A training system for improving spatial contrast sensitivity in the elderly

Abstract

The application is particularly a training system for improving the spatial contrast sensitivity of the elderly, and relates to the technical field of visual function training, comprising: a training frequency evaluation module; a training parameter setting module; a training image generation module; and a training process control module.In the application, based on the functional status characteristics of the elderly, the training of spatial contrast sensitivity is efficiently realized through the synchronous combination of targeted training image design, rigorous training process control and training auxiliary equipment, and the functional decline in spatial perception caused by normal aging is quickly improved so as to restore the spatial contrast sensitivity to the level close to that of normal young people.

Description

Technical Field

[0001] This invention relates to the field of visual function training technology, and in particular to a training system for improving the spatial contrast sensitivity of older adults. Background Technology

[0002] The visual system's ability to perceive information at different spatial frequencies varies. This variation in perception typically manifests as an "asymmetric, inverted U-shaped" spatial contrast sensitivity curve. That is, the visual system is highly sensitive to mid-range spatial frequencies (1-10 cycles / degree), less sensitive to low spatial frequencies (<1 cycle / degree), and least sensitive to high spatial frequencies (>10 cycles / degree).

[0003] Spatial contrast sensitivity in living organisms is influenced by a variety of factors. For example, organic problems of the eye, such as myopia, astigmatism, glaucoma, and cataracts, can significantly reduce spatial contrast sensitivity. Furthermore, factors affecting the central visual nervous system, such as amblyopia and brain injury, can also decrease spatial contrast sensitivity. Existing data indicates that the visual system's ability to perceive high spatial frequencies is more susceptible to the influence of various factors.

[0004] According to a 1983 study by Cynthia Owsley et al. (Vision Research, Vol. 23, No. 7, pp. 689-699), the spatial contrast sensitivity of the human visual system gradually changes during normal aging, specifically manifesting as a gradual decrease in contrast sensitivity at mid-to-high spatial frequencies after age 40. This decrease in perceptual ability is more pronounced at high spatial frequencies than at mid-spatial frequencies.

[0005] Existing data indicates that visual perception learning (clinically also known as "visual training") helps improve various visual functions. However, training systems specifically designed to improve or enhance spatial contrast sensitivity in healthy older adults are currently almost nonexistent. It is important to emphasize that, compared to other visual function training systems, the design of systems to improve or enhance spatial contrast sensitivity in healthy older adults requires a primary focus on training efficiency. This is because the frequency range to be improved / trained in healthy older adults is extremely broad, ranging from 4 cycles / degree to 32 cycles / degree. If training is implemented at each desired frequency, based on a standard training time of 2-3 weeks per frequency, the entire training would require several months or even close to a year. Such an excessively long training period significantly increases the difficulty for older adults to persist in completing the training, drastically reducing the practical application value of the training.

[0006] Therefore, a training system for improving spatial contrast sensitivity in older adults is proposed to address the aforementioned problems. Summary of the Invention

[0007] The purpose of this invention is to provide a training system for improving the spatial contrast sensitivity of the elderly in order to solve the above-mentioned problems.

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

[0009] A training system for improving spatial contrast sensitivity in older adults includes:

[0010] The training frequency evaluation module uses a preset model to analyze and determine the training frequency based on the difference between the spatial contrast sensitivity curve of the individual before training and the preset standard spatial contrast sensitivity curve.

[0011] The training parameter setting module sets training parameters based on a determined training frequency, including the training amount, the initial difficulty of training image recognition, and the minimum unit of difficulty change.

[0012] The training image generation module generates visual stimulus images for training based on the training frequency determined by the training frequency evaluation module, the training parameters determined by the training parameter setting module, and the training parameters transmitted by the flow control module.

[0013] The training process control module is used for sequential control between different trials during a single training session. Specifically, it includes: analyzing the training effectiveness of the previous completed trial based on the environmental and training status information obtained from the monitoring equipment, and sending control signals to the training image generation module in combination with the individual trainee's recognition of the training images to adjust the training parameters in the next trial.

[0014] Preferably, in the training frequency evaluation module, the step of determining the training frequency includes:

[0015] S1-1. Calculate the difference between the spatial contrast sensitivity curve of the individual before training and the preset standard spatial contrast sensitivity curve, and perform standardization processing to convert the difference values ​​at all spatial frequencies into relative difference values ​​with a numerical range of [0,1].

[0016] S1-2. Use a pre-defined model to fit the relative differences to the data, and determine the optimal model based on statistical analysis; the formula for the pre-defined model is:

[0017] ;

[0018] ;

[0019] in, For spatial frequency, the value must be greater than 1.0; This represents the relative difference in contrast sensitivity at the corresponding spatial frequency after standardization, with a numerical range of [0,1]. σ and All are fitted parameters;

[0020] S1-3. Determine the main training frequency, specifically the spatial frequency corresponding to the data points with a contrast sensitivity of 2.0 on the spatial contrast sensitivity curve before training of the individual.

[0021] S1-4. Determine the corresponding secondary training frequency based on the selected model.

[0022] Preferably, the method by which the training image generation module generates training images includes:

[0023] S2-1. The training image is set to a circle, consisting of an inner circular region and an outer annular region. The relationship between the diameter of the inner circular region and the width of the outer annular region is as follows:

[0024] ;

[0025] S2-2. Based on the training frequency settings, determine the stimulus images within the inner circular region and the outer annular region, specifically as follows:

[0026] If only the main training frequency is used, then the training images are:

[0027] ;

[0028] If a secondary training frequency is set in addition to the primary training frequency, then the training image is as follows:

[0029] ;

[0030] If, in addition to the main training frequency, n secondary training frequencies are set, then the training stimuli include n classes of images, namely:

[0031] ;

[0032] in, and This represents the brightness at each point (x, y) in the training stimulus image; Average brightness; Main training frequency; The contrast ratio corresponds to the main training frequency; and For secondary training frequency; and The contrast value corresponding to the secondary training frequency is taken as the reciprocal of the contrast sensitivity corresponding to the secondary training frequency on the spatial contrast sensitivity curve before training. The viewpoint occupied by each point (x, y) in the image; and These are the orientations of the main training frequency grating and the secondary training frequency grating, respectively. and These are the phases of the main training frequency grating and the secondary training frequency grating, respectively, both of which are random values; For image masking.

[0033] Preferably, the recognition difficulty of the training image is determined by the contrast corresponding to the main training frequency within the inner circular region. The initial contrast value corresponding to the main training frequency is a first value. The initial contrast value corresponding to the secondary training frequency is set as the reciprocal of the contrast sensitivity at the corresponding spatial frequency on the spatial contrast sensitivity curve of the individual before training.

[0034] Preferably, the process control module for analyzing the training effectiveness of the previous trial and determining the training parameters for the next trial specifically involves the following process control method:

[0035] S3-1. If, during the presentation of the training images in the previous trial, the training process control module receives an abnormal status prompt signal from the monitoring device in the human-computer interaction module, then the previous trial is determined to be invalid, and a control signal is sent to the training image generation module to determine that in the next trial, the contrast of the main training frequency in the training image will not be adjusted, and the contrast of the previous trial will continue to be used; otherwise, it is determined to be valid, and proceeds to S3-2.

