A finger training device combined with electroencephalogram signal feedback

Abstract

The application discloses a finger training device combined with electroencephalogram signal feedback, which comprises an electroencephalogram acquisition device and a host computer, the host computer comprises a shell, a plurality of fine pinching holes, a plurality of fine screwing holes, a plurality of hanging elbow perforations and a hanging elbow translation hole are formed in the upper surface of the shell, a display screen is fixedly arranged above the upper surface of the shell, a circuit board is arranged in the shell, and an MCU, a wireless receiver, an infrared sensor detection cluster, a limit sensor detection cluster, a disc sensor detection unit, a wedge-shaped disc sensor detection unit, a probe circuit unit and a display unit are integrated on the circuit board. The application integrates the electroencephalogram detection device, can acquire the electroencephalogram information of a user in real time, combines finger flexibility detection training with brain nerve activity, and is additionally provided with a plurality of micro-motion detection functions which can detect finger flexibility from different aspects, cover a plurality of movement forms of fingers, make the evaluation result more comprehensive and accurate, and are more rich in function.

Description

Technical Field

[0001] This application relates to the field of rehabilitation training equipment technology, specifically to a finger training device that incorporates electroencephalogram (EEG) signal feedback. Background Technology

[0002] Brain-computer interface (BCI) technology is a technology that allows the human brain to interact with a computer system, enabling direct control of the computer system and other external devices via the human brain. BCI technology has been widely applied in fields such as medicine, gaming, assistive communication, and psychology.

[0003] Currently, most finger dexterity testing and training devices on the market focus solely on detecting hand movements themselves. For example, they obtain finger dexterity values ​​by having users perform actions such as inserting and removing metal rods or tightening screws. However, these devices lack real-time monitoring and feedback of brain neural activity. The brain's neural regulation ability is closely related to finger motor function, and traditional devices cannot combine finger movement data with EEG information, making it difficult to comprehensively assess the connection between a user's hand motor ability and brain neural function. In addition, most devices only provide single-dimensional movement training (such as grasping or rotation), lacking multi-dimensional and comprehensive movement training. Utility Model Content

[0004] Therefore, this application provides a finger training device that combines EEG signal feedback to solve the problems of existing finger dexterity detection and training devices being unable to combine finger movement data with EEG information and having limited functionality.

[0005] To achieve the above objectives, this application provides the following technical solution:

[0006] A finger training device incorporating EEG signal feedback includes an EEG acquisition device and a main unit. The main unit includes a housing. The upper surface of the housing has multiple fine pinching holes on the left side and multiple fine twisting holes on the right side. The lower surface of the housing has multiple elbow-through holes along the long side of the housing. An elbow translation hole is provided between the multiple elbow-through holes and the long side of the housing. A display screen is fixedly installed in the middle of the upper surface of the housing. A rod-shaped probe insertion hole is provided on the side of the housing.

[0007] The housing contains a circuit board that integrates an MCU, a wireless receiver, an infrared sensor detection cluster, a limit sensor detection cluster, a disc sensor detection unit, a wedge-shaped disc sensor detection unit, a probe circuit unit, and a display unit. The wireless receiver, the infrared sensor detection cluster, the limit sensor detection cluster, the disc sensor detection unit, the wedge-shaped disc sensor detection unit, the probe circuit unit, and the display unit are all electrically connected to the MCU, and the display unit is electrically connected to the display screen.

[0008] The positions of the infrared sensor detection cluster, the limit sensor detection cluster, the disc sensor detection unit, the wedge-shaped disc sensor detection unit, and the display unit on the circuit board correspond to the positions of the plurality of fine pinch holes, the plurality of fine screw holes, the plurality of cantilever perforations, the cantilever translation holes, and the display screen on the upper surface of the housing, respectively. The position of the probe circuit unit on the circuit board corresponds to the position of the rod-shaped probe insertion hole. The EEG acquisition device is equipped with a wireless transmitter, and the EEG acquisition device communicates with the wireless receiver in the host through the wireless transmitter.

