can also be weighted fusion, which assigns different weights to the characteristics of different sensors. For example, a higher weight is given to sEMG signals when detecting fatigue, and a higher weight is given to lower limb IMU signals when detecting posture, and so on. No specific limitation is made here.

[0127] The technical solution of the embodiment of the present invention can provide a comprehensive assessment of the movement state by collecting and fusing multimodal data, thereby improving the accuracy of the movement state assessment and further improving the accuracy of the target weight loss determination.

[0128] An optional technical solution, the fusion submodule includes a single-modal feature acquisition unit and a feature fusion unit; wherein,

[0129] A unimodal feature obtaining unit is used to extract features from each unimodal data in the multimodal data to obtain unimodal features;

[0130] The feature fusion unit is used to fuse the obtained single-modal features to obtain a fusion result.

[0131] The feature-level fusion scheme described above can reduce noise while maintaining signal diversity.

[0132] On this basis, an optional unimodal feature acquisition unit is specifically used for: when the unimodal data is the surface electromyography signal of the lower limbs, feature extraction is performed on the surface electromyography signal of the lower limbs to obtain unimodal features that characterize the activation degree and / or fatigue condition of the lower limb muscles of the target object.

[0133] Exemplarily, sEMG signals are used to analyze the activation degree and / or fatigue of lower limb muscles. The feature extraction scheme may include at least one of time domain features, frequency features, and time-frequency threshold features. Specifically,

[0134] Time domain characteristics: (1) Mean and variance: used to analyze the overall level and fluctuation of muscle activity; (2) Root mean square (RMS): reflects the intensity of muscle contraction and is a commonly used feature for analyzing muscle workload; (3) Integrated electromyogram (IEMG): used to evaluate the overall intensity of muscle activity.

[0135] Frequency domain features: (1) Median frequency (MDF) and mean power frequency (MPF): These two features can reflect the fatigue state of the muscle. As fatigue increases, the signal frequency usually decreases.

[0136] Time-frequency domain features: (1) Wavelet transform and short-time Fourier transform: The time-frequency analysis method can be used to extract the frequency components of the electromyographic signal at different times, helping to identify muscle contraction patterns and fatigue conditions.

[0137] The above technical solution realizes the effective feature extraction of lower limb surface electromyography signals.

[0138] Another optional unimodal feature obtaining unit is specifically used for: when the unimodal data is a lower limb inertial measurement signal, feature extraction is performed on the lower limb inertial measurement signal to obtain a unimodal feature that characterizes at least one of the swing amplitude, swing rhythm, stability, abnormality and tilt of the target object's gait.

[0139] For example, the IMU sensor can measure the acceleration, angular velocity and posture of the target object through an accelerometer and a gyroscope. Feature extraction schemes may include: Angular velocity: measuring the rotational angular velocity of the lower limbs during movement through a gyroscope to analyze the swing amplitude and rhythm of the gait; Linear acceleration: used to detect the acceleration and deceleration of the lower limbs during walking to help determine the stability of the gait; Posture estimation: calculating the posture changes of the lower limbs through the fusion of the accelerometer and the gyroscope to analyze abnormalities or tilt phenomena in the gait.

[0140] The above technical solution realizes effective feature extraction of lower limb IMU signals.

[0141] Alternatively, the unimodal feature obtaining unit is specifically used to: when the unimodal data is a plantar pressure signal, perform feature extraction on the plantar pressure signal to obtain a unimodal feature that characterizes the stability of the gait of the target object.

[0142] For example, the sensor of the plantar pressure measurement module can detect the pressure changes in different areas of the plantar during gait. This example can determine whether the target object has an abnormal force pattern through pressure distribution: analyzing the pressure distribution of the forefoot, midfoot and hindfoot, and help judge the walking stability; plantar contact area: determine the size of the contact area between the foot and the ground according to the pressure distribution, and then evaluate the stability during gait.

[0143] The above technical solution realizes effective feature extraction of plantar pressure signals.

[0144] In order to better understand the working process of the lower limb rehabilitation walking aid system as a whole, the following Figure 8 The examples given are used as examples for illustrative purposes. Figure 8 :

[0145] In order to achieve adaptive weight loss of a multimodal lower limb rehabilitation walker, this example collects the actual weight, sEMG signals, lower limb IMU signals, and plantar pressure signals of the target object, extracts and fuses these signals through features, processes them through the host computer, and sends control instructions to the lower limb rehabilitation walker. At this time, the lower limb rehabilitation walker can achieve adaptive weight loss by adjusting the opening and closing height of the lower limb rehabilitation walker in real time through PID control through the built-in torque motor and force feedback motor.

[0146] Among them, PID control ensures that the support force provided by the lower limb rehabilitation walker to the target object matches the real-time motion state of the target object by adjusting the motor output. For example, the support force needs to be increased when the gait is unstable, and the support force is gradually reduced when the muscle activity is normal. PID control calculates the error between the support force output by the current motor and the target weight loss, and calculates the new motor output adjustment parameters based on the error, and adjusts the motor output accordingly. In addition, the force feedback motor can detect the real-time weight-bearing situation of the target object. If the pressure applied by the target object exceeds the set range, PID control can automatically increase the weight loss support.

[0147] In addition, the system can continuously monitor the motion status and support conditions of the target object, and dynamically adjust the PID control parameters based on real-time monitoring results to optimize the weight loss effect.

[0148] Among them, the specific steps of adaptive weight loss are as follows:

[0149] Initialization: The system sets the initial weight loss support based on the actual weight and training goals of the target object. Real-time monitoring and data acquisition: Multimodal data is collected in real time, and the motion state of the target object is analyzed through multimodal data fusion. PID control adjustment: Through PID control, the motor output is adjusted according to the real-time error, and the weight loss force is dynamically adjusted. State feedback and adjustment: If the target object is detected to have unstable gait, muscle fatigue or abnormal force feedback, PID control can quickly adjust the support force to ensure the safety of the target object, and provide more accurate support to the target object through the force feedback motor. Training completion and summary: At the end of each training, the system can record the target object's motion data and weight loss support, generate a report and adjust the initial settings for the next training, thereby ensuring the personalization of lower limb rehabilitation training.

[0150] In the above example, adaptive weight loss of a lower limb rehabilitation walker is achieved by combining multimodal data. At the same time, based on the characteristics of adaptive weight loss, the lower limb rehabilitation walker also has the characteristics of personalized training program generation, long-term data evaluation, and multi-level safety feedback mechanism, which completely revolutionizes the way of lower limb rehabilitation training, thereby greatly improving the accuracy, safety and effectiveness of the target objects during the training process.

[0151] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A lower limb rehabilitation walking aid system, characterized in that: include: Lower limb rehabilitation walker; among them, The lower limb rehabilitation walker comprises a movable device movable on the ground, a first adjustment device, a second adjustment device, a human body fixing device and a main control device, one end of the movable device is connected to the first adjustment device in a V-shaped rotation and the other end is connected to the second adjustment device in a V-shaped rotation, the first adjustment device is connected to the second adjustment device in an X-shaped rotation, the first adjustment device is provided with a first torque motor and a force feedback motor, the force feedback motor is rigidly connected to the human body fixing device, and the second adjustment device is provided with a second torque motor; The main control device includes a pressure acquisition module, a target weight loss acquisition module, a motor output adjustment parameter acquisition module and a torque motor output adjustment module; wherein, The pressure acquisition module is used to acquire, through the force feedback motor, the pressure applied on the human body fixation device by the target subject who is wearing the human body fixation device for lower limb rehabilitation training; The target weight loss obtaining module is used to obtain the target weight loss of the target object; The motor output adjustment parameter obtaining module is used to perform proportional integral differential control according to the error between the pressure and the target weight loss to obtain the motor output adjustment parameter; The torque motor output adjustment module is used to adjust the output of the first torque motor and / or the second torque motor according to the motor output adjustment parameters to adjust the opening and closing angle between the first adjustment device and the second adjustment device, wherein the opening and closing angle is negatively correlated with the supporting force provided to the target object by the human body fixing device, and the supporting force is used to resist the gravity of the target object.

2. The system according to claim 1, characterized in that The main control device also includes a force feedback motor output adjustment module: wherein, The force feedback motor output adjustment module is used to adjust the output of the force feedback motor according to the motor output adjustment parameter to control the human body fixing device to rotate around the target object.

3. The system according to claim 1, characterized in that Also includes: Host computer; among them, The host computer includes: a control instruction sending module; wherein, The control instruction sending module is used to send control instructions to the lower limb rehabilitation walker; The target weight loss obtaining module is specifically configured to respond to the received control instruction, analyze the control instruction, and obtain the target weight loss of the target object.

4. The system according to claim 3, characterized in that The host computer also includes: a data acquisition module and a control instruction generation module; wherein, The data acquisition module is used to acquire the training data of the target object; The control instruction generation module is used to determine the motion state of the target object according to the training data, and generate the control instruction according to the motion state.

5. The system according to claim 4, characterized in that The training data is multimodal data, and the multimodal data includes at least two types of unimodal data; The control instruction generation module includes a fusion submodule and a control instruction generation submodule; wherein, The fusion submodule is used to perform fusion related to at least two types of the single-modal data to obtain a fusion result; The control instruction generation submodule is used to determine the motion state of the target object according to the fusion result, and generate the control instruction according to the motion state.

6. The system according to claim 5, characterized in that The fusion submodule includes a single-modal feature acquisition unit and a feature fusion unit; wherein, The unimodal feature obtaining unit is used to extract features from each of the at least two types of unimodal data to obtain unimodal features; The feature fusion unit is used to fuse the obtained single-modal features to obtain a fusion result.

7. The system according to claim 6, characterized in that The unimodal feature obtaining unit is specifically used for: In the case where the unimodal data is a lower limb surface electromyographic signal, feature extraction is performed on the lower limb surface electromyographic signal to obtain a unimodal feature characterizing the activation degree and / or fatigue condition of the lower limb muscles of the target object; and / or, In the case where the unimodal data is a lower limb inertial measurement signal, feature extraction is performed on the lower limb inertial measurement signal to obtain a unimodal feature that characterizes at least one of the swing amplitude, swing rhythm, stability, abnormality and tilt of the gait of the target object; and / or, In the case that the unimodal data is a plantar pressure signal, feature extraction is performed on the plantar pressure signal to obtain a unimodal feature that characterizes the stability.

8. The system according to claim 4, characterized in that In the case where the motion state indicates that the target object has a tendency to fall, the control instruction includes a weight adjustment sub-instruction and a support force adjustment sub-instruction, and the main control device also includes a support force adjustment module; wherein, The target weight loss obtaining module is further used to analyze the weight adjustment sub-instruction in response to the received weight adjustment sub-instruction to obtain the target weight loss of the target object; The support force adjustment module is used to adjust the output of the force feedback motor in response to the received support force adjustment sub-instruction to control the human body fixing device to rotate around the target object.

9. The system according to claim 4, characterized in that The host computer also includes: a personalized training program acquisition module; wherein, The personalized training program acquisition module is used to acquire the personalized training program of the target object; The control instruction generation module is specifically used to determine the motion state of the target object according to the training data, and generate the control instruction according to the motion state and the personalized training plan.

10. The system according to claim 9, characterized in that The host computer also includes: a rehabilitation training record acquisition module and a personalized training program generation module; The rehabilitation training record acquisition module is used to acquire the rehabilitation training record of the target subject during the rehabilitation training process using the lower limb rehabilitation walker; The personalized training program generation module is used to generate the personalized training program based on the rehabilitation training record.

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