A Balance Perception Enhancement System and Method Based on Neural Feedback

Abstract

This invention belongs to the field of non-invasive neurointervention technology, and relates to a balance perception enhancement system and method based on neurofeedback. The balance perception enhancement system includes: a balance perturbation application module, a data acquisition and processing module, a neurofeedback parameter calculation and mapping module, and a feedback information presentation module. The neurofeedback parameter calculation and mapping module calculates neurofeedback parameters, configures threshold ranges for these parameters, calculates feedback values ​​based on the parameters and threshold ranges, and maps the neurofeedback parameters to neurofeedback information based on the feedback values. The feedback information presentation module presents the neurofeedback information to the trainee in a visual form, allowing the trainee to adjust their neural activity in real time based on the presented information to enhance their balance perception ability. This invention also provides a balance perception enhancement method based on neurofeedback. The system and method proposed in this invention can effectively enhance the balance perception ability of trainees.

Description

Technical Field

[0001] This invention relates to the field of non-invasive neurointervention technology, and in particular to a balance perception enhancement system and method based on neural feedback. Background Technology

[0002] Balance dysfunction, caused by impaired coordination of the cerebellum, visual system, vestibular system, proprioception, or neuromuscular system, resulting in unsteadiness in standing and walking, is a common manifestation of frailty syndrome in the elderly and also a common functional impairment in patients with stroke, Parkinson's disease, and other illnesses. Research on balance rehabilitation is of great significance. Currently, mainstream balance rehabilitation techniques include: exercise therapy centered on general muscle strength training; physical therapy primarily using functional electrical stimulation, massage, and acupuncture; sensory compensation therapy combining virtual reality and biofeedback technology; and neuromodulation therapy primarily using transcranial electrical stimulation and transcranial magnetic stimulation. These techniques have the following shortcomings: (1) Exercise therapy and physical therapy focus on strengthening muscle strength and stretching relaxation, neglecting to train and enhance balance perception; (2) Sensory compensation therapy focuses on increasing the input information of balance-related senses to improve the ability to perceive human posture, but because it fails to improve the perception of balance information and the central integration ability, the training is difficult to produce long-term effects; (3) Neuroplasticity is the key mechanism for functional recovery after the damage of neural circuits, and real-time and accurate feedback is a necessary prerequisite, but neuromodulation therapy cannot provide real-time feedback on the brain activity state of the trainee, making it difficult to achieve timely and proactive training adjustments.

[0003] The process of maintaining balance in the human body involves three stages: balance perception, information processing in the central nervous system, and motor control. Specifically, when the body encounters an external balance disturbance, the visual, vestibular, and proprioceptive systems in the balance perception pathway transmit sensory input information to the brain. The central nervous system integrates and processes this information, comparing the integrated information with experiential templates to form a decision needed to cope with the current balance disturbance. The premotor cortex and motor cortex then sequentially formulate motor plans based on these decisions, issuing corresponding motor control commands to adjust the coordinated movement of bones and muscles, ultimately maintaining balance. The aforementioned balance rehabilitation techniques all neglect the enhancement training of balance perception.

[0004] Neurofeedback training technology provides a potentially effective new approach to enhance balance perception. This technology encompasses various forms, including EEG-based neurofeedback, near-infrared and magnetoencephalography-based neurofeedback, etc. Different types of neurofeedback technologies have their own characteristics and can monitor and regulate the neural activity of the brain from different angles. Among these technologies, EEG-based neurofeedback technology has unique advantages such as low cost, high temporal resolution, good portability and comfort. Balance disturbances can induce changes in brain neural activity. EEG-based neurofeedback training technology acquires EEG signals in real time and feeds back the EEG decoding results to the trainee in real time through visual / auditory means, helping them to autonomously regulate the corresponding neural activity, thereby promoting the functional remodeling of neurons in the balance perception pathway and further improving balance perception ability. Compared with the current mainstream balance rehabilitation technology, EEG neurofeedback technology has the following advantages: (1) It allows for personalized adjustments based on individual EEG activity patterns to form personalized training programs and improve the efficiency of rehabilitation treatment; (2) It helps to form lasting changes. By real-time regulation of EEG activity, it enhances the time-dependent effect, improves the brain's self-regulation ability and neural plasticity, and makes functional improvement lasting.

[0005] Nevertheless, the following problems still need to be solved in EEG neurofeedback technology: (1) Traditional EEG neurofeedback training systems usually use spontaneous EEG signals as feedback parameters. Spontaneous EEG signals have low noise-to-noise ratios, are easily interfered with by other cognitive processes, and have high variability among different individuals; (2) A few studies have tried to use single-trial ERP-induced EEG signals as feedback parameters, but single-trial ERP feature extraction is difficult, resulting in low accuracy of neurofeedback training systems.

[0006] Therefore, it is urgent to find reliable EEG neurofeedback parameters, establish a design paradigm for neurofeedback training, and construct a stable and reliable neurofeedback training system and method to enhance balance perception. Summary of the Invention

[0007] The purpose of this invention is to address the shortcomings of existing technologies, such as neglecting balance perception training, low spontaneous EEG signal-to-noise ratio, susceptibility to interference from other cognitive processes, and difficulty in extracting EEG features evoked by a single trial ERP. This invention proposes a balance perception enhancement system and method based on neurofeedback, which uses rhythmic evoked EEG to provide real-time feedback to trainees on their brain electrical activity during the balance perception process, thereby improving the reliability of the evoked EEG feedback parameters and effectively enhancing the trainees' balance perception ability.

[0008] To achieve the above objectives, the present invention adopts the following technical solution:

[0009] In a first aspect, the present invention provides a balance perception enhancement system based on neural feedback, comprising:

[0010] The balanced perturbation application module is used to generate rhythmic perturbation stimuli with alternating intensities to induce rhythmic EEG signals in trainees.

[0011] The data acquisition and processing module is used to acquire and preprocess the EEG signals of the trainees, and the EEG signals include at least the rhythmic EEG signals.

[0012] The neural feedback parameter calculation and mapping module receives preprocessed EEG signals, calculates neural feedback parameters, configures the threshold range of neural feedback parameters, calculates feedback values ​​based on neural feedback parameters and threshold ranges, and maps neural feedback parameters to neural feedback information based on feedback values.

[0013] And a feedback information presentation module, used to present neurofeedback information to trainees in a visual form;

[0014] Trainees adjust their neural activity in real time based on the presented neural feedback information to enhance their balance perception.

[0015] As one possible implementation, the neural feedback parameter calculation and mapping module includes:

[0016] The neural feedback parameter extraction unit is used to receive the preprocessed EEG signal and extract the EEG power spectral density at a specific frequency, which is the neural feedback parameter. The specific frequency is calculated based on the frequency of a single rhythmic perturbation stimulus and the number of perturbations at different stimulus intensities.

[0017] The threshold range calculation unit calculates the threshold range of the neural feedback parameters based on the trainee's balance perturbation deviation identification results, and calculates the feedback value based on the neural feedback parameters and the threshold range.

[0018] And a neural feedback parameter mapping unit, which maps neural feedback parameters into neural feedback information based on feedback values.

[0019] As one possible implementation, the threshold range of neural feedback parameters is calculated based on the balance perception assessment results of the trainees, specifically:

[0020] A preset deviation identification accuracy rate is set. When the evaluation result reaches the deviation identification accuracy rate, the baseline perturbation angle pair of the balance perturbation applied to the trainee and the peak perturbation angle pair of the balance perturbation applied to the trainee when the trainee's identification accuracy rate is the highest are recorded. Both the baseline perturbation angle pair and the peak perturbation angle pair include the standard stimulus angle and the deviation stimulus angle. The baseline threshold is the EEG power spectral density at a specific frequency when the standard stimulus angle perturbation in the baseline perturbation angle pair is applied to the trainee. The peak threshold is the EEG power spectral density at a specific frequency when the standard stimulus angle perturbation and the deviation stimulus angle perturbation in the peak perturbation angle pair are applied to the trainee alternately. The baseline threshold and the peak threshold constitute the threshold range of the neural feedback parameters.

[0021] As one possible implementation, the feedback value is calculated based on the neural feedback parameters and threshold range in the following way:

[0022] When the neural feedback parameter is greater than the peak threshold, the feedback value is 1; when the neural feedback parameter is less than the baseline threshold, the feedback value is 0; when the neural feedback parameter is greater than or equal to the baseline threshold and less than or equal to the peak threshold, the feedback value is calculated using a linear interpolation method.

[0023] In a second aspect, the present invention provides a balance perception enhancement method based on neural feedback, which applies the balance perception enhancement system based on neural feedback provided in the first aspect. The balance perception enhancement method involves conducting multiple rounds of balance perception training on the trainee. Each round of balance perception training includes at least a pre-test balance perception assessment experiment and neural feedback training. The pre-test balance perception assessment experiment is used to determine the perturbation tilt angle pair of the rhythmic perturbation stimulus required for neural feedback training.

[0024] Neurofeedback training includes:

[0025] S1. After the trainee has been in a resting state for a preset time, apply alternating stimuli of the angles included in the perturbation tilt angle pair; collect and preprocess the EEG signals of the trainee in the resting state and during the application of stimulation.

[0026] S2. Extract rhythmic features from the preprocessed EEG data, calculate the EEG power spectral density at a specific frequency, and obtain neural feedback parameters; the neural feedback parameters are the difference between the EEG power spectral density during the perturbation stimulus and the resting-state EEG power spectral density.

[0027] S3. Calculate the threshold range of the neural feedback parameters, and calculate the feedback value based on the neural feedback parameters and the threshold range;

[0028] S4. Based on the feedback value, the neural feedback parameters are mapped to neural feedback information, and the neural feedback information is presented to the trainee in a visual form. The trainee adjusts his own neural activity in real time based on the presented neural feedback information to enhance his balance perception ability.

[0029] As one possible implementation, balance-aware enhancement methods also include:

[0030] S5. Configure a post-test balance perception assessment experiment to obtain the change in the accuracy of balance perturbation deviation identification when the trainee receives the same perturbation stimulus as in the pre-test balance perception assessment experiment, so as to verify the results of this round of balance perception training.

[0031] As one possible approach, the pre-test balance perception assessment experiment uses a rhythmic stimulus plus an oddball paradigm, with n perturbation sequences of the same angle as the standard stimulus and n-1 perturbation sequences of the same angle plus 1 perturbation sequence of a different angle as the bias stimulus.

[0032] As one possible implementation, the threshold range for calculating neural feedback parameters includes:

[0033] S30. Preset the deviation identification accuracy rate, obtain the baseline perturbation angle pair of the balance perturbation applied to the trainee when the deviation identification accuracy rate is reached, and the peak perturbation angle pair of the balance perturbation applied to the trainee when the identification accuracy rate is the highest.

[0034] S31. Obtain the EEG power spectral density at a specific frequency when the standard stimulus angle perturbation in the baseline perturbation angle pair is applied to the trainee, which is the baseline threshold; and obtain the EEG power spectral density at a specific frequency when the standard stimulus angle perturbation and the deviated stimulus angle perturbation in the peak perturbation angle pair are applied alternately to the trainee, which is the peak threshold.

[0035] S32. The threshold range for obtaining neural feedback parameters is greater than or equal to the baseline threshold and less than or equal to the peak threshold.

[0036] As one possible implementation, the feedback value is calculated based on the neural feedback parameters and threshold range. Specifically: when the neural feedback parameter is greater than the peak threshold, the feedback value is 1; when the neural feedback parameter is less than the baseline threshold, the feedback value is 0; when the neural feedback parameter is greater than or equal to the baseline threshold and less than or equal to the peak threshold, the feedback value is calculated using the following linear interpolation method:

[0037] Feedback = (C X —C B ) / (C T —C B ), C B ≤C X ≤C T ;

[0038] Where Feedback represents the feedback value, C X C represents the neural feedback parameter. B C represents the baseline threshold. T This indicates the peak threshold.

[0039] As one possible implementation, the neural feedback information is represented by a ring, and the radius of the ring is determined as follows:

[0040] R X =R pre ―k×F eedback ;

[0041] Where Feedback represents the feedback value, R X R is the radius of the annulus at the current moment. pre Let be the radius of the annulus at the previous moment, and k be a constant.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0043] 1. The balance perception enhancement system and method proposed in this invention innovatively improves the balance perception sensitivity of trainees by addressing the functional remodeling of the balance perception pathway. By acquiring brain neural signals and providing real-time feedback of EEG decoding results to trainees through visual means, it helps trainees to autonomously regulate corresponding neural activities in real time, thereby promoting the functional remodeling of neurons in the balance perception pathway and further enhancing balance perception ability.

[0044] 2. The balance perception enhancement system and method based on neural feedback proposed in this invention utilizes the proposed rhythmic balance perturbation stimulation paradigm to extract rhythmic neural entrainment induced by exogenous stimulation as feedback parameters. Compared with existing technologies, this invention solves the problems of high spontaneous EEG signal-to-noise ratio, large cross-individual variability, and difficulty in extracting EEG features induced by a single trial ERP, thereby improving the reliability of neural feedback parameters.

[0045] 3. The balance perception enhancement system and method based on neurofeedback proposed in this invention uses rhythmic stimulation with alternating intensity. Compared with existing technologies, it can effectively induce the trainee to generate balance homeostasis induced by the intensity change cycle, improve the trainee's ability to distinguish differences in balance disturbances, and enhance the transferability of training effects.

[0046] 4. The balance perception enhancement system and method proposed in this invention, based on neurofeedback, allows for personalized adjustments according to individual brainwave activity patterns, forming a personalized training program, thereby improving the efficiency of balance perception enhancement. Furthermore, neurofeedback training technology enhances the brain's self-regulation ability and neural plasticity, enabling functional improvements to be maintained persistently and contributing to long-term, stable enhancement effects. Attached Figure Description

[0047] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0048] Figure 1 This is a schematic diagram of the balance perception enhancement system based on neural feedback in an embodiment of the present invention;

[0049] Figure 2This is a schematic diagram of a complete balance perception training scheme in an embodiment of the present invention;

[0050] Figure 3 This is a flowchart of the balance perception enhancement method based on neural feedback in an embodiment of the present invention;

[0051] Figure 4 This is a schematic diagram illustrating the presentation of neurofeedback information to the trainee in a visual form in an embodiment of the present invention;

[0052] Figure 5 This is a schematic diagram of the overall scheme for conducting experiments using this method in an embodiment of the present invention;

[0053] Figure 6 This is a flowchart of the balance perception behavioral measurement process in an embodiment of the present invention;

[0054] Figure 7 This is a flowchart of the balance perception training process proposed in the embodiments of the present invention.

[0055] Figure Labels

[0056] 1-Balance perturbation application module, 2-Data acquisition and processing module, 3-Neural feedback parameter calculation and mapping module, 30-Neural feedback parameter extraction unit, 31-Threshold range calculation unit, 32-Neural feedback parameter mapping unit, 4-Feedback information presentation module. Detailed Implementation

[0057] To facilitate a clear description of the technical solutions in the embodiments of the present invention, the terms "first" and "second" are used to distinguish identical or similar items with essentially the same function and effect. For example, the first threshold and the second threshold are merely used to distinguish different thresholds and do not limit their order. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that the terms "first" and "second" are not necessarily different.

[0058] It should be noted that in this invention, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in this invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0059] In this invention, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one" or similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, "at least one of a, b, or c" can represent: a, b, c, a combination of a and b, a combination of a and c, a combination of b and c, or a, b, and c, where a, b, and c can be single or multiple.

[0060] This invention aims to provide a balance perception enhancement system and method based on neurofeedback, which can solve the problems of neglecting balance perception ability training, low spontaneous EEG signal-to-noise ratio, susceptibility to interference from other cognitive processes, and difficulty in extracting EEG features evoked by a single trial ERP. This invention uses rhythmic evoked EEG to provide real-time feedback to the trainee on their EEG activity during the balance perception process, improves the reliability of evoked EEG feedback parameters, and effectively enhances the trainee's balance perception ability.

[0061] In a first aspect, embodiments of the present invention provide a balance perception enhancement system based on neural feedback, see [link to previous document]. Figure 1 It includes: a balance perturbation application module 1, a data acquisition and processing module 2, a neural feedback parameter calculation and mapping module 3, and a feedback information presentation module 4;

[0062] Among them, the balance perturbation application module 1 is used to generate rhythmic perturbation stimuli with alternating intensity to induce rhythmic EEG signals in the trainees;

[0063] As an example, the rhythmic perturbation stimulus uses several alternating variations of different intensities. For instance, it uses the following two different alternating intensities: Intensity 1 (tilt angle) The perturbation stimulus presents m

[0064] Second, intensity 2 (tilt angle) The perturbation stimulus is presented m times, then switched back to intensity 1, and this process is repeated multiple times. This setting guides trainees to autonomously adjust their psychological strategies to regulate neural feedback parameters, thereby improving their ability to identify differences in balance perturbations.

[0065] By employing rhythmic balance perturbation stimulation to induce rhythmic EEG in trainees, we can solve problems such as high signal-to-noise ratio of spontaneous EEG feedback parameters, large cross-individual variability, and difficulty in extracting EEG features induced by a single trial of ERP.

[0066] The data acquisition and processing module 2 is used to acquire and preprocess the trainee's EEG signals; the EEG signals include at least rhythmic EEG signals.

[0067] As one possible implementation, the data acquisition and processing module 2 includes an amplifier and a processing host. The amplifier is used to amplify the acquired EEG signals of the trainees, and the processing host performs preprocessing on the amplified EEG signals, such as filtering, rereference, downsampling, and artifact removal.

[0068] The neural feedback parameter calculation and mapping module 3 receives the preprocessed EEG signal, calculates the neural feedback parameters, configures the threshold range of the neural feedback parameters, calculates the feedback value based on the neural feedback parameters and the threshold range, and maps the neural feedback parameters into neural feedback information based on the feedback value.

[0069] See Figure 1 As one possible implementation, the neural feedback parameter calculation and mapping module 3 includes: a neural feedback parameter extraction unit 30, a threshold range calculation unit 31, and a neural feedback parameter mapping unit 32;

[0070] The neural feedback parameter extraction unit 30 is used to receive the preprocessed EEG signal and extract the EEG power spectral density of a specific frequency, which is the neural feedback parameter; the specific frequency is calculated based on the frequency of a single rhythmic perturbation stimulus and the number of perturbations of different stimulus intensities.

[0071] As an example, assuming the frequency of a single rhythmic perturbation stimulus applied to the trainee is f, and two different intensities are alternated, with m perturbations for both intensities, the specific frequency f′ is calculated as follows:

[0072]

[0073] For example, the power spectral density of an EEG signal can be calculated using the Welch method, Bartlett method, Blackman-Tukey method, and the multitaper method. The power spectral density C of the EEG signal at frequency f′ is given by... (f′) This refers to the neural feedback parameters.

[0074] The threshold range calculation unit 31 calculates the threshold range of the neural feedback parameters based on the trainee's balance perturbation deviation identification results, and calculates the feedback value based on the neural feedback parameters and the threshold range.

[0075] As one possible implementation, the threshold range of neural feedback parameters is calculated based on the balance perception assessment results of the trainees, specifically:

[0076] A preset deviation identification accuracy rate is set. When the evaluation result reaches the deviation identification accuracy rate, the baseline perturbation angle pair of the balance perturbation applied to the trainee and the peak perturbation angle pair of the balance perturbation applied to the trainee when the trainee's identification accuracy rate is the highest are recorded. Both the baseline perturbation angle pair and the peak perturbation angle pair include the standard stimulus angle and the deviation stimulus angle. The baseline threshold is the EEG power spectral density at a specific frequency when the standard stimulus angle perturbation in the baseline perturbation angle pair is applied to the trainee. The peak threshold is the EEG power spectral density at a specific frequency when the standard stimulus angle perturbation and the deviation stimulus angle perturbation in the peak perturbation angle pair are applied to the trainee alternately. The baseline threshold and the peak threshold constitute the threshold range of the neural feedback parameters.

[0077] As an example, the preset deviation identification accuracy range is generally between 75% and 85%. Assuming a preset deviation identification accuracy of 80%, when the trainee's assessment results reach a deviation identification accuracy of 80%, the baseline perturbation angle pair of the balance perturbation applied to the trainee is denoted as... And the peak perturbation angle of the balance perturbation applied to the trainee when the trainee's recognition accuracy is highest, denoted as Both the baseline perturbation angle pair and the peak perturbation angle pair include a standard stimulus angle and a deviated stimulus angle. For example, the standard stimulus angle is defined as all n perturbation angles being standard stimulus angles, and the deviated stimulus angle is defined as the first n-1 perturbation angles being standard stimulus angles, with the nth perturbation angle being a deviated stimulus angle. The baseline threshold is the EEG power spectral density at a specific frequency when the standard stimulus angle perturbation in the baseline perturbation angle pair is applied to the trainee. For example, when the trainee is subjected to... The power spectral density of brainwaves at a specific frequency during angular perturbation, i.e. Or, apply pressure to the trainees The power spectral density of brainwaves at a specific frequency during angular perturbation, i.e. The peak threshold is the EEG power spectral density at a specific frequency when the trainee is alternately subjected to standard stimulus angle perturbations and deviated stimulus angle perturbations within a peak perturbation angle pair. and The perturbation was used to extract the EEG power spectral density of the trainee at a specific frequency, i.e. The baseline threshold and the peak threshold constitute the threshold range of the neural feedback parameters; that is, the threshold range of the neural feedback parameters is greater than or equal to the baseline threshold and less than or equal to the peak threshold. The calculation method for a specific frequency has been described above and will not be repeated here.

[0078] As one possible implementation, the feedback value is calculated based on the neural feedback parameters and threshold range in the following way:

[0079] When the neural feedback parameter is greater than the peak threshold, the feedback value is 1; when the neural feedback parameter is less than the baseline threshold, the feedback value is 0; when the neural feedback parameter is greater than or equal to the baseline threshold and less than or equal to the peak threshold, the feedback value is calculated using a linear interpolation method.

[0080] As an example, the feedback value is calculated as follows:

[0081]

[0082] Among them, C X C represents the neural feedback parameter. B C represents the baseline threshold. T This represents the peak threshold, and Feedback represents the feedback value.

[0083] The neurofeedback parameter mapping unit 32 maps neurofeedback parameters into neurofeedback information based on feedback values. The feedback information presentation module 4 is used to present the neurofeedback information to the trainee in a visual form; the trainee adjusts their neural activity in real time based on the presented neurofeedback information to enhance their balance perception ability.

[0084] As an example, neural feedback information can be in the form of a circular ring, a square ring, a flame, etc., without any specific limitation. Any presentation method will not affect the implementation of the technical solution of this invention.

[0085] Secondly, embodiments of the present invention provide a balance perception enhancement method based on neurofeedback, applying the balance perception enhancement system based on neurofeedback provided in the first aspect. The balance perception enhancement method involves conducting multiple rounds of balance perception training on the trainee, see [link to previous section]. Figure 2 Each round of balance perception training includes at least a pre-test balance perception assessment experiment and neurofeedback training.

[0086] The pre-test balance perception assessment experiment is used to determine the perturbation tilt angle pairs of rhythmic perturbation stimuli required for neurofeedback training. In the pre-test balance perception assessment experiment, trainees are asked to perform a balance perturbation deviation identification task. For example, the pre-test balance perception assessment experiment uses a rhythmic stimulus plus oddball paradigm, with n consecutive perturbation sequences at the same angle as the standard stimulus, and n-1 consecutive perturbation sequences at the same angle plus 1 perturbation sequence at a different angle as the deviation stimulus. It is assumed that the determined perturbation tilt angle pairs of rhythmic perturbation stimuli required for neurofeedback training are...

[0087] See Figures 2 to 3 Neurofeedback training includes the following steps:

[0088] S1. After the trainee has been in a resting state for a preset time, apply alternating stimuli of the angles included in the perturbation tilt angle pair; collect and preprocess the EEG signals of the trainee in the resting state and during the application of stimulation.

[0089] As an example, in each round of neurofeedback training, the trainee is initially in a resting state. After a period of time, a balance board is used to apply two rhythmic perturbation stimuli of alternating intensities to the trainee. The perturbation angle of the intensity 1 rhythmic stimulus is the angle of the perturbation tilt. The perturbation angle of a 2-intensity rhythmic stimulus is the center of the perturbation tilt angle. Specifically, the balance plate is at an angle Tilt and return to position, repeat m times; then switch to angle-based tilting. Tilt and return to position, repeat m times; then switch to angle again. This process is repeated multiple times. The frequency at which the balance plate tilts and returns to its original position is fHz.

[0090] S2. Extract rhythmic features from the preprocessed EEG signal and calculate the EEG power spectral density at a specific frequency, which is the neural feedback parameter;

[0091] As an example, a multi-channel electrode cap is used to acquire and amplify the EEG signals of trainees in real time. The amplified signals are then preprocessed sequentially through filtering, rereference, downsampling, and artifact removal before being used for rhythm feature extraction. Exemplarily, the Welch method, Bartlett method, Blackman-Tukey method, and the multitaper method are used to calculate the power spectral density of the EEG signals, and the power spectral density C at a specific frequency f′ is calculated. (f′) , which refers to the neural feedback parameters. The specific frequency f′ is calculated based on the frequency f of a single rhythmic perturbation stimulus applied to the trainee, with the stimulus intensity change period being m, as detailed below:

[0092]

[0093] The neural feedback parameter is the difference between the EEG power spectral density during the perturbation stimulus and the resting-state EEG power spectral density, i.e.:

[0094] C (f′) =PSD test (f′)―PSDbase(f′)

[0095] Among them, PSD test (f′) represents the power spectral density of the electroencephalogram (EEG) during the perturbation stimulus, PSD. base (f′) represents the resting-state EEG power spectral density.

[0096] The balance perception enhancement method provided in this embodiment utilizes the proposed rhythmic balance perturbation stimulation paradigm to extract rhythmic neural entrainment induced by exogenous stimuli as feedback parameters. Compared with existing technologies, it solves the problems of high spontaneous EEG signal-to-noise ratio, large cross-individual variability, and difficulty in extracting EEG features induced by a single trial ERP, thereby improving the reliability of neural feedback parameters.

[0097] S3. Calculate the threshold range of the neural feedback parameters, and calculate the feedback value based on the neural feedback parameters and the threshold range;

[0098] As one possible implementation, the threshold range for calculating neural feedback parameters includes:

[0099] S30. Preset the deviation identification accuracy rate, obtain the baseline perturbation angle pair of the balance perturbation applied to the trainee when the balance perception assessment test results reach the deviation identification accuracy rate, and the peak perturbation angle pair of the balance perturbation applied to the trainee when the identification accuracy rate is the highest.

[0100] As an example, the preset deviation identification accuracy range is generally between 75% and 85%. Assuming a preset deviation identification accuracy of 80%, when the trainee's assessment results reach a deviation identification accuracy of 80%, the baseline perturbation angle pair of the balance perturbation applied to the trainee is denoted as... And the peak perturbation angle of the balance perturbation applied to the trainee when the trainee's recognition accuracy is highest, denoted as Both the baseline perturbation angle pair and the peak perturbation angle pair include a standard stimulus angle and a deviated stimulus angle. For example, the standard stimulus angle is that all n perturbation angles are standard stimulus angles, and the deviated stimulus angle is that the first n-1 perturbation angles are standard stimulus angles, and the nth perturbation angle is a deviated stimulus angle.

[0101] S31. Obtain the EEG power spectral density at a specific frequency when the standard stimulus angle perturbation in the baseline perturbation angle pair is applied to the trainee, which is the baseline threshold; and obtain the EEG power spectral density at a specific frequency when the standard stimulus angle perturbation and the deviated stimulus angle perturbation in the peak perturbation angle pair are applied alternately to the trainee, which is the peak threshold.

[0102] The baseline threshold is the EEG power spectral density at a specific frequency when a standard stimulus angle perturbation in the baseline perturbation angle pair is applied to the trainee. For example, when a trainee is subjected to... The power spectral density of brainwaves at a specific frequency during angular perturbation, i.e. Or, apply pressure to the trainees The power spectral density of brainwaves at a specific frequency during angular perturbation, i.e. The peak threshold is the EEG power spectral density at a specific frequency when the trainee is alternately subjected to standard stimulus angle perturbations and deviated stimulus angle perturbations within a peak perturbation angle pair. and The perturbation was used to extract the EEG power spectral density of the trainee at a specific frequency, i.e.

[0103] S32. The threshold range for obtaining neural feedback parameters is greater than or equal to the baseline threshold and less than or equal to the peak threshold, i.e.: C B ≤C X ≤C T .

[0104] As one possible implementation, the feedback value is calculated based on the neural feedback parameters and threshold range. Specifically: when the neural feedback parameter is greater than the peak threshold, the feedback value is 1; when the neural feedback parameter is less than the baseline threshold, the feedback value is 0; when the neural feedback parameter is greater than or equal to the baseline threshold and less than or equal to the peak threshold, the feedback value is calculated using the following linear interpolation method:

[0105] Feedback = (C X —C B ) / (C T —C B ), C B ≤C X ≤C T ;

[0106] Where Feedback represents the feedback value, C X C represents the feedback parameter. B C represents the baseline threshold. T This indicates the peak threshold.

[0107] S4. Based on the feedback value, the neural feedback parameters are mapped to neural feedback information, and the neural feedback information is presented to the trainee in a visual form. The trainee adjusts his own neural activity in real time based on the presented neural feedback information to enhance his balance perception ability.

[0108] As one possible implementation, the neural feedback information is represented by a ring, and the radius of the ring is determined as follows:

[0109] R X =R pre ―k×Feedback;

[0110] Where Feedback represents the feedback value, R X R is the radius of the annulus at the current moment. pre Let be the radius of the annulus at the previous moment, and k be a constant.

[0111] For example, the initial radius of the ring is given in advance, and the radius of the ring is dynamically adjusted based on the changes in the feedback parameters during training.

[0112] In summary, the specific mapping rules for neural feedback parameters are as follows: if the current time feedback parameter is less than the baseline threshold C... B (i.e., the feedback value is 0), then the radius of the ring remains unchanged; if the current time feedback parameter is greater than the peak threshold C T (i.e., the feedback value is 1), then the radius of the ring shrinks to R. pre ―k; If the current time feedback parameter is within two threshold intervals, the radius of the ring shrinks to R. pre ―k×(C X —C B / C T —C B The neural characteristics are dynamic and updated every 500ms, so the radius of the ring also changes dynamically.

[0113] See Figure 4 As an example, a circular image is generated based on a dynamically adjusted circular radius and presented to the trainee. The change in the circular radius reflects the dynamic characteristics of the trainee's neural activity, helping the trainee to intuitively perceive and adjust their own neural activity state. During stimulation, the trainee is required to actively regulate neural activity using psychological strategies to reduce the radius of the circular ring, following the principle of "making the ring as small as possible."

[0114] Each round of balance perception training includes neural feedback training across multiple blocks. At the start of each neural feedback training trial, the initial radius of the ring inherits the final radius from the previous trial. This process is repeated q times to complete one block of balance perception training.

[0115] In practical applications, a training group and a control group are set up. The training group undergoes neurofeedback training using the above process, while the control group receives the same perturbation scheme during training as the training group. The difference is that the subjects in the control group are asked to look at the radius of the ring but do not attempt to control it.

[0116] It should be explained that the presentation of neural feedback information is not necessarily in the form of a circle; it can also be in other shapes or patterns, such as a square ring or a flame shape. Regardless of the presentation method, it does not affect the essence of the present invention.

[0117] As one possible implementation, balance-aware enhancement methods also include:

[0118] S6. Configure a post-test balance perception assessment experiment to obtain the change in the accuracy of balance perturbation deviation identification when the trainee receives the same perturbation stimulus as in the pre-test balance perception assessment experiment, so as to verify the results of this round of balance perception training.

[0119] The following experiments were conducted using the balance perception enhancement system and method proposed in the embodiments of this invention. See [link to relevant documentation]. Figure 5 This is a complete training process, comprising six parts: balance dysfunction assessment scale data recording (pre-test), balance perception behavioral assessment (pre-test), neurofeedback training based on evoked EEG characteristics, balance perception behavioral assessment (post-test), balance dysfunction assessment scale data recording (post-test), and neurofeedback training effect evaluation. These are detailed below:

[0120] Part 1: Recruiting stroke patients for training. Inclusion criteria included an age range of 40-60 years, with gender balance among participants. Further data collection using the Berg Balance Scale was conducted. The experimenter guided participants to complete each item on the scale and calculated their scores. The degree of balance impairment was determined based on the scores; lower scores indicated more severe impairment. Participants scoring below 20 points were excluded. The selected patients were randomly assigned to a training group and a control group.

[0121] Part Two: First, behavioral methods were used to assess the balance perception levels of patients in the training and control groups. This embodiment used the oddball balance perturbation task as the behavioral method (standard stimulus: deviation stimulus = 1:4). Patients were asked to stand on a balance board, and balance perturbations were applied by tilting the board at different intensities. The subjective perception of deviation or standard was recorded, and the detection rate of subjective perception under different intensities of perturbation stimulation was recorded as the patient's balance perception level.

[0122] Before the formal task, patients need to perform a familiarization task, receiving balance board stimulation at different angles in sequence. To improve the generalization performance of the model, this embodiment sets up three different intensities of standard stimulation: weak, medium, and strong. Based on the tilt angle of the standard stimulation, with a deviation range of ±20% to 25%, four deviation stimulation tilt angles are set for each standard stimulation condition, as shown in Table 1:

[0123] Table 1. Parameters of the disturbance angle of the balance plate

[0124]

[0125] Formal task flow as follows Figure 6 As shown:

[0126] (1) For each trial, a 1-second sound prompt appears first, followed by a 200-second "beep" sound, and an 800-second interval.

[0127] (2) After the prompting, the balance board generates a rhythmic orientation perturbation stimulation sequence, that is, it tilts and returns to its original position 5 times at a fixed frequency of 1 Hz to induce rhythmic EEG in the patient. The tilt angle of the last tilt can be different from the previous 4 times (deviation stimulation) or the same as the previous 4 times (standard stimulation);

[0128] (3) After the last stimulus, the patient enters a 2-second rest period and reports whether they felt the deviation stimulus and their confidence in the response;

[0129] (4) Repeat steps (1) to (3) 20 times to form one block (one trial block). The number of trials for the biased stimulus and the standard stimulus are 8 and 12, respectively, and the order is random.

[0130] Each level has 4 blocks, and there are 12 blocks in total across 3 levels. The total time is approximately 24 minutes.

[0131] Part Three: The entire neurofeedback training plan is as follows Figure 7 As shown, both the training group (neuroferritory group) and the control group received feedback training for 8 consecutive days. The specific training plan for the training group was as follows:

[0132] (1) After entering the training period, a balance perception pretest is conducted every day. In the balance perception pretest block, in each trial, the patient receives the same stimulus task as the balance perception behavioral assessment paradigm, repeated 20 times, to obtain their balance perception threshold, that is, the balance perturbation difference angle pair corresponding to the 85% detection rate level (e.g., standard stimulus angle = 5°, deviation stimulus angle = 5.5°), and the angle pair corresponding to the maximum perception level (e.g., standard stimulus angle = 5°, deviation stimulus angle = 4°);

[0133] (2) Upon entering the feedback training block, each trial begins with an audio cue. After the cue disappears, the balance board undergoes two alternating rhythmic directional perturbation stimuli of varying intensities. The perturbation angle for intensity 1 is 5°, and for intensity 2 it is 5.5°. Specifically, the balance board tilts at a 5° angle and returns to its original position, repeated 4 times; then it switches to tilting at a 5.5° angle and returns to its original position, repeated 4 times; then it switches back to a 5° angle, repeating this process 5 times. The frequency of the balance board tilting and returning to its original position is f = 1 Hz. After completing the above task, the trainee rests for 2 seconds. After the rest period, the current trial ends, and the next trial begins.

[0134] (3) After the perturbation stimulus is presented, the system acquires the trainee's EEG signal in real time through a multi-channel electrode cap and amplifies and saves it. The signal is then transmitted to the feedback parameter extraction module after passing through filtering, rereference, downsampling, and artifact removal preprocessing.

[0135] (4) Extract target rhythm features from the preprocessed EEG data, calculate the relative power as a feedback parameter, and calculate the feedback value based on the feedback parameter threshold. Finally, map the feedback value to a quantized value that can be used for subsequent feedback, as follows:

[0136] ① Extract specific rhythmic neural activity characteristics of the brain. The power spectral density of the EEG signal was calculated using the Welch method, and the power spectral density C of the EEG corresponding to the rhythm f′=1 / 8Hz of the periodic change in the intensity of the perturbation stimulus in the motor area of ​​the brain was extracted. (f′) As a feedback parameter, the formula for calculating the target EEG power spectrum for each trainee in each channel is as follows: C (f′＝1 / 8) =PSC test (f′=1 / 8)―PSD base (f′=1 / 8)

[0137] Among them, PSD test (f′=1 / 8) is the power spectral density during the perturbation stimulation period, PSD base (f′=1 / 8) is the resting power spectral density during the pre-cue period of the perturbation stimulus.

[0138] ② Calculate the minimum and maximum thresholds of the neurofeedback parameters. Trainees receive the same stimulus task as in feedback training, but with different intensity parameters. Specifically: Intensity 1 and Intensity 2 are set to be the same, i.e., the tilt angle is 5°, the standard stimulus angle in the balance perception threshold. The EEG power spectral density of the trainee's motor cortex at f′ = 1 / 8 Hz is extracted as the baseline threshold C. B The perturbation angles of intensity 1 and intensity 2 were set to correspond to the maximum perceptual level as angle pairs (5°, 4°), and the EEG power spectral density of the trainee's motor area at f′ = 1 / 8 Hz was extracted as the peak threshold C. T ;

[0139] ③ Calculate the feedback value (Feedback) based on the neural feedback parameters and the feedback parameter threshold. Determine the current feedback parameter C. (f′＝1 / 8) The difference from the threshold, if C (f′＝1 / 8) Greater than the peak threshold C T If C, then the feedback value is 1; (f′＝1 / 8) Less than the baseline threshold C T If C, then the feedback value is 0; (f′＝1 / 8) If the value falls between the baseline threshold and the peak threshold, the feedback value is calculated using linear interpolation:

[0140]

[0141] Among them, C X C represents the neural feedback parameter. B C represents the baseline threshold. T This represents the peak threshold, and feedback represents the feedback value.

[0142] ④ Map the feedback parameters to neural feedback signals based on the feedback values. The radius of the neural feedback signal is dynamically adjusted based on the signal changes between the subject's current and previous time points. The calculation method is as follows:

[0143] R X =R pre ―k×feedback

[0144] Among them, R X R is the radius of the current time annulus. pre Let be the radius of the annulus at the previous time step, and k be a constant.

[0145] If the current time feedback parameter C (f′＝1 / 8) Less than the baseline threshold C B (i.e., the feedback value is 0), then the radius of the ring remains unchanged; if the current time feedback parameter C (f′＝1 / 8) Greater than the peak threshold C T (i.e., the feedback value is 1), then the radius of the ring shrinks to R. pre ―k; If the current time feedback parameter C (f′＝1 / 8) At both threshold intervals, the radius of the annulus shrinks to R. pre ―k×(C X —C B / C T —C B The neural characteristics are dynamic and updated every 500ms, so the radius of the ring also changes dynamically.

[0146] (5) The feedback information presentation module is responsible for presenting the mapped neural feedback signals to the trainee in a visual form. Specifically, the module presents the signals to the trainee based on the dynamically adjusted radius R of the annulus. X Generate a circular image and display it on a screen in real time;

[0147] (6) During the stimulation period, trainees are required to use psychological strategies to actively regulate their neural activity, reduce the radius of the ring, and follow the principle of "making the ring as small as possible";

[0148] (7) At the start of each trial, the initial radius of the ring inherits the final radius at the end of the previous trial. Repeat 10 trials to complete 1 feedback training block; repeat steps (2)-(6) 8 times to complete 8 blocks of feedback training. The control group received the same perturbation scheme as the training group during training; subjects were asked to visually observe the radius of the ring but not attempt to control it. After the feedback training block of the day was completed, repeat step (1) for another balance perception post-test. Training is considered complete after 8 training days.

[0149] Parts Four and Five: One week after neurofeedback training, trainees are required to perform balance perception behavioral measurements to assess the maintenance effect of balance perception ability after training. Trainers guide patients to perform the tasks on the Balance Dysfunction Assessment Scale again and record the scores to obtain an assessment of the degree of balance dysfunction in stroke patients.

[0150] Part VI: By comparing the results of the first balance perception assessment with the post-balance perception assessment on the last day of training, behavioral and EEG results were obtained before and after the entire training cycle. The effects of the training group and the control group were compared to determine the effectiveness of neurofeedback training. Furthermore, the maintenance effect of neurofeedback training was evaluated by comparing the results of the first balance perception assessment with those one week after the end of training.

[0151] The method proposed in this application allows for personalized adjustments based on individual brainwave activity patterns, creating a customized training program that improves the efficiency of balance perception enhancement. Furthermore, neurofeedback training technology enhances the brain's self-regulation and neuroplasticity, enabling functional improvements to be sustained and contributing to long-term, stable enhancement effects.

[0152] Although the invention has been described herein in conjunction with various embodiments, those skilled in the art will understand and implement other variations of the disclosed embodiments by reviewing the accompanying drawings, the disclosure, and the description of the drawings, in carrying out the claimed invention. In this specification, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude multiple components. A single processor or other unit can implement several of the functions listed in the specification. While certain measures are described in different embodiments, this does not mean that these measures cannot be combined to produce good results.

[0153] Although the invention has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made therein without departing from the spirit and scope of the invention. Accordingly, this specification and drawings are merely illustrative of the invention and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the invention. Clearly, those skilled in the art can make various alterations and modifications to the invention without departing from its spirit and scope. Thus, if such modifications and modifications fall within the scope of the invention and its equivalents, the invention is also intended to include such modifications and modifications.

Claims

1. A balance perception enhancement system based on neural feedback, characterized in that, include: The balanced perturbation application module is used to generate rhythmic perturbation stimuli with alternating intensities to induce rhythmic EEG signals in trainees. The data acquisition and processing module is used to acquire and preprocess the electroencephalogram (EEG) signals of the trainees, wherein the EEG signals include at least the rhythmic EEG signals. The neurofeedback parameter calculation and mapping module receives preprocessed EEG signals, calculates neurofeedback parameters, configures the threshold range of the neurofeedback parameters, calculates feedback values ​​based on the neurofeedback parameters and threshold range, and maps the neurofeedback parameters to neurofeedback information based on the feedback values. The threshold range of the neurofeedback parameters is specifically calculated as follows: a preset deviation identification accuracy rate is set; the baseline perturbation angle pair applied to the trainee when the evaluation result reaches the deviation identification accuracy rate, and the peak perturbation angle pair applied to the trainee when the trainee's identification accuracy rate is highest, are recorded. Both the baseline perturbation angle pair and the peak perturbation angle pair include a standard stimulus angle and a deviation stimulus angle. The baseline threshold is the EEG power spectral density at a specific frequency when the standard stimulus angle perturbation in the baseline perturbation angle pair is applied to the trainee; the peak threshold is the EEG power spectral density at a specific frequency when the standard stimulus angle perturbation and the deviation stimulus angle perturbation in the peak perturbation angle pair are applied alternately to the trainee. The baseline threshold and the peak threshold constitute the threshold range of the neurofeedback parameters. And a feedback information presentation module, used to present the neurofeedback information to the trainee in a visual form; Trainees adjust their neural activity in real time based on the presented neural feedback information to enhance their balance perception.

2. The balance perception enhancement system based on neurofeedback according to claim 1, characterized in that, The neural feedback parameter calculation and mapping module includes: The neural feedback parameter extraction unit is used to receive the preprocessed EEG signal and extract the EEG power spectral density at a specific frequency, which is the neural feedback parameter; the specific frequency is calculated based on the frequency of a single rhythmic perturbation stimulus and the number of perturbations at different stimulus intensities. The threshold range calculation unit calculates the threshold range of the neural feedback parameters based on the trainee's balance perturbation deviation identification results, and calculates the feedback value based on the neural feedback parameters and the threshold range. And a neural feedback parameter mapping unit, which maps neural feedback parameters into neural feedback information based on the feedback value.

3. The balance perception enhancement system based on neurofeedback according to claim 2, characterized in that, The feedback value is calculated based on the neural feedback parameters and threshold range in the following manner: When the neural feedback parameter is greater than the peak threshold, the feedback value is 1; when the neural feedback parameter is less than the baseline threshold, the feedback value is 0; when the neural feedback parameter is greater than or equal to the baseline threshold and less than or equal to the peak threshold, the feedback value is calculated using a linear interpolation method.

4. A method for enhancing balance perception based on neural feedback, characterized in that, The balance perception enhancement system based on neurofeedback according to any one of claims 1 to 3 is described in the method of performing multiple rounds of balance perception training on the trainee. Each round of balance perception training includes at least a pre-test balance perception assessment experiment and neurofeedback training. The pre-test balance perception assessment experiment is used to determine the perturbation tilt angle pair of the rhythmic perturbation stimulus required for neurofeedback training. The neurofeedback training includes the following steps: S1. After the trainee has been in a resting state for a preset time, apply alternating stimuli of the angles included in the perturbation tilt angle pair; collect and preprocess the EEG signals of the trainee in the resting state and during the stimulation process; S2. Extract rhythmic features from the preprocessed EEG data, calculate the EEG power spectral density at a specific frequency, and obtain neural feedback parameters; the neural feedback parameters are the difference between the EEG power spectral density during perturbation stimulation and the resting-state EEG power spectral density; S3. Calculate the threshold range of the neural feedback parameters, and calculate the feedback value based on the neural feedback parameters and the threshold range; the calculation of the threshold range of the neural feedback parameters includes: S30. Preset the deviation identification accuracy rate, obtain the baseline perturbation angle pair of the balance perturbation applied to the trainee when the balance perception assessment test result reaches the deviation identification accuracy rate, and the peak perturbation angle pair of the balance perturbation applied to the trainee when the identification accuracy rate is the highest; S31. Obtain the EEG power spectral density at a specific frequency when applying the standard stimulus angle perturbation in the baseline perturbation angle pair to the trainee, as the baseline threshold; obtain the EEG power spectral density at a specific frequency when alternately applying the standard stimulus angle perturbation and the deviation stimulus angle perturbation in the peak perturbation angle pair to the trainee, as the peak threshold; S32. Obtain the threshold range of the neural feedback parameters as greater than or equal to the baseline threshold and less than or equal to the peak threshold; S4. Based on the feedback value, the neural feedback parameters are mapped to neural feedback information, and the neural feedback information is presented to the trainee in a visual form. The trainee adjusts his / her neural activity in real time based on the presented neural feedback information to enhance his / her balance perception ability.

5. The balance perception enhancement method based on neurofeedback according to claim 4, characterized in that, The balance perception enhancement method further includes: S5. Configure a post-test balance perception assessment experiment to obtain the change in the accuracy of balance perturbation deviation identification when the trainee receives the same perturbation stimulus as in the pre-test balance perception assessment experiment, so as to verify the results of this round of balance perception training.

6. The balance perception enhancement method based on neural feedback according to claim 4, characterized in that, The pre-test balance perception assessment experiment uses a rhythmic stimulus plus oddball paradigm, with n perturbation sequences of the same angle as the standard stimulus and n-1 perturbation sequences of the same angle plus 1 perturbation sequence of a different angle as the deviation stimulus.

7. The balance perception enhancement method based on neural feedback according to claim 4, characterized in that, The feedback value is calculated based on the neural feedback parameters and threshold range, specifically as follows: when the neural feedback parameter is greater than the peak threshold, the feedback value is 1; when the neural feedback parameter is less than the baseline threshold, the feedback value is 0; when the neural feedback parameter is greater than or equal to the baseline threshold and less than or equal to the peak threshold, the feedback value is calculated using the following linear interpolation method: ， ； in, Indicates the feedback value. Indicates neural feedback parameters, Indicates the baseline threshold. This indicates the peak threshold.

8. The balance perception enhancement method based on neurofeedback according to claim 7, characterized in that, The neural feedback information is in the form of a ring, and the radius of the ring is determined as follows: ； in, Indicates the feedback value. Let be the radius of the annulus at the current moment. The radius of the annulus at the previous moment. It is a constant.

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