[0009] Preferably, the side of the housing is provided with a power supply and communication port, and a communication and electrical adapter unit is integrated on the circuit board at a position corresponding to the power supply and communication port. The communication and electrical adapter unit is electrically connected to the MCU and is used for power supply and communication with the host computer.

[0010] Preferably, the power supply and communication jack adopts a Type-C interface, which is used for electrical connection with a host computer or power supply.

[0011] Preferably, the device also includes an EEG display lamp assembly, which is fixedly disposed on the upper surface of the housing and located between the plurality of fine pinch holes and the plurality of fine screw holes. An LED unit is integrated on the circuit board, the input terminal of the LED unit is electrically connected to the output terminal of the MCU, and the output terminal of the LED unit is electrically connected to the EEG display lamp assembly.

[0012] Preferably, a warning light is also included, which is fixedly installed below the EEG display light group. An alarm circuit unit is integrated on the circuit board. The input terminal of the alarm circuit unit is electrically connected to the output terminal of the MCU, and the output terminal of the alarm circuit unit is electrically connected to the warning light.

[0013] Preferably, it also includes function buttons, which are fixedly disposed above the upper surface of the housing, next to the display screen.

[0014] Preferably, the main body of the housing is made of nylon, and the upper surface panel of the housing is made of aluminum oxide.

[0015] Preferably, the plurality of cantilever holes are 7 sets of wedge-shaped holes with different diameters.

[0016] Preferably, the EEG acquisition device adopts a forehead patch design.

[0017] Compared with the prior art, this application has at least the following beneficial effects:

[0018] This application provides a finger training device incorporating EEG signal feedback, including an EEG acquisition device and a main unit. The main unit includes a housing with multiple fine pinching holes, multiple fine twisting holes, multiple elbow insertion holes, and multiple elbow translation holes on its upper surface. A display screen is fixedly mounted in the center of the upper surface of the housing. A circuit board is housed inside the housing, integrating an MCU, a wireless receiver, an infrared sensor detection cluster, a limit sensor detection cluster, a disc sensor detection unit, a wedge-shaped disc sensor detection unit, a probe circuit unit, and a display unit. This application integrates an EEG detection device, enabling real-time acquisition of the user's EEG information. It combines finger dexterity testing and training with brain neural activity, thereby comprehensively assessing the user's hand motor ability and brain neural regulation ability. In addition, multiple micro-motion detection functions can detect finger dexterity from different aspects, covering various forms of finger movement, making the assessment results more comprehensive and accurate, and the functions more abundant. Attached Figure Description

[0019] To more intuitively illustrate the prior art and this application, exemplary drawings are provided below. It should be understood that the specific shapes and structures shown in the drawings should not generally be regarded as limiting conditions for implementing this application; for example, based on the technical concept disclosed in this application and the exemplary drawings, those skilled in the art are able to easily make conventional adjustments or further optimizations to the addition / reduction / classification, specific shapes, positional relationships, connection methods, size ratios, etc. of certain units (components).

[0020] Figure 1 A schematic diagram of a finger training device incorporating EEG signal feedback provided in this application;

[0021] Figure 2 A schematic diagram of the rod-shaped probe socket structure of a finger training device incorporating EEG signal feedback provided in this application;

[0022] Figure 3 A schematic diagram showing the location of the internal circuit board integrated module of a finger training device that incorporates EEG signal feedback, provided in this application;

[0023] Figure 4The circuit diagram provided in this application illustrates the principle of a finger training device that incorporates EEG signal feedback.