[0036] S3-2. If the training individual correctly identified the training stimulus image in the previous trial, the contrast of the main training frequency will decrease by 1 minimum change unit in the next trial; if the identification result was incorrect in the previous trial, the contrast of the main training frequency will increase by a first specified number of minimum change units in the next trial; where the first specified number is a positive integer greater than 1; if the number of secondary training frequencies determined by the training frequency evaluation module is greater than 1, proceed to S3-3.

[0037] S3-3. Determine the secondary training frequency to be used in the next trial.

[0038] Preferably, the method further includes:

[0039] The data recording and analysis module can analyze and adjust the contrast corresponding to the sub-training frequency in the next training session based on the completion status of each training session. Specific methods include:

[0040] S4-1. Based on the spatial contrast sensitivity curves of all individuals trained before the start of training and the preset standard spatial contrast sensitivity curve, calculate the difference in contrast sensitivity at the main training frequency and each sub-training frequency.

[0041] S4-2. Based on the contrast sensitivity threshold obtained at the main training frequency after the end of this training, calculate the difference in contrast sensitivity between the spatial contrast sensitivity curves before the start of all training and the preset standard spatial contrast sensitivity curve at the main training frequency.

[0042] S4-3. Following the principle of proportionally increasing the contrast sensitivity at each secondary training frequency after the training period, calculate the difference between the contrast sensitivity at that secondary training frequency and the preset standard spatial contrast sensitivity curve. ;

[0043] S4-4, Based on And the contrast sensitivity of the preset standard spatial contrast sensitivity curve at this sub-training frequency, calculate the contrast sensitivity at the sub-training frequency after this training. ;

[0044] S4-5, will The reciprocal of is set as the sub-training frequency in the next training iteration. The corresponding contrast.

[0045] Preferably, the azimuth of the main training frequency grating With the sub-training frequency grating orientation The relationship is:

[0046] and ;

[0047] in, It is a normal distribution function.

[0048] Preferably, in each trial of training image identification, it is necessary to distinguish between training images and interfering candidate images; the method for generating interfering candidate images includes:

[0049] If the training images contain only the main training frequencies, then the interfering candidate images are:

[0050] ;

[0051] If a secondary training frequency is set in addition to the primary training frequency in the training images, then the interfering candidate images are:

[0052] ;

[0053] in, This represents the brightness at each point (x, y) in the interfering candidate image; Average brightness; The interference frequency has a value range of [0.5, 1.0]. The contrast value corresponding to the interference frequency is taken as the reciprocal of the contrast sensitivity corresponding to the interference frequency on the spatial contrast sensitivity curve of the training individual before training. The viewpoint occupied by each point (x, y) in the image; The orientation of the interference frequency grating; The phase of the interference frequency grating is randomly selected.

[0054] Preferably, the method further includes:

[0055] The human-computer interaction module includes a display device, an information input device, a sound prompt device, and a monitoring device; the refresh rate of the display device is not lower than the second value, and can be used to achieve a flickering display of training images up to 40Hz.

[0056] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0057] 1. Based on the functional characteristics of the elderly, this invention can efficiently train spatial contrast sensitivity through targeted training image design, rigorous training process control, and synchronous use of training aids, thereby rapidly improving the functional decline in spatial perception caused by normal aging and restoring it to a level close to that of normal young people.

[0058] 2. This invention offers several advantages: First, it boasts strong personalization and adaptability. By comparing sensitivity curve differences and model fitting, it accurately locates the spatial frequency channels of individual decline, scientifically determines the primary and secondary training frequencies, and adapts to single-channel or multi-channel decline, avoiding the blindness of uniform training. Second, it offers high training efficiency. The inner-circle and outer-ring dual-layer image structure cleverly matches the primary and secondary frequency training needs. High-intensity training of the primary frequency ensures core effects, while the threshold contrast setting of the secondary frequency avoids interference and achieves efficient exposure, shortening the training process. Third, it offers excellent controllability during the training process. Through multi-dimensional monitoring of eye movement, distance, and illumination, it promptly corrects abnormal situations and dynamically adjusts the contrast based on trial recognition results, ensuring training effectiveness. Fourth, it offers good long-term training adaptability. The data recording and analysis module accurately evaluates the training stage and simultaneously optimizes the primary and secondary frequency contrast to adapt to the needs of different training stages. Fifth, it offers optional enhancement functions to improve the effect. Flickering stimulation and mid-frequency current stimulation enhance attention and neuroplasticity, while multimodal feedback further optimizes the training experience, making it suitable for the elderly and other groups, helping their visual function recover to near-youthful levels. Attached Figure Description

[0059] Further details, features, and advantages of this application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0060] Figure 1 This is an example diagram of a training system for improving spatial contrast sensitivity in the elderly, as proposed in this invention.

[0061] Figure 2 A schematic diagram of the training image and interfering candidate images;

[0062] Figure 3 This is a schematic diagram showing the training image and interfering alternative images presented sequentially in a single trial. Detailed Implementation

[0063] Several embodiments of this application will now be described in more detail with reference to the accompanying drawings to enable those skilled in the art to implement this application. This application may be embodied in many different forms and for various purposes and should not be limited to the embodiments set forth herein. These embodiments are provided to make this application thorough and complete, and to fully convey the scope of this application to those skilled in the art. The embodiments described do not limit this application.

[0064] Unless otherwise defined, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It will be further understood that terms such as those defined in commonly used dictionaries shall be interpreted as having a meaning consistent with their meaning in the relevant field and / or the context of this specification, and shall not be interpreted in an idealized or overly formal sense unless expressly defined herein.

[0065] Example 1

[0066] Its specific implementation method is combined with the appendix Figure 1 To be continued Figure 3 Please provide a detailed explanation.

[0067] Appendix Figure 1 This invention provides a structural block diagram of a training system for improving the spatial contrast sensitivity of the elderly, showing the connection relationship between the training frequency evaluation module and the training process control module, and annotating the main functional interaction flow of each module.

[0068] In this embodiment, it includes:

[0069] The training frequency evaluation module uses a preset model to analyze and determine the training frequency based on the difference between the spatial contrast sensitivity curve of the individual before training and the preset standard spatial contrast sensitivity curve.

[0070] The steps to determine the training frequency include:

[0071] S1-1. Calculate the difference between the spatial contrast sensitivity curve of the individual before training and the preset standard spatial contrast sensitivity curve, and perform standardization processing to convert the difference values ​​at all spatial frequencies into relative difference values ​​with a numerical range of [0,1].

[0072] S1-2. Use a pre-defined model to fit the relative differences to the data, and determine the optimal model based on statistical analysis; the formula for the pre-defined model is:

[0073] ;Formula 1;

[0074] ;Formula 2;

[0075] in, For spatial frequency, the value must be greater than 1.0; This represents the relative difference in contrast sensitivity at the corresponding spatial frequency after standardization, with a numerical range of [0,1]. σ and All are fitted parameters;

[0076] S1-3. Determine the main training frequency, specifically the spatial frequency (i.e., the horizontal axis) corresponding to the data points on the spatial contrast sensitivity curve before training of the individual, where the contrast sensitivity (i.e., the vertical axis) is equal to 2.0.

[0077] S1-4. Determine the corresponding secondary training frequencies based on the selected model, specifically as follows:

[0078] If the optimal model is Equation 1 and σ≤1.0, no secondary training frequency is set;

[0079] If the optimal model is Equation 1 and σ>1.0, set a secondary training frequency, specifically as follows:

[0080] ;Formula 3;

[0081] If the optimal model is Equation 2, multiple secondary training frequencies are set as follows:

[0082] and ;Formula 4;

[0083] in, Main training frequency, The sub-training frequency is set when a single sub-training frequency is used. This refers to the nth sub-training frequency when multiple sub-training frequencies are set, where n is a positive integer greater than or equal to 1. and Both are parameters. The former represents the bandwidth of the spatial frequency information processing channel in the visual system under normal circumstances, with a value range of 1.0 to 1.8 octaves, preferably 1.2 octaves; the latter represents the bandwidth of the spatial frequency information processing channel that processes the highest frequency information in the visual system of normal elderly people (i.e., the spatial frequency processed by this channel is higher than all other spatial frequency information processing channels), with a value range of 1.0 to 2.0 octaves, preferably 1.35 octaves.

[0084] If multiple sub-training gratings are set, the training images will also have various combinations of primary and secondary frequencies. For details on the selection of different combinations during training, please refer to the strategy description in the training process control module when determining the training parameters for the next trial.

[0085] To determine the optimal model, we first need to obtain the goodness of fit when using Equation 1 and Equation 2 for data fitting. The calculation method is as follows:

[0086] ;

[0087] in, For the goodness of fit of the data, The data predicted by the model (i.e., the expected value of the difference in contrast sensitivity at different spatial frequencies). These are the actual differences in contrast sensitivity at different spatial frequencies. This is the function for taking the average value.

[0088] After obtaining the goodness of fit, a comparison between models is necessary. Since Equation 1 uses one fewer fitting parameter than Equation 2 (i.e., the baseline), if the goodness of fit of Equation 1 is not lower than that of Equation 2, then Equation 1 can be determined as the best model. However, if the goodness of fit of Equation 2 is greater than that of Equation 1, further analysis should be conducted to determine whether the improvement in goodness of fit of Equation 2 is statistically significant.

[0089] If the model has a good fit, then Formula 2 can be determined as the optimal model; otherwise, Formula 1 remains the optimal model. To determine whether the improvement in goodness of fit of Formula 2 is statistically significant, one can use... test, The formula for calculating the value and its degrees of freedom is as follows:

[0090] ;

[0091] ;

[0092] ;

[0093] in, This represents the number of fitting parameters used in Formula 2 (i.e., 3 parameters). N represents the number of fitting parameters used in Formula 1 (i.e., 2 parameters), and N represents the number of data points used when fitting data using Formula 1 and Formula 2.

[0094] The steps in the training frequency assessment module described above for determining the training frequency are related to many important discoveries in the field of biomedical research, and are briefly described below:

[0095] (a) Numerous studies have shown that the human visual system perceives different spatial frequency information through different spatial frequency channels within the visual cortex. Spatial frequency channels typically exhibit band-pass characteristics, primarily processing spatial frequency information "within a certain range centered on a specific frequency." When a spatial frequency channel is affected, its function (e.g., sensitivity) changes significantly, while the functions of other spatial frequency channels remain largely unaffected. Therefore, when assessing damaged spatial frequency channels to determine training frequencies, the difference between the pre-training spatial contrast sensitivity curve and a preset standard value (preferably the contrast sensitivity curve of untrained normal young adults) is first calculated in S1-1. Then, Gaussian model analysis in S1-2 is used to assess spatial frequency information processing channels in the aging visual system that may exhibit functional decline. It is important to note that since the aging visual system does not exhibit functional decline at low spatial frequencies, data corresponding to spatial frequencies of 1.0 period / degree and below should be removed during model analysis in S1-2 to improve the accuracy of the analysis.

[0096] (b) If only one spatial frequency channel in the visual system of an elderly person experiences functional decline, then the model analysis in Formula 1 of S1-2 can effectively perform the assessment. In fact, although functional decline exists in all elderly individuals at medium and high spatial frequencies from a population perspective, individual differences cannot be ignored. Some elderly individuals, despite their advanced age, exhibit sensitivity at medium spatial frequencies comparable to younger individuals, only showing significant functional decline at high spatial frequencies. That is, only one spatial frequency channel experiences functional decline. In this case, the spatial frequency channel with impaired function suggested by the model analysis must be the spatial frequency information processing channel within the visual system that processes the highest frequency information (i.e., the spatial frequency processed by this channel is higher than all other spatial frequency information processing channels). Based on existing research experience and supporting data, the training frequency can be set to the spatial frequency corresponding to the data point with a contrast sensitivity of 2.0 on the spatial contrast sensitivity curve before training. This spatial frequency is also called the cutoff spatial frequency. Generally, the cutoff frequency of normal elderly individuals is above 20.0 cycles / degree.

[0097] (c) It is important to note that in the visual system of the elderly, there may be functional decline in two or more spatial frequency channels, manifested as lower sensitivity in multiple high spatial frequency segments compared to normal young adults. To effectively distinguish these situations, a comprehensive analysis combining the fitting parameter σ and the baseline is necessary. If two spatial frequency channels in the visual system of the elderly exhibit functional decline, these two channels must be adjacent, and one of them must be the spatial frequency information processing channel handling the highest frequency information within the visual system. Therefore, in the Gaussian model analysis in Equation 1, this will manifest as a functionally impaired, fusional spatial frequency channel with a significantly larger bandwidth. That is, the value of the fitting parameter σ in Equation 1 will be significantly higher than normal. In this case, two training frequencies should be set: one higher cutoff frequency and the other lower frequency, approximately one spatial frequency channel bandwidth away from the cutoff frequency. Because the bandwidth of the spatial frequency channel handling the highest frequency information at the cutoff frequency is slightly larger than that of the spatial frequency channel handling mid-to-low frequency information, the value range is 1.0–2.0 octaves, with 1.35 octaves being preferred in the system. Here, 1 octave represents a distance of 1 unit on a logarithmic coordinate axis with base 2. If the cutoff frequency is 24.0 cycles / degree, based on the above introduction, the lower training frequency can be calculated as 24 / 2^1.35 = 9.4 cycles / degree.

[0098] (d) If multiple spatial frequency channels in the elderly visual system experience functional decline, a significant difference will be observed across multiple segments of mid-to-high spatial frequencies when comparing the spatial contrast sensitivity curve before training with the preset standard value. This indicates that the existence of the parameter baseline is statistically significant, and Equation 2 represents the best-fit model. In this case, multiple training frequencies should be set, with the highest training frequency remaining the cutoff frequency. Other training frequencies should maintain a distance of one spatial frequency channel bandwidth from the previous training frequency. Based on existing research experience and supporting data, the distance between spatial frequency channels ranges from 1.0 to 1.8 octaves, with 1.2 octaves being preferred in the system. Furthermore, since the low spatial frequency processing capability of the elderly visual system shows almost no functional decline, the training frequency need not be lower than 4.0 cycles / degree. If the cutoff frequency is 24.0 cycles / degree, based on the above description, the training frequencies can be calculated as 24.0, 10.4, and 4.5 cycles / degree.

[0099] (e) Related research indicates that older adults can improve their contrast sensitivity at mid-to-high spatial frequencies through visual perception learning (also known as visual training), restoring it to a level roughly equivalent to that of untrained young adults. However, the sensitivity of the older visual system to training at different spatial frequencies varies considerably, with higher training intensity required at higher spatial frequencies to achieve optimal results. For mid-spatial frequencies of 2–10 cycles / degree, lower training intensity can produce significant training effects, essentially reaching the level of untrained healthy young adults. However, for high spatial frequencies greater than 10 cycles / degree, if the training intensity is insufficient, training at high spatial frequencies will quickly plateau, and the functional level will differ significantly from that of untrained healthy young adults. At this point, increasing the training intensity will further improve sensitivity at high spatial frequencies, until it reaches or approaches the level of untrained healthy young adults.

[0100] Therefore, when there is more than one determined training frequency, we should give full attention to the high spatial frequency that requires high-intensity training, set the cutoff frequency as the main training frequency to achieve good training results, and set other training frequencies as secondary training frequencies. We should also appropriately adjust the training strategy of the medium spatial frequency with lower training requirements to shorten the overall training process and improve the overall training efficiency.

[0101] It is worth noting that, as mentioned earlier, the training effect on older adults at high spatial frequencies is closely related to training intensity. At lower training intensities, training quickly plateaus, with the plateau level significantly different from that of untrained, healthy young adults. Only when the training intensity increases to a certain level will the training continue to be effective, enabling older individuals to achieve or approach the sensitivity levels of untrained, healthy young adults. Therefore, compared to other training systems, training systems targeting spatial contrast sensitivity in older adults require higher and more rigorous training volumes.

[0102] The training parameter settings module also allows you to set the presentation time of training images. To avoid eye drift when observing training images, the presentation time should not be too long, generally between 50 and 250 milliseconds. Preferably, the presentation time is 200 milliseconds.

[0103] The training parameter setting module also allows setting the initial difficulty and minimum difficulty change unit for training image recognition. The recognition difficulty of the training image is determined by the contrast of the core component of the image (i.e., the main training frequency grating). Since the main training frequency is the cutoff frequency, the contrast threshold level before training is fixed at 0.5. Therefore, the initial difficulty (i.e., the initial contrast value) can be set to 0.5–1.0, preferably 0.8, and the minimum contrast change unit (i.e., the minimum difficulty change unit) can range from 0.5 to 2.0 dB, preferably 1.0 dB.

[0104] Optionally, the stimulation size can also be set in the training parameter setting module. Considering the characteristics of the human eye, such as "spatial resolution gradually decreases from the center to the periphery in different visual fields, showing a radial distribution" and "the macula, which has the highest spatial resolution on the retina, generally does not exceed 6 degrees of visual angle," and the structural feature of "training images having a double-layered region of inner circle and outer ring" required by this system, the stimulation size is usually "5.0 to 6.0 degrees of visual angle in diameter." Preferably, the diameter of the inner circular region is 4.0 degrees of visual angle, the width of the outer ring region is 0.83 degrees of visual angle, and the overall diameter of the training image is 5.7 degrees of visual angle.

[0105] The training parameter setting module sets training parameters based on a determined training frequency, including the training amount, the initial difficulty of training image recognition, and the minimum unit of difficulty change.

[0106] The training image generation module generates visual stimulus images for training based on the training frequency determined by the training frequency evaluation module, the training parameters determined by the training parameter setting module, and the training parameters transmitted by the flow control module.

[0107] Methods for generating training images include:

[0108] S2-1. The training image is set to a circle, consisting of an inner circular region and an outer annular region. The relationship between the diameter of the inner circular region and the width of the outer annular region is as follows:

[0109] ;

[0110] S2-2. Based on the training frequency settings, determine the stimulus images within the inner circular region and the outer annular region, specifically as follows:

[0111] If only the main training frequency is used, then the training images are:

[0112] ;

[0113] If a secondary training frequency is set in addition to the primary training frequency, then the training image is as follows:

[0114] ;

[0115] If, in addition to the main training frequency, n secondary training frequencies are set, then the training stimuli include n classes of images, namely:

[0116] ;

[0117] in, and This represents the brightness at each point (x, y) in the training stimulus image; Average brightness; Main training frequency; The contrast ratio corresponds to the main training frequency; and For secondary training frequency; and The contrast value corresponding to the secondary training frequency is taken as the reciprocal of the contrast sensitivity corresponding to the secondary training frequency on the spatial contrast sensitivity curve before training. The viewpoint (in degrees) occupied by each point (x, y) in the image; and These are the orientations of the main training frequency grating and the secondary training frequency grating, respectively. and These are the phases of the main training frequency grating and the secondary training frequency grating, respectively, both of which are random values; As an image mask, its function is to make the grating stimulation within the inner circular region conform to a predetermined contrast. Fully rendered, but with reduced contrast of the grating stimulation within the outer annular region. It gradually decreases to 0 along the radial direction from the inside out.

[0118] Figure 2 The left-middle image shows an example of a training image. It can be seen that the primary training frequency is higher in the inner circular region, while the secondary training frequency is lower in the outer annular region. It should be noted that a higher contrast was used in the image here for clarity, but in actual training, because the contrast used for the secondary training frequencies remains at a threshold level, the image in the outer annular region always appears very blurry. Similarly, except for a few trials at the beginning of training, the contrast of the primary training frequency grating fluctuates around the threshold in the remaining trials, thus the image in the inner circular region also remains very blurry.

[0119] In addition, in the above formula It is related to the pixel size of the display device and the training distance, specifically:

[0120] ;

[0121] in, The viewpoint occupied by each point in the training image, in degrees per point; The actual size of each point in the training image (i.e., the pixel size of the display device), in centimeters; The distance is measured in centimeters.

[0122] It is important to emphasize that the circular structure of the training image, and the relationship between the diameter of the inner circular region and the width of the outer annular region, can ensure that the training image conforms to the physiological characteristics of the human visual system (i.e., the visual resolution is highest in the central field of vision and then decreases radially from the center to the periphery). On the other hand, it can structurally divide the training image into two regions of the same area but different spatial locations to match the settings of the training task.

[0123] The inner circular region contains the primary training frequency grating, which is directly related to the training task requirements. During training, individuals are required to identify the stimulus attributes of the training images within this region. For example, whether the grating's orientation is "rotated clockwise by a certain angle relative to the vertical direction" or "rotated counterclockwise by a certain angle." The outer annular region contains secondary training frequency gratings, used only for "repeated exposure" and not directly related to the training task requirements. In other words, to correctly complete the training task, individuals will concentrate on identifying the primary training frequency grating stimulus within the inner circular region. Simultaneously, because the outer annular region is adjacent to the inner circular region and its total area is relatively small (not exceeding 6.0 degrees of visual angle), individuals will "casually browse" the secondary training frequency gratings appearing simultaneously with the primary training frequency grating within the outer annular region while concentrating their attention. Studies have shown that during visual perception learning, the functional level of the core task of focused observation is significantly improved. While focusing on the core task stimulus, the visual system's ability to perceive other stimuli surrounding the core task stimulus, presented synchronously with it, repeatedly exposed to it, or casually viewed is also enhanced to some extent. Considering the earlier point that "the visual system of the elderly exhibits functional decline at both mid- and high spatial frequencies, but requires less training at mid-spatial frequencies, and low-intensity training can achieve good results," it can be seen that this double-layered training image design with an inner circle and outer ring precisely meets the different training intensity requirements of the elderly visual system for primary and secondary spatial frequencies, thereby improving training efficiency.

[0124] It should be noted that research indicates that other stimuli that are presented synchronously with, repeatedly exposed to, or incidentally viewed around the core task stimulus, if their intensity significantly exceeds a threshold level, will be perceived as "interference noise" by the visual system and thus suppressed, resulting in a loss of training effectiveness. Therefore, the contrast of the sub-training grating within the outer annular region should be set at the threshold level. On the other hand, the visual system's ability to perceive visual stimuli is related to the area of ​​the visual stimulus. Generally, the larger the area of ​​the visual stimulus, the easier it is to identify, and the lower the identification threshold. Therefore, when the area of ​​the outer annular region is set to be the same as the area of ​​the inner circular region, and the area of ​​the inner circular region is roughly equivalent to the stimulus area used in the pre-training spatial contrast sensitivity curve measurement, the contrast of the sub-training frequency grating can be directly selected from the pre-training spatial contrast sensitivity curve.

[0125] It should be noted that although trainees are instructed to "focus on the features of the training image within the inner circular region and complete the image recognition task," it is inevitable that when faced with a high level of difficulty and unable to accurately identify the main training frequency grating within the inner circular region, trainees will unconsciously rely on all possible, ambiguous perceptions to make task judgments, regardless of whether this ambiguity originates from the inner circular region or the outer annular region. In other words, the secondary training frequency grating within the outer annular region can still interfere with the identification of the main training frequency grating within the inner circular region.

[0126] The recognition difficulty of the training image is determined by the contrast corresponding to the main training frequency within the inner circular region. The initial contrast value corresponding to the main training frequency is the first value. The initial contrast value corresponding to the secondary training frequency is set to the reciprocal of the contrast sensitivity at the corresponding spatial frequency on the spatial contrast sensitivity curve of the individual before training.

[0127] The process of obtaining the first value includes: if the main training frequency is less than 4 cycles / degree, the first value is set to 0.6; if the main training frequency is greater than or equal to 4 cycles / degree but less than 10 cycles / degree, the first value is set to 0.7; if the main space frequency is greater than or equal to 10 cycles / degree, the first value is set to 0.8.

[0128] The training process control module is used for sequential control between different trials during a single training session. Specifically, it includes: analyzing the training effectiveness of the previous completed trial based on the environmental and training status information obtained from the monitoring equipment, and sending control signals to the training image generation module in combination with the individual trainee's recognition of the training images to adjust the training parameters in the next trial.

[0129] The training process control module analyzes the training effectiveness of the previous trial and determines the specific process control method for the training parameters in the next trial as follows:

[0130] S3-1. If, during the presentation of the training images in the previous trial, the training process control module receives an abnormal status prompt signal from the monitoring device in the human-computer interaction module, then the previous trial is determined to be invalid, and a control signal is sent to the training image generation module to determine that in the next trial, the contrast of the main training frequency in the training image will not be adjusted, and the contrast of the previous trial will continue to be used; otherwise, it is determined to be valid, and proceeds to S3-2.

[0131] S3-2. If the training individual correctly identified the training stimulus image in the previous trial, the contrast of the main training frequency will decrease by 1 minimum change unit in the next trial; if the identification result was incorrect in the previous trial, the contrast of the main training frequency will increase by a first specified number of minimum change units in the next trial; where the first specified number is a positive integer greater than 1; if the number of secondary training frequencies determined by the training frequency evaluation module is greater than 1, proceed to S3-3.

[0132] S3-3. Determine the secondary training frequency to be used in the next trial, specifically:

[0133] ;

[0134] in, The secondary training frequency to be used in the next trial; Main training frequency; For the remainder function, is the total number of all valid trials completed in this training, and n is the total number of sub-training frequencies; The parameter has the same meaning as in S1-4.

[0135] As described above, when there are n secondary training frequencies during training, there are also n corresponding primary and secondary training combinations for the training images. During training, these combinations will appear in turn in the effective training trials. This setting ensures that the n secondary training frequencies receive equal "exposure intensity" and "exposure duration".

[0136] The data recording and analysis module is used to record and analyze the training data for this session, and can evaluate the overall training progress based on all training data recorded this time and previously.

[0137] Based on the completion status of each training session, the contrast corresponding to the sub-training frequency in the next training session can be analyzed and adjusted. Specific methods include:

[0138] S4-1. Based on the spatial contrast sensitivity curves of all individuals trained before the start of training and the preset standard spatial contrast sensitivity curve, calculate the difference in contrast sensitivity at the main training frequency and at each sub-training frequency, and record them as follows: and Specifically:

[0139] ;

[0140] ;

[0141] in, The contrast sensitivity corresponding to the main training frequency on the preset standard spatial contrast sensitivity curve; The contrast sensitivity corresponding to each sub-training frequency on the preset standard spatial contrast sensitivity curve; The contrast sensitivity on the spatial contrast sensitivity curve of all individuals trained before training begins, corresponding to the main training frequency; The contrast sensitivity corresponding to each sub-training frequency on the spatial contrast sensitivity curve of all individuals trained before training begins.

[0142] S4-2. Based on the contrast sensitivity threshold obtained at the main training frequency after this training, calculate the difference in contrast sensitivity between the spatial contrast sensitivity curves before all training begins and the preset standard spatial contrast sensitivity curve at the main training frequency, denoted as . Specifically:

[0143] ;

[0144] in, The contrast sensitivity obtained at the main training frequency after the completion of this training;

[0145] S4-3. Following the principle of proportionally increasing the contrast sensitivity at each secondary training frequency after the training period, calculate the difference between the contrast sensitivity at that secondary training frequency and the preset standard spatial contrast sensitivity curve. Specifically:

[0146] ;

[0147] S4-4, Based on And the contrast sensitivity of the preset standard spatial contrast sensitivity curve at this sub-training frequency, calculate the contrast sensitivity at the sub-training frequency after this training. ;

[0148] ;

[0149] S4-5, will The reciprocal of is set as the sub-training frequency in the next training iteration. The corresponding contrast.

[0150] The data recording and analysis module can also analyze and adjust the starting contrast corresponding to the main training frequency at the start of the next training session based on the completion status of each training session, specifically:

[0151] ;

[0152] in, The initial contrast corresponding to the main training frequency at the start of the next training session; This is the initial contrast corresponding to the main training frequency at the start of this training session; This is the contrast threshold corresponding to the main training frequency, obtained from the analysis after the end of this training session. This is a function that takes the minimum value.

[0153] It should be noted that the strategy of adjusting the contrast of the primary and secondary training frequencies in the next training session based on the results of this training is aimed at achieving better training results. Generally, after each training session, the contrast sensitivity of the individual at the primary and secondary training frequencies will improve to some extent, especially in the early stages of training. At this time, appropriately adjusting the initial contrast of the primary training frequency helps to reach the threshold level corresponding to the primary training frequency more quickly in the next training session, thereby obtaining more training time near the threshold level and achieving better training results. Furthermore, based on the degree of improvement in contrast sensitivity at the primary training frequency, simultaneously increasing the contrast at the secondary training frequencies in the training images helps to keep the secondary training frequency grating near the threshold level, improving the "exposure" effect (i.e., training effect) of the secondary training frequency grating. As mentioned earlier, other stimuli that are around the core task stimulus, presented synchronously with the core task stimulus, repeatedly exposed, or casually viewed, if their intensity significantly exceeds the threshold level, will be perceived as "interference noise" by the visual system and thus suppressed, resulting in a loss of training effect.

[0154] As mentioned earlier, the entire training process for older adults requires a duration ranging from ten days to one to two months. So, how do the behavioral characteristics of older adults change during the training process? Based on the general principles of functional training, we can understand that the entire training process can be roughly divided into three stages in the long term. At the beginning of training, the individual's functional level improves rapidly; this rapid improvement stage can be considered the first stage. Subsequently, the improvement in functional level enters a slow growth stage; this stage can be considered the second stage. Finally, functional level reaches a plateau; even with continued training, no significant increase in functional level can be observed; this stage can be considered the third stage.

[0155] Therefore, the data recording and analysis module can further evaluate the overall training progress of an individual over a long period of training based on the "contrast threshold obtained in this training session." Specific steps include:

[0156] S5-1. List the contrast thresholds for all main training frequencies in this and previous records. If the number is not less than the first specified number, then evaluate the overall training progress. During the evaluation, first use the following formula to fit the data:

[0157] ;(Formula 5)

[0158] ;(Formula 6)

[0159] in, This refers to the contrast threshold obtained during the nth training iteration in this and previous training iterations; n is a positive integer greater than or equal to 1; a, b, c, and d are all parameters to be fitted; preferably, the first specified number is 8.

[0160] S5-2. Evaluate the results of data fitting using Formula 5 and Formula 6 in S5-1. If the goodness of fit obtained using Formula 5 is better than that obtained using Formula 6, and the data fitting using Formula 5 is statistically significant, then it is determined that "the training process is in the first stage," and the evaluation ends. If the goodness of fit obtained using Formula 5 is better than that obtained using Formula 6, but the data fitting using Formula 5 is not statistically significant, then it is determined that "the training process is in the third stage," and the evaluation ends. If the goodness of fit obtained using Formula 6 is better than that obtained using Formula 5, and the data fitting using Formula 6 is statistically significant, then it is preliminarily determined that "the training process has entered the second stage," and proceed to S5-3.

[0161] S5-3. Based on the contrast threshold obtained at the second specified number of main training frequencies, the formula in S5-1 is used again for data fitting. If the goodness of fit of the data obtained by using formula 5 is better than the goodness of fit of the data obtained by using formula 6, but the data fitting using formula 5 is not statistically significant, then it is determined that "the training process has entered the third stage"; otherwise, it is formally determined that "the training process has entered the second stage". Preferably, the second specified number is 6.

[0162] It should be noted that Formula 5 indicates a linear relationship between the number of training iterations and the functional level, while Formula 6 indicates an exponential relationship. Correspondingly, Formula 5 better matches the "Phase One" scenario in the training process, while Formula 6 better matches the "Phase One + Phase Two" scenario. Therefore, if the data fitting results show that Formula 5 has a better fit than Formula 6, it can be determined that the current training process is still in Phase One. If the data fitting results show that Formula 4 has a better fit, the training process has necessarily surpassed "Phase One." However, whether it is in "Phase Two" or "Phase Three" at this point requires analysis of the latest training data. If the latest training data exhibits a linear change (i.e., as mentioned in S5-3, "the goodness of fit obtained using Formula 5 is better than the goodness of fit obtained using Formula 6, but the data fitting using Formula 5 is not statistically significant"), it indicates that the functional level no longer improves with the training process, and the training has entered "Phase Three"; otherwise, it can be determined that the current training process is still in "Phase Two."

[0163] When using Formulas 5 and 6 for data fitting, the method for calculating the goodness of fit is similar to that for Formulas 1 and 2, as follows:

[0164] ;

[0165] in, For the goodness of fit of the data, The data predicted for the model (here, the linear model corresponding to Equation 5, or the exponential function model corresponding to Equation 6). This data was obtained during actual training. The contrast threshold obtained during the nth training iteration. This is the function for taking the average value.

[0166] To reduce the interference of the secondary training frequency grating on the primary training frequency grating, optimization can be achieved through the following two methods:

[0167] (a) Optional, main training frequency grating orientation With the sub-training frequency grating orientation The relationship is:

[0168] and ;

[0169] in, It is a normal distribution function.

[0170] The sub-training frequency grating orientation is selected from a normal distribution with a mean orthogonal to the main training frequency grating and a standard deviation of less than 15 degrees. This setting ensures that the sub-training frequency grating orientation not only possesses a degree of randomness but also consistently maintains a significant difference from the main training frequency grating orientation. Therefore, even if a trainee develops a vague sense of the sub-training frequency grating during training, relying on this sense to identify the attributes of the main training frequency grating (e.g., whether the grating orientation is "rotated clockwise by a certain angle relative to the vertical direction" or "rotated counterclockwise by a certain angle") is highly likely to result in errors.

[0171] (b) Optionally, in each trial of training image recognition, instead of the task mode of "requiring the trainee to judge the stimulus attribute after a single presentation of the training image," a task mode of "requiring the trainee to judge the sequential position of the training image after the training image and interfering alternative images are presented in a random order" is adopted, such as... Figure 3 As shown, this is essentially a "mandatory either / or" choice, requiring the trainee to distinguish between images within two time windows: which window contains the training image and which contains the distracting candidate image. It's important to emphasize that the "mandatory" aspect means that while acknowledging that "the image in one time window is the training image," it also acknowledges that "the image in the other time window is the distracting candidate image." This differs from the situation where the training image or the distracting candidate image is presented individually, requiring the trainee to make a judgment. When presented individually, the trainee's judgment of the training image does not affect its judgment of the distracting candidate image.

[0172] In each trial of training image recognition, it is necessary to distinguish between training images and distracting candidate images; the methods for generating distracting candidate images include:

[0173] If the training images contain only the main training frequencies, then the interfering candidate images are:

[0174] ;

[0175] If a secondary training frequency is set in addition to the primary training frequency in the training images, then the interfering candidate images are:

[0176] ;

[0177] in, This represents the brightness at each point (x, y) in the interfering candidate image; Average brightness; The interference frequency has a value range of [0.5, 1.0]. The contrast value corresponding to the interference frequency is taken as the reciprocal of the contrast sensitivity corresponding to the interference frequency on the spatial contrast sensitivity curve of the training individual before training. The viewpoint (in degrees) occupied by each point (x, y) in the image; The orientation of the interference frequency grating; The phase of the interference frequency grating is randomly selected.

[0178] Figure 2 The right image shows an example of a distracting candidate image. It can be seen that the inner circular region of the right image represents the average brightness, while the frequency of the distracting grating in the outer annular region of the right image is significantly lower than the sub-training frequency in the outer annular region of the left image. Furthermore, the orientation of the distracting grating is 45 degrees counterclockwise from the vertical orientation. It should be noted that... Figure 2 To display the image more clearly, a high contrast was used in the image, so the left and right images look very different. However, in actual training, when the contrast of the main training frequency grating, the secondary training frequency grating, and the interference frequency grating are all near the threshold level, the visual perception of the main training frequency grating (left image) in the inner annular region is almost the same as the average brightness (right image). The secondary training frequency grating (right image) in the outer annular region, like the interference frequency grating, also appears very blurry and difficult to distinguish.

[0179] Understandably, in this task mode, not only the outer annular region of the training image, but also interfering alternative images can cause blurring in the trainee's perception. Under the "forced binary choice" task requirement, the trainee must make a discriminative selection (which time window contains the training image and which contains the interfering alternative image). This setting greatly reduces the interference of the secondary training frequency grating in the outer annular region on the primary training frequency grating in the inner circular region.

[0180] It is worth mentioning that in the above task modes, the interference frequency should be far away from the training frequency, and especially should not be consistent with the secondary training frequency, otherwise it will affect the training effect under the secondary training frequency.

[0181] The human-computer interaction module includes a display device, an information input device, an audio prompt device, and a monitoring device. The display device is used to present the generated training images to the trainee, and the information input device is used to obtain the trainee's recognition of the training images. The audio prompt device is used to provide feedback to the trainee on the correctness / incorrectness of the training image recognition. The monitoring device is used to monitor the training environment and the training status of the trainee, and can send prompt signals to the training process control module based on the abnormal status detected, while reminding the trainee to correct the abnormal status through the audio prompt device.

[0182] The monitoring equipment of the human-computer interaction module includes an eye-tracking monitoring device, which is used to monitor the direction of the trainee's gaze when the training image appears. When it is found that the angle of the trainee's gaze deviates from the center of the training image by more than the preset ratio of the viewing angle corresponding to the diameter of the inner circular area of ​​the training image, an abnormal situation prompt signal is sent to the training process control module in real time, and an audio prompt to correct the gaze direction is sent to the trainee through the audio prompt device.

[0183] The refresh rate of the display device is no less than the second value, which can be used to achieve a flickering display of training images up to 40Hz.

[0184] Generally, training does not place high demands on the display device in the human-computer interaction module; most commonly used LCD monitors are sufficient. However, it's important to note that some children are not sensitive to training images, showing no substantial functional improvement after repeated training sessions. In such cases, it's necessary to use reinforcing visual stimulation, specifically flashing training images, without significantly altering other settings. The flashing frequency should range from 1.0 to 40.0 Hz. It's worth noting that flashing visual images automatically attract and maintain the trainee's attention, especially in children. Therefore, this setting helps them focus more on the training task, effectively improving training results. Furthermore, research shows that 40 Hz flashing stimulation guides the visual cortex to generate electrical activity of the same frequency, allowing this rhythm to propagate to other brain regions (such as the hippocampus and prefrontal cortex), thereby synchronizing and enhancing gamma-wave activity throughout the brain and exerting a series of positive and beneficial physiological effects, including enhanced neuroplasticity and improved coordination between different brain regions. To ensure the image flicker frequency reaches the maximum requirement of 40Hz and to avoid image distortion that may occur during continuous image refresh, the presentation time of each image during flickering should be no less than 3 frames. Therefore, the number of refreshes per second of the display device should be no less than (3+3)×40=240 frames. Among them, 120 frames are training images and 120 frames are gray backgrounds. That is, optionally, the refresh rate of the display device in the human-computer interaction module is not lower than the second value. Preferably, the second value is 240Hz.

[0185] Optionally, the eye-tracking monitoring device is used to monitor the gaze direction of the trainee when the training image appears; when it is found that the angle of the trainee's gaze direction deviates from the center of the training image by more than a preset proportion corresponding to the viewing angle of the inner circular area of ​​the training image, an abnormal situation prompt signal is sent to the training process control module in real time, and an audio prompt message "Correct gaze direction" is sent to the trainee through an audio prompt device. Preferably, the preset proportion is 20%.

[0186] It should be noted that due to the unique structure of the inner circle and outer ring of the training image, and the training task requiring the trainees to focus primarily on the inner circle region, this training system has higher and stricter requirements for monitoring eye movements than ordinary training systems. If the eye movements of the trainees cannot be effectively monitored, the design concept of simultaneously obtaining efficient training of primary and secondary frequencies cannot be implemented, and the training effect will inevitably be greatly reduced.

[0187] Optionally, the training distance monitoring device monitors and displays the distance between the device and the trainee in real time using a distance sensor; when the monitored distance exceeds a preset proportion of the predetermined training distance, it sends an abnormal situation prompt signal to the training process control module in real time, indicating that the training behavior is not standardized, and sends an audio prompt to the trainee to "correct training distance" through an audio prompt device; preferably, the preset proportion is 10%.

[0188] It should be noted that, since the parameter DPD in the training image formula is directly related to the training distance, and DPD further affects the spatial frequency of the training grating, this training system has higher and stricter requirements for monitoring the training distance than ordinary training systems. If the training distance cannot be effectively monitored, the design of the primary and secondary training frequencies will deviate significantly in implementation, thereby significantly reducing the training effect.

[0189] Optionally, the ambient illuminance monitoring device monitors the illuminance of the training environment in real time using an illuminance sensor. When the relative change in ambient illuminance compared to the initial ambient illuminance exceeds a preset proportion, an abnormal situation alert signal is sent to the training process control module in real time, indicating a significant change in the training environment. An audible alert, "Correct ambient illuminance," is also sent to the individual trainee. Preferably, the preset proportion is 50%. It should be noted that higher ambient illuminance reduces the contrast of the grating stimulation presented to the individual trainee, interfering with training process control and thus affecting training effectiveness.

[0190] Optionally, to achieve better training results, the human-computer interaction module also includes a mid-frequency current stimulation device, which can generate a low-frequency modulated mid-frequency current and act on acupoints around the eyes during the presentation of training images; optionally, both the mid-frequency carrier current and the low-frequency modulation signal use sinusoidal alternating current, with the frequency range of the mid-frequency carrier current being 1.0kHz to 5.0kHz and the frequency range of the low-frequency modulation signal being 10.0Hz to 120.0Hz.

[0191] When a low-frequency modulated mid-frequency current is applied to acupoints around the eyes, the output power is related to the color contrast of the target stimulus in the training image, as shown in the formula:

[0192] ;

[0193] in, , These are the minimum and maximum values ​​of the output power, respectively, and C is the contrast of the main training frequency grating in the training image; Preferred , They are 0.5W and 5.0W respectively.

[0194] It should be noted that perceptions from different sensory organs can be interconnected. The underlying mechanism is highly complex, involving cognitive integration and neurotransmitter regulation, among other factors. In practical applications, using low-frequency modulated mid-frequency current applied to acupoints around the eyes during training image presentation can effectively create a linkage between "visually meaningful light stimulation" and "surface electrical stimulation" within the body, effectively promoting visual cognitive optimization and enhancing training results. Furthermore, when the target stimulus has low color contrast and high recognition difficulty, the intensity of electrical stimulation can be increased to strengthen visual cognitive optimization under high difficulty. Additionally, the above formula describes the relationship between two types of stimulus energy, namely the relationship between the visual signal energy carried by the training image and the current energy; therefore, the formula uses... Instead .

[0195] ;

[0196] in, The coordinates on the training image are The contrast of the points.

[0197] Numerous scientific studies have shown that providing feedback to trainees during training, indicating correct or incorrect identification, helps them subconsciously adjust their identification strategies and promotes functional optimization, especially when the identification difficulty is high. Generally, this feedback is provided through sound. For example, a specific cue tone is given when the identification is correct; no cue tone is given when the identification is incorrect, or a different cue tone is given. However, considering the aforementioned sensory linkage effect, providing training feedback through electrical stimulation can actually achieve better results. Therefore, optionally, the mid-frequency current stimulation device can also provide training feedback through current stimulation, specifically: in each trial, after the trainee completes the identification of the target stimulus in the training pattern, if the identification is correct, a current stimulation with a specified power and duration is provided; otherwise, no current stimulation is provided. Preferably, the first specified power is 2.5W and the duration is 0.5s.

[0198] Optionally, to avoid confusion of training data between different training individuals and to improve the effectiveness and accuracy of training progress evaluation (for details on training progress evaluation, please refer to the introduction related to the data recording and analysis module later), basic information of the training individual can be entered through the information input device of the human-computer interaction module during each training session, which will be used as an identifier for recording, storing and retrieving training data.

[0199] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0200] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0201] It should be noted that, in this document, the use of relational terms such as "first" and "second" is merely for distinguishing one entity or operation from another, and does not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0202] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0203] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0204] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0205] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0206] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0207] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0208] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A training system for improving spatial contrast sensitivity in older adults, characterized in that, include: The training frequency evaluation module uses a preset model to analyze and determine the training frequency based on the difference between the spatial contrast sensitivity curve of the individual before training and the preset standard spatial contrast sensitivity curve. The steps to determine the training frequency include: S1-1. Calculate the difference between the spatial contrast sensitivity curve of the individual before training and the preset standard spatial contrast sensitivity curve, and perform standardization processing to convert the difference values ​​at all spatial frequencies into relative difference values ​​with a numerical range of [0,1]. S1-2. Use a pre-defined model to fit the relative differences to the data, and determine the optimal model based on statistical analysis; the formula for the pre-defined model is: ； ； in, For spatial frequency, the value must be greater than 1.0; This represents the relative difference in contrast sensitivity at the corresponding spatial frequency after standardization, with a numerical range of [0,1]. σ and All are fitted parameters; S1-3. Determine the main training frequency, specifically the spatial frequency corresponding to the data points with a contrast sensitivity of 2.0 on the spatial contrast sensitivity curve before training of the individual. S1-4. Determine the corresponding sub-training frequency based on the selected model; The training parameter setting module sets training parameters based on a determined training frequency, including the training amount, the initial difficulty of training image recognition, and the minimum unit of difficulty change. The training image generation module generates visual stimulus images for training based on the training frequency determined by the training frequency evaluation module, the training parameters determined by the training parameter setting module, and the training parameters transmitted by the flow control module. The training process control module is used for sequential control between different trials during a single training session. Specifically, it includes: analyzing the training effectiveness of the previous completed trial based on the environmental and training status information obtained from the monitoring equipment, and sending control signals to the training image generation module in combination with the individual trainee's recognition of the training images to adjust the training parameters in the next trial.

2. The training system for improving spatial contrast sensitivity in the elderly according to claim 1, characterized in that, The training image generation module generates training images using the following methods: S2-1. The training image is set to a circle, consisting of an inner circular region and an outer annular region. The relationship between the diameter of the inner circular region and the width of the outer annular region is as follows: ； S2-2. Based on the training frequency settings, determine the stimulus images within the inner circular region and the outer annular region, specifically as follows: If only the main training frequency is used, then the training images are: ； If a secondary training frequency is set in addition to the primary training frequency, then the training image is as follows: ； If, in addition to the main training frequency, n secondary training frequencies are set, then the training stimuli include n classes of images, namely: ； in, and This represents the brightness at each point (x, y) in the training stimulus image; Average brightness; Main training frequency; The contrast ratio corresponds to the main training frequency; and For secondary training frequency; and The contrast value corresponding to the secondary training frequency is taken as the reciprocal of the contrast sensitivity corresponding to the secondary training frequency on the spatial contrast sensitivity curve before training. The viewpoint occupied by each point (x, y) in the image; and These are the orientations of the main training frequency grating and the secondary training frequency grating, respectively. and These are the phases of the main training frequency grating and the secondary training frequency grating, respectively, both of which are random values; For image masking.

3. A training system for improving spatial contrast sensitivity in the elderly according to claim 2, characterized in that, The recognition difficulty of the training image is determined by the contrast corresponding to the main training frequency within the inner circular region. The initial contrast value corresponding to the main training frequency is the first value. The initial contrast value corresponding to the secondary training frequency is set to the reciprocal of the contrast sensitivity at the corresponding spatial frequency on the spatial contrast sensitivity curve of the individual before training.

4. A training system for improving spatial contrