Active multifunctional rehabilitation training system

Abstract

The present application belongs to the technical field of medical devices, and relates to a rehabilitation training system, in particular to an active multifunctional rehabilitation training system, which comprises two parts of a hardware system and a software system. The hardware system comprises a signal acquisition module and a signal transmission module, and the software system comprises a signal processing module, a signal coding module and a signal mapping module. Compared with the existing rehabilitation training system, the muscle strength training device uses biological sensing based on surface electromyography, the grip and pinch strength training device uses a training device based on mechanical sensing, and the interesting rehabilitation training scene design makes the patient get rid of the traditional boring rehabilitation training mode, achieves the purpose of synchronous and coordinated training of the patient's limbs, eyes and brain, and at the same time, the patient can realize the training by himself without a therapist, so as to promote and accelerate the rehabilitation training effect.

Description

Technical Field

[0001] This invention belongs to the field of medical device technology, and relates to a rehabilitation training system, and more particularly to an active multifunctional rehabilitation training system. Background Technology

[0002] Stroke is characterized by high incidence, high mortality, and high disability rates, and its sequelae often have a profound impact on patients' limb function. Although rapid advancements in medical technology in recent years have increased the survival rate of stroke patients to 60%-70%, approximately 80% of these survivors still experience limb dysfunction. Limb dysfunction caused by stroke not only severely impacts patients' daily lives, but the increasing number of stroke patients each year also places a significant economic burden on their families and society as a whole. In recent years, with increasing attention paid to stroke rehabilitation, the stroke prevention and treatment system is gradually being improved. How to develop rehabilitation techniques for limb dysfunction caused by stroke is an urgent problem to be solved in the field of rehabilitation medicine.

[0003] Existing rehabilitation training relies on the help and guidance of rehabilitation therapists, but the training equipment is often mainly mechanical, lacking fun and being boring. It also fails to train the patient's ability to coordinate the limbs, eyes, brain and other senses, as well as the patient's responsiveness. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and propose an active multifunctional rehabilitation training system. This system overcomes the limitations of existing training equipment, which often focuses on mechanical exercise, lacks the fun of the training process, and fails to train the synchronous coordination of the patient's limbs, eyes, brain, and other senses, as well as the patient's insufficient responsiveness, thereby accelerating the rehabilitation training effect.

[0005] To achieve the above objectives, the present invention adopts the following specific technical solution:

[0006] This invention provides an active multifunctional rehabilitation training system, comprising a hardware system and a software system. The hardware system includes a signal acquisition module and a signal transmission module. The signal acquisition module is used to acquire surface electromyography (EMG) analog signals and human hand grip and pinch force analog signals. The signal transmission module is used to convert the EMG analog signals and human hand grip and pinch force analog signals acquired by the signal acquisition module into digital signals and send them to the software system. The software system includes a signal processing module, a signal encoding module, and a signal mapping module. The signal processing module is used to receive and process the EMG signals and human hand grip and pinch force signals uploaded by the signal transmission module. The signal encoding module is used to encode the EMG signals and human hand grip and pinch force signals processed by the signal processing module. The signal mapping module is used to map the EMG signals and human hand grip and pinch force signals encoded by the signal encoding module into changes in the position, speed, angle, and movement of a visualized object.

[0007] The signal acquisition module includes a wearable surface electromyography (EMG) sensor, a grip force signal sensing device, and a pinch force signal sensing device. The wearable surface EMG sensor is used to acquire simulated surface EMG signals, the grip force signal sensing device is used to acquire simulated grip force signals, and the pinch force signal sensing device is used to acquire simulated pinch force signals.

[0008] Furthermore, the wearable surface electromyography (EMG) sensor is equipped with three metal dry electrodes as signal sensing front-ends, which output surface EMG analog signals after signal amplification and processing circuitry.

[0009] Furthermore, the grip force signal sensing device includes two support rods and a bar-shaped pressure sensor. The bar-shaped pressure sensor is positioned between the two support rods and captures the grip force signal through the squeezing action of the two support rods.

[0010] Furthermore, the pinch force signal sensing device includes a cylindrical upper support cover, a cylindrical lower support cover, and a cylindrical pressure sensor. The cylindrical pressure sensor is disposed between the cylindrical upper support cover and the cylindrical lower support cover, and collects pinch force signals between different fingers through the squeezing action of the cylindrical upper support cover and the cylindrical lower support cover.

[0011] The signal transmission module includes a wireless transmission device and a wired transmission device. The wireless transmission device includes a Bluetooth transmitter and a Bluetooth receiver. The Bluetooth transmitter is connected to the signal acquisition module and is used to convert the surface electromyography (EMG) analog signals and human hand grip and pinch force analog signals acquired by the signal acquisition module into digital signals through A / D conversion and send them into space. The Bluetooth receiver is used to receive the signals sent from the Bluetooth transmitter and upload them to the software system. The wired transmission device includes a main control board, which is connected to the signal acquisition module and the computer. It is used to convert the surface EMG analog signals and human hand grip and pinch force analog signals acquired by the signal acquisition module into digital signals through A / D conversion and upload them directly to the software system.

[0012] Furthermore, both the Bluetooth transmitter and receiver use Bluetooth Low Energy Smart 5.0 technology and employ the nRF52840 Bluetooth chip.

[0013] Furthermore, the CPU in the main control board uses an STM32 series microcontroller.

[0014] The signal processing module in the software system includes a surface electromyography (EMG) signal processing unit and a grip and pinch force information processing unit. The EMG signal processing unit includes the following processing steps:

[0015] The surface electromyography signal processing unit performs median filtering on the signal using a sliding window with a window length of 100ms, and applies two sliding mean filters to the signal within the window to eliminate signal noise;

[0016] The grip strength and pinching strength information processing unit includes the following processing steps:

[0017] The grip and pinch force information processing unit calculates the average force within a 100ms sliding window as the overall force effect within the window.

[0018] The signal encoding module in the software system includes the following steps:

[0019] S1. Store the n signals from any given time in a buffer X = {X1, X2, ..., X...} n}middle;

[0020] S2. Find the maximum value X in buffer X. max and minimum value X min ;

[0021] S3. Summate all data in buffer X.

[0022]

[0023] S4. Subtract the maximum value X in the buffer. max and minimum value X min Take the average again

[0024]

[0025] S5. Determine two consecutive adjacent X's t X t-1 The change between values ​​is considered valid when the change exceeds a certain threshold TH, and the result is output as a new value.

[0026]

[0027] S6. The output result X o Further processing was performed to allow users to adjust the sensitivity of visual object control during rehabilitation training in different situations.

[0028]

[0029] Where a is one-tenth of the maximum value of the sampled signal, b is the maximum value of the sampled signal, c is one-twentieth of the maximum value of the sampled signal, and k is 0, 1, 2, 3, 4, 5, 6, representing 7 adjustable sensitivity levels.

[0030] The software system's signal mapping module maps encoded surface electromyography signals and human hand grip and pinch force signals into visual representations of changes in object position, velocity, angle, and motion as follows:

[0031] For visual object position mapping: the initial position is x0, and the signal output corresponding to the initial position is X. output =0, the range of the visualized object's position movement is x0 to x m Then the signal output X will be... output Mapped to the actual position x of the visualized object p :x p =x0+X output / (x m -x0-k×d), when x p >x m At that time, x p =x m ;

[0032] For visualizing object velocity mapping: Assuming the initial velocity is v0, the signal output corresponding to the initial velocity is X. output =0, the range of the visualized object's velocity change is v0 to v m Then the signal output X will be... output Mapped to the actual velocity v of the visualized object p :v p =v0+X output / (v m -v0-k×d), when v p >vm At that time, v p =v m ;

[0033] For angle mapping of visualized objects: the initial angle is w0, and the signal output corresponding to the initial angle is X. output =0, the range of the visual object's angle change is w0 to w m Then the signal output X will be... output Mapped to the actual angle w of the visualized object p :w p =w0+X output / (w m -w0-k×d), when w p >w m At that time, w p =w m ;

[0034] For motion mapping of visualized objects: define n actions, numbered 1, 2, 3...n, and the range of motion changes of the visualized objects is m1, m2,...,m n Calculate the signal output X output Mapped to the action number i of the visualized object: i = 1 + X output / (1+k×d), round the first decimal place of i to the nearest integer and map it to the action: m i , when i>n, take i=n;

[0035] Where k is a parameter in the sensitivity control of the visualized object, and k takes values ​​of 0, 1, 2, 3, 4, 5, and 6, representing 7 adjustable sensitivity levels respectively. d is a constant, which is one-tenth of the maximum value of the signal output.

[0036] The present invention can achieve the following technical effects:

[0037] This invention utilizes biosensing based on surface electromyography and training devices based on mechanical sensing, combined with an engaging rehabilitation training scenario design, to free patients from the traditional, monotonous rehabilitation training mode. It achieves the goal of synchronously coordinating the patient's limbs, eyes, and brain. This training system does not require a therapist; patients can train on their own and improve their ability to autonomously control the motor central nervous system, thereby promoting motor function and accelerating the rehabilitation training effect. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the overall process of the active multifunctional rehabilitation training system provided in an embodiment of the present invention.

[0039] Figure 2This is a schematic diagram of the grip force signal sensing device provided in an embodiment of the present invention.

[0040] Figure 3 This is a schematic diagram of the structure of the pinch force signal sensing device provided in an embodiment of the present invention.

[0041] Figure 4 This is a schematic diagram of the logical structure of a wireless transmission device provided according to an embodiment of the present invention.

[0042] Figure 5 This is a schematic diagram of the hardware structure connection of a Bluetooth wireless transmitter provided according to an embodiment of the present invention.

[0043] Figure 6 This is a schematic diagram of the hardware structure connection of a Bluetooth wireless receiver provided according to an embodiment of the present invention.

[0044] Figure 7 This is a schematic diagram of the logical structure of a wired transmission device provided according to an embodiment of the present invention.

[0045] The reference numerals in the accompanying drawings include: support rod 1, bar pressure sensor 2, cylindrical upper support cover 3, cylindrical lower support cover 4, and cylindrical pressure sensor 5. Detailed Implementation

[0046] In the following description, embodiments of the invention will be described with reference to the accompanying drawings. In the description below, the same modules are denoted by the same reference numerals. Where the same reference numerals are used, their names and functions are also the same. Therefore, their detailed description will not be repeated.

[0047] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not constitute a limitation thereof.

[0048] Figure 1This invention illustrates the overall process of an active multifunctional rehabilitation training system, comprising a hardware system and a software system. The hardware system includes a signal acquisition module and a signal transmission module. The signal acquisition module acquires surface electromyography (EMG) analog signals and hand grip and pinch force analog signals. The signal transmission module converts the EMG analog signals and hand grip and pinch force analog signals acquired by the signal acquisition module into digital signals and uploads them to the software system. The software system includes a signal processing module, a signal encoding module, and a signal mapping module. The signal processing module receives and processes the EMG signals and hand grip and pinch force signals uploaded by the signal transmission module. The signal encoding module encodes the processed EMG signals and hand grip and pinch force signals. The signal mapping module maps the encoded EMG signals and hand grip and pinch force signals into changes in the position, speed, angle, and movement of a visualized object, thereby controlling the visualized object to achieve the purpose of rehabilitation training.

[0049] The signal acquisition module includes a wearable surface electromyography (EMG) sensor, a grip force signal sensing device, and a pinch force signal sensing device. The wearable surface EMG sensor is used to acquire simulated surface EMG signals, the grip force signal sensing device is used to acquire simulated grip force signals, and the pinch force signal sensing device is used to acquire simulated pinch force signals.

[0050] The wearable surface electromyography (EMG) sensor is equipped with three metal dry electrodes as signal sensing front-ends, and outputs surface EMG analog signals after signal amplification and processing circuitry.

[0051] Figure 2 The structure of the grip force signal sensing device is shown. The grip force signal sensing device includes two support rods and a bar pressure sensor. The bar pressure sensor is located between the two support rods and captures the grip force signal through the squeezing action of the two support rods.

[0052] Figure 3 The structure of the pinch force signal sensing device is shown. The pinch force signal sensing device includes a cylindrical upper support cover, a cylindrical lower support cover, and a cylindrical pressure sensor. The cylindrical pressure sensor is disposed between the cylindrical upper support cover and the cylindrical lower support cover. The cylindrical pressure sensor collects the pinch force signal between different fingers through the squeezing action of the cylindrical upper support cover and the cylindrical lower support cover.

[0053] The signal transmission module includes wireless transmission devices and wired transmission devices. Figure 4 The logical structure of the wireless transmission device is shown. The wireless transmission device includes a Bluetooth transmitter and a Bluetooth receiver. Figure 5The hardware structure of the Bluetooth wireless transmitter is shown. The Bluetooth transmitter is connected to the signal acquisition module, which converts the surface electromyography analog signals and the human hand grip and pinch force analog signals acquired by the signal acquisition module into digital signals via A / D conversion and then transmits them into space. Figure 6 The hardware structure connection of the Bluetooth wireless receiver is shown. The Bluetooth receiver is used to receive signals sent from the Bluetooth transmitter and upload them to the software system. Figure 7 The logical structure of the wired transmission device is shown. The wired transmission device includes a main control board, which is connected to the signal acquisition module and the computer. It is used to convert the surface electromyography analog signals and the human hand grip and pinch force analog signals acquired by the signal acquisition module into digital signals through A / D conversion and upload them directly to the software system.

[0054] The Bluetooth transmitter and receiver can use Bluetooth Low Energy Smart 5.0 technology and utilize the nRF52840 Bluetooth chip.

[0055] The CPU in the main control board uses an STM32 series microcontroller.

[0056] The signal processing module in the software system includes a surface electromyography (EMG) signal processing unit and a grip and pinch force information processing unit. The EMG signal processing unit includes the following processing steps:

[0057] The surface electromyography signal processing unit performs median filtering on the signal using a sliding window with a window length of 100ms, and applies two sliding mean filters to the signal within the window to eliminate signal noise;

[0058] The grip strength and pinching strength information processing unit includes the following processing steps:

[0059] The grip and pinch force information processing unit calculates the average force within a 100ms sliding window as the overall force effect within the window.

[0060] The signal encoding module in the software system includes the following steps:

[0061] S1. Store the n signals from any given time in a buffer X = {X1, X2, ..., X...} n}middle;

[0062] S2. Find the maximum value X in buffer X. max and minimum value X min ;

[0063] S3. Summate all data in buffer X.

[0064]

[0065] S4. Subtract the maximum value X in the buffer. maxand minimum value X min Take the average again

[0066]

[0067] S5. Determine two consecutive adjacent X's t X t-1 The change between values ​​is considered valid when the change exceeds a certain threshold TH, and the result is output as a new value.

[0068]

[0069] S6. The output result X o Further processing was performed to allow users to adjust the sensitivity of visual object control during rehabilitation training in different situations.

[0070]

[0071] Where a is one-tenth of the maximum value of the sampled signal, b is the maximum value of the sampled signal, c is one-twentieth of the maximum value of the sampled signal, and k is 0, 1, 2, 3, 4, 5, 6, representing 7 adjustable sensitivity levels.

[0072] The software system's signal mapping module maps encoded surface electromyography signals and human hand grip and pinch force signals into visual representations of changes in object position, velocity, angle, and motion as follows:

[0073] For visual object position mapping: the initial position is x0, and the signal output corresponding to the initial position is X. output =0, the range of the visualized object's position movement is x0 to x m Then the signal output X will be... output Mapped to the actual position x of the visualized object p :x p =x0+X output / (x m -x0-k×d), when x p >x m At that time, x p =x m ;

[0074] For visualizing object velocity mapping: Assuming the initial velocity is v0, the signal output corresponding to the initial velocity is X. output =0, the range of the visualized object's velocity change is v0 to v m Then the signal output X will be... output Mapped to the actual velocity v of the visualized object p :v p =v0+X output / (v m-v0-k×d), when v p >v m At that time, v p =v m ;

[0075] For angle mapping of visualized objects: the initial angle is w0, and the signal output corresponding to the initial angle is X. output =0, the range of the visual object's angle change is w0 to w m Then the signal output X will be... output Mapped to the actual angle w of the visualized object p :w p =w0+X output / (w m -w0-k×d), when w p >w m At that time, w p =w m ;

[0076] For motion mapping of visualized objects: define n actions, numbered 1, 2, 3...n, and the range of motion changes of the visualized objects is m1, m2,...,m n， Calculate signal output X output Mapped to the action number i of the visualized object: i = 1 + X output / (1+k×d), round the first decimal place of i to the nearest integer and map it to the action: m i , when i>n, take i=n;

[0077] Where k is a parameter in the sensitivity control of the visualized object, and k takes values ​​of 0, 1, 2, 3, 4, 5, and 6, representing 7 adjustable sensitivity levels respectively. d is a constant, which is one-tenth of the maximum value of the signal output.

[0078] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0079] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

[0080] The specific embodiments of the present invention described above do not constitute a limitation on the scope of protection of the present invention. Any other corresponding changes and modifications made in accordance with the technical concept of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. An active, multifunctional rehabilitation training system, characterized in that, include: The system comprises a hardware system and a software system. The hardware system includes a signal acquisition module and a signal transmission module. The signal acquisition module is used to acquire surface electromyography (EMG) analog signals and human hand grip and pinch force analog signals. The signal transmission module is used to convert the EMG analog signals and human hand grip and pinch force analog signals acquired by the signal acquisition module into digital signals and send them to the software system. The software system includes a signal processing module, a signal encoding module, and a signal mapping module. The signal processing module is used to receive and process the EMG signals and human hand grip and pinch force signals uploaded by the signal transmission module. The signal encoding module is used to encode the EMG signals and human hand grip and pinch force signals processed by the signal processing module. The signal mapping module is used to map the EMG signals and human hand grip and pinch force signals encoded by the signal encoding module into changes in the position, velocity, angle, and movement of a visualized object. The signal encoding module processes the surface electromyography signal and the grip and pinch force signals of the human hand as follows: S1. Store the n signals from any given time in a buffer. middle; S2, Locate the buffer The maximum value in and minimum value ; S3, Regarding the buffer Sum all the data: ； S4. Subtract the maximum value in the buffer. and minimum value Take the average again: ； S5. Determine two consecutive adjacent pairs. The amount of change between them, when the amount of change is greater than a certain threshold TH, this time Validate and output as the new value: ； S6. Output results Further processing will be performed to allow users to adjust the sensitivity of visual object control during rehabilitation training in different situations: ； in, Take one-tenth of the maximum value of the sampled signal. Take the maximum value of the sampled signal. Take one-twentieth of the maximum value of the sampled signal. The values ​​0, 1, 2, 3, 4, 5, and 6 represent seven adjustable sensitivity levels.

2. The active multifunctional rehabilitation training system according to claim 1, characterized in that, The signal acquisition module includes a wearable surface electromyography (EMG) sensor, a grip force signal sensing device, and a pinch force signal sensing device. The wearable surface EMG sensor is used to acquire simulated surface EMG signals, the grip force signal sensing device is used to acquire simulated grip force signals, and the pinch force signal sensing device is used to acquire simulated pinch force signals.

3. The active multifunctional rehabilitation training system according to claim 1, characterized in that, The signal transmission module includes a wireless transmission device and a wired transmission device. The wireless transmission device includes a Bluetooth transmitter and a Bluetooth receiver. The Bluetooth transmitter is connected to the signal acquisition module and is used to convert the surface electromyography (EMG) analog signals and the human hand grip and pinch force analog signals acquired by the signal acquisition module into digital signals and send them into space. The Bluetooth receiver is used to receive the signals sent from the Bluetooth transmitter and upload them to the software system. The wired transmission device includes a main control board. The main control board is connected to the signal acquisition module and the computer and is used to convert the surface EMG analog signals and the human hand grip and pinch force analog signals acquired by the signal acquisition module into digital signals and upload them directly to the software system.

4. The active multifunctional rehabilitation training system according to claim 2, characterized in that, The wearable surface electromyography (EMG) sensor is equipped with three metal dry electrodes as signal sensing front-ends, and outputs surface EMG analog signals after signal amplification and processing circuitry.

5. The active multifunctional rehabilitation training system according to claim 2, characterized in that, The grip force signal sensing device includes two support rods and a bar-shaped pressure sensor. The bar-shaped pressure sensor is located between the two support rods, and the two support rods are in contact with the bar-shaped pressure sensor near their ends. The bar-shaped pressure sensor captures the grip force signal through the squeezing action of the two support rods.

6. The active multifunctional rehabilitation training system according to claim 2, characterized in that, The pinch force signal sensing device includes a cylindrical upper support cover, a cylindrical lower support cover, and a cylindrical pressure sensor. The cylindrical pressure sensor is disposed between the cylindrical upper support cover and the cylindrical lower support cover. The cylindrical pressure sensor collects pinch force signals between different fingers through the squeezing action of the cylindrical upper support cover and the cylindrical lower support cover.

7. The active multifunctional rehabilitation training system according to claim 1, characterized in that, The signal processing module includes a surface electromyography (SEMG) signal processing unit and a grip and pinch force information processing unit. The SEMG signal processing unit performs median filtering on the signal using a sliding window with a window length of 100ms, and applies two sliding mean filtering operations to the signal within the window to eliminate signal noise. The grip and pinch force information processing unit calculates the average force within the 100ms sliding window as the overall force effect within the window.

8. The active multifunctional rehabilitation training system according to claim 1, characterized in that, The signal mapping module maps the encoded surface electromyography signals and the grip and pinch force signals of the human hand into the visualization of changes in the position, velocity, angle, and movement of an object as follows: For visual object position mapping: the initial position is... Signal output corresponding to the initial position The range of movement of the visualized object is Then the signal will be output. Mapped to the actual position of the visualized object : ,when hour, ; For visualizing object velocity mapping: assuming the initial velocity is... Signal output corresponding to the initial velocity The range of the speed change of a visualized object is Then the signal will be output. Mapped to the actual speed of the visualized object : ,when hour, ; For angle mapping of visualized objects: the initial angle is... Signal output corresponding to the initial angle The range of changes in the angle of a visualized object is Then the signal will be output. Mapped to the actual angle of the visualized object : ,when hour, ; For motion mapping of visualized objects: define n actions, with action numbers 1, 2, 3...n. The range of changes in the visualized object's actions is: Calculate signal output Mapped to action numbers of visual objects i : ,Will i Round the first decimal place to the nearest integer and map it to an action. ,when At that time, take ; Where k is a parameter in the sensitivity control of the visualized object, and k takes values ​​of 0, 1, 2, 3, 4, 5, and 6, representing 7 adjustable sensitivity levels respectively. d is a constant, which is one-tenth of the maximum value of the signal output.

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