[0024] Explanation of reference numerals in the attached figures:

[0025] 1. Main unit; 2. Power and communication jack; 3. Display screen; 4. Function buttons; 5. Precision pinch hole; 6. Housing; 7. Top surface; 8. Rod-shaped probe jack; 9. EEG display light group; 10. Warning light; 11. Elbow perforation; 12. Elbow translation hole; 13. Rod-shaped probe; 14. Precision screw hole. Detailed Implementation

[0026] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0027] In the description of this application: unless otherwise stated, "a plurality of" means two or more. The terms "first," "second," "third," etc., in this application are intended to distinguish the objects referred to and do not have any special meaning in terms of technical connotation (e.g., they should not be construed as an emphasis on importance or order). Expressions such as "comprising," "including," and "having" also mean "not limited to" (certain units, components, materials, steps, etc.).

[0028] The terms used in this application, such as "upper," "lower," "left," "right," and "middle," are generally used to indicate the general relative positional relationship for the purpose of intuitive understanding by referring to the accompanying drawings, and are not absolute limitations on the positional relationship in the actual product.

[0029] Please see Figure 1 This application provides a finger training device combining EEG signal feedback, including an EEG acquisition device and a main unit 1 (i.e., a fine motor EEG feedback training device). The main unit 1 includes a housing 6. Multiple fine pinching holes 5 are provided on the left side of the upper surface 7 (i.e., the panel) of the housing 6, and multiple fine twisting holes 14 are provided on the right side of the upper surface 7 of the housing 6. Multiple elbow through holes 11 are provided along the long side of the upper surface 7 of the housing 6 below, and elbow translation holes 12 are provided between the multiple elbow through holes 11 and the long side of the housing 6. A display screen 3 is fixedly installed in the middle of the upper surface 7 of the housing 6. The display screen 3 is preferably an OLED display screen. A rod-shaped probe insertion hole 8 is provided on the side of the housing 6. Figure 2 As shown.

[0030] Please see Figure 3 and Figure 4This application provides a finger training device that combines EEG signal feedback. The housing 6 contains a circuit board, on which a main control chip (MCU), a wireless receiver, an infrared sensor detection cluster, a limit sensor detection cluster, a disc sensor detection unit, a wedge-shaped disc sensor detection unit, a probe circuit unit, and a display unit are integrated. The wireless receiver, the infrared sensor detection cluster, the limit sensor detection cluster, the disc sensor detection unit, the wedge-shaped disc sensor detection unit, the probe circuit unit, and the display unit are all electrically connected to the MCU, and the display unit is electrically connected to the display screen 3.

[0031] The positions of the infrared sensor detection cluster, the limit sensor detection cluster, the disc sensor detection unit, the wedge-shaped disc sensor detection unit, and the display unit on the circuit board correspond to the positions of multiple fine pinching holes 5, multiple fine twisting holes 14, multiple cantilever through holes 11, cantilever translation holes 12, and the display screen 3 on the upper surface 7 of the housing 6, respectively. The position of the probe circuit unit on the circuit board corresponds to the position of the rod-shaped probe insertion hole 8. The EEG acquisition device is equipped with a wireless transmitter, and the EEG acquisition device communicates with the wireless receiver in the host 1 through the wireless transmitter.

[0032] This application provides a finger training device incorporating EEG signal feedback. The housing 6 has a power supply and communication jack 2 on its side. A communication and electrical adapter unit is integrated on the circuit board at a position corresponding to the power supply and communication jack 2. The communication and electrical adapter unit is electrically connected to an MCU and is used for power supply and communication with a host computer. Preferably, the power supply and communication jack 2 uses a Type-C interface, which can both supply power and connect to a host PC via a Type-C data cable. Using a Type-C data cable combines power supply and PC communication functions, realizing power transmission and data interaction between the device and an external power source and the host PC. This convenient design can meet the needs of different usage scenarios.

[0033] This application provides a finger training device incorporating EEG signal feedback, which further includes an EEG display light group 9. The EEG display light group 9 is fixedly mounted on the upper surface 7 of the housing 6, and is located between multiple fine pinch holes 5 and multiple fine screw holes 14. An LED unit is integrated on the circuit board. The input terminal of the LED unit is electrically connected to the output terminal of the MCU, and the output terminal of the LED unit is electrically connected to the EEG display light group 9. Preferably, the EEG display light group 9 integrates five LEDs, which can display EEG parameter values ​​in real time, i.e., the number of LEDs lit can be adjusted based on the EEG parameter values.

[0034] This application provides a finger training device incorporating EEG signal feedback, which also includes an alarm light 10. The alarm light 10 is fixedly mounted below the EEG display light group 9. An alarm circuit unit is integrated on the circuit board. The input terminal of the alarm circuit unit is electrically connected to the output terminal of the MCU, and the output terminal of the alarm circuit unit is electrically connected to the alarm light 10. Preferably, the alarm light 10 is an audible and visual alarm light, which can indicate the current status through audible and visual alarms when the user triggers an alarm condition during operation.

[0035] The finger training device combined with EEG signal feedback provided in this application also includes a function button 4. The function button 4 is fixedly installed on the upper surface 7 of the housing 6, next to the display screen 3. The function button 4 is used by the user to select different function modules, set parameters, etc.

[0036] This application provides a finger training device that incorporates electroencephalogram (EEG) signal feedback. The main body of the shell 6 is made of PA66 nylon (impact strength ≥10kJ / m). 2 Made of 6061-T6 aluminum oxide (surface anodized), the upper surface 7 (i.e. panel) of the housing 6 is made of 6061-T6 aluminum oxide (surface anodized treatment). The dimensions of the entire housing 6 are 248×175×72mm (ergonomic handheld size), making it a portable desktop device.

[0037] This application provides a finger training device that incorporates EEG signal feedback. The device can capture pinching, twisting, piercing, and translating movements through a fine pinching hole 5, a fine twisting hole 14, a suspended elbow piercing hole 11, and a suspended elbow translation hole 12. Specifically:

[0038] I. Precise pinching motion capture

[0039] This application can capture fine pinching actions through fine pinching holes 5. There are 16 fine pinching holes 5, and the size of the 16 fine pinching holes 5 is φ3±0.05mm (ISO2768-m grade tolerance). The 16 fine pinching holes 5 form a hole array and are set on the left side of the upper surface 7 of the housing 6.

[0040] Correspondingly, the infrared sensor cluster integrated on the circuit board for detecting pinching motions has a range of 5mm and a resolution of 0.1mm.

[0041] During use, the user inserts and removes the metal rods from the 16 circular holes sequentially according to the device prompts. The device records data such as the insertion and removal time of each metal rod and whether it is accurately inserted into the hole in real time. It calculates the finger dexterity value through a built-in algorithm and displays it on the OLED display screen 3. The metal rods are made of TC4 stainless steel with a non-slip coating (coefficient of friction ≤0.15) on the surface.

[0042] II. Precision Twisting Motion Capture

[0043] This application captures fine-tightening actions through 16 fine-tightening holes 14. During use, the user screws in and out of the 16 mushroom-shaped nuts. The device records parameters such as the screwing time, screwing time, and uniformity of force during the screwing process for each nut, calculates the finger dexterity value, and displays it on the display screen 3.

[0044] The mushroom-shaped screw cap is made of stainless steel, specifically TC4 stainless steel, with a DLC coating on the surface (coefficient of friction ≤0.15).

[0045] III. Perforation Motion Capture

[0046] This application uses a suspended piercing hole 11 to capture the piercing action. The suspended piercing hole 11 is equipped with seven sets of wedge-shaped holes with different diameters (taper 1:50). In use, the user holds the rod-shaped probe 13 and attempts to touch the seven circular holes with a suspended elbow. During the touching process, the device uses a disk sensor to detect whether the rod-shaped probe 13 touches the hole wall. If it does not touch, the touching time and path are recorded; if it touches, the number of touches and other data are recorded, and finally, the finger dexterity value is calculated.

[0047] The rod-shaped probe 13 is made of stainless steel (bending stiffness ≥180GPa), and its overall impedance value is <2Ω, which is achieved through a three-dimensional detection unit. In this application, the rod-shaped probe 13 serves as a tool for user operation, used to complete actions such as elbow piercing and elbow translation. Its structural design conforms to ergonomics, making it easy for users to hold and operate.

[0048] IV. Translational Movement Capture

[0049] This application captures translational movements through the elbow translation hole 12. In use, the user uses the rod-shaped probe 13 to perform elbow translation, touching the wedge-shaped hole. The wedge-shaped disk sensor monitors whether the finger touches the hole wall and calculates the finger dexterity value according to relevant rules.

[0050] This application provides a finger training device incorporating EEG signal feedback. The EEG acquisition device adopts a forehead patch design (compliant with system FP1 / FP2 sites) and has a built-in dry electrode array. The dry electrode array uses 1 / 2 channel Ag / AgCl electrodes (contact impedance <20kΩ). During use, the user wears the EEG acquisition device on their forehead to collect EEG information in real time. This information is then transmitted wirelessly to a dedicated wireless receiver in the main unit, enabling real-time transmission of EEG data. The wireless signal uses the RF radio frequency protocol, with a sampling rate of 512Hz and a resolution of 16 bits.

[0051] This application provides a finger training device that incorporates EEG signal feedback, in which a 32-bit main control chip (MCU) is used. In this application, while the user performs the aforementioned micro-movement detection and training, the EEG acquisition device collects the user's EEG signals in real time and transmits them wirelessly to a dedicated wireless receiver in the main unit 1. The data processing chip (MCU) within the main unit 1 combines the EEG signals with the finger movement data, performing a series of algorithmic calculations, such as analyzing the correlation between brain neural activity and the accuracy and speed of finger movements. The calculation results are presented to the user through an OLED display screen in graphical and numerical forms, allowing the user to understand the impact of their brain's neural state on finger movements and thus make targeted adjustments during training.

[0052] It should be noted that in this application, the action signal is evaluated through four-dimensional action ability quantification, and the EEG signal is extracted using wavelet transform (db4 wavelet basis) to extract real-time focus, relaxation and other frequency band parameter values. These are all existing technologies and will not be described in detail here.

[0053] The specific steps for using the finger training device combining EEG signal feedback provided in this application are as follows:

[0054] Step 1: Equipment self-test;

[0055] - After connecting the Type-C power supply, the OLED display shows a 3-second startup animation;

[0056] - The main control chip performs hardware diagnostics (including sensor response testing, memory verification, and wireless module detection);

[0057] - Automatically paired frontal EEG acquisition device (2.4GHz band, pairing time <0.5 seconds).

[0058] Step 2: Create a user ID by manually entering it;

[0059] - Select user type (rehabilitation patient / professional athlete / regular user);

[0060] Download historical training data from the cloud (if it exists).

[0061] Step 3: Calibrate the EEG device;

[0062] - Secure the EEG acquisition headband to the FP1 / FP2 position on the forehead;

[0063] - The system automatically detects the electrode contact resistance (threshold < 10kΩ);

[0064] - Perform a 30-second baseline EEG recording (sampling rate 256Hz) to establish an individualized EEG baseline.

[0065] Step 4: Pre-testing phase (≥2 cycles);

[0066] - The system randomly generates a four-module test sequence (e.g., screwing → plugging and unplugging → piercing → translation);

[0067] - The OLED display shows dynamic task guidance icons and a countdown timer, allowing users to complete micro-actions based on the task guidance.

[0068] This application provides a finger training device that integrates EEG signal feedback. It integrates EEG detection equipment to acquire the user's EEG information in real time, combining finger dexterity testing and training with brain neural activity to comprehensively assess the user's hand motor ability and brain neural regulation ability. In addition, multiple micro-movement detection functions (fine pinching, fine knob insertion and removal, suspended elbow piercing, and suspended elbow translation) can detect finger dexterity from different aspects, covering multiple forms of finger movement, making the assessment results more comprehensive and accurate, and the functions more abundant.

[0069] The technical features of the above embodiments can be combined in any way (as long as there is no contradiction in the combination of these technical features). For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described; these embodiments not explicitly written should also be considered to be within the scope of this specification.

Claims

1. A finger training device incorporating electroencephalogram (EEG) signal feedback, characterized in that, The device includes an EEG acquisition device and a main unit. The main unit includes a housing. The upper surface of the housing has multiple fine pinch holes on the left side and multiple fine screw holes on the right side. The lower surface of the housing has multiple cantilever holes along the long side of the housing. A cantilever translation hole is provided between the multiple cantilever holes and the long side of the housing. A display screen is fixedly installed in the middle of the upper surface of the housing. A rod-shaped probe insertion hole is provided on the side of the housing. The housing contains a circuit board that integrates an MCU, a wireless receiver, an infrared sensor detection cluster, a limit sensor detection cluster, a disc sensor detection unit, a wedge-shaped disc sensor detection unit, a probe circuit unit, and a display unit. The wireless receiver, the infrared sensor detection cluster, the limit sensor detection cluster, the disc sensor detection unit, the wedge-shaped disc sensor detection unit, the probe circuit unit, and the display unit are all electrically connected to the MCU, and the display unit is electrically connected to the display screen. The positions of the infrared sensor detection cluster, the limit sensor detection cluster, the disc sensor detection unit, the wedge-shaped disc sensor detection unit, and the display unit on the circuit board correspond to the positions of the plurality of fine pinch holes, the plurality of fine screw holes, the plurality of cantilever perforations, the cantilever translation holes, and the display screen on the upper surface of the housing, respectively. The position of the probe circuit unit on the circuit board corresponds to the position of the rod-shaped probe insertion hole. The EEG acquisition device is equipped with a wireless transmitter, and the EEG acquisition device communicates with the wireless receiver in the host through the wireless transmitter.

2. The finger training device combining EEG signal feedback according to claim 1, characterized in that, The side of the housing is provided with a power supply and communication port. A communication and electrical adapter unit is integrated on the circuit board at a position corresponding to the power supply and communication port. The communication and electrical adapter unit is electrically connected to the MCU and is used for power supply and communication with the host computer.

3. The finger training device combining EEG signal feedback according to claim 2, characterized in that, The power supply and communication jack uses a Type-C interface, which is used for electrical connection with a host computer or power supply.

4. The finger training device combining EEG signal feedback according to claim 1, characterized in that, It also includes an EEG display light assembly, which is fixedly mounted on the upper surface of the housing and located between the plurality of fine pinch holes and the plurality of fine screw holes. An LED unit is integrated on the circuit board, the input terminal of the LED unit is electrically connected to the output terminal of the MCU, and the output terminal of the LED unit is electrically connected to the EEG display light assembly.

5. The finger training device combining EEG signal feedback according to claim 4, characterized in that, It also includes a warning light, which is fixedly installed below the EEG display light group. An alarm circuit unit is integrated on the circuit board. The input terminal of the alarm circuit unit is electrically connected to the output terminal of the MCU, and the output terminal of the alarm circuit unit is electrically connected to the warning light.

6. The finger training device combining EEG signal feedback according to claim 1, characterized in that, It also includes function buttons, which are fixedly mounted on the upper surface of the housing, next to the display screen.

7. The finger training device combining EEG signal feedback according to claim 1, characterized in that, The main body of the shell is made of nylon, and the upper surface panel of the shell is made of aluminum oxide.

8. The finger training device combining EEG signal feedback according to claim 1, characterized in that, The multiple cantilever holes are 7 sets of wedge-shaped holes with different diameters.

9. The finger training device combining EEG signal feedback according to claim 1, characterized in that, The EEG acquisition device adopts a forehead patch design.

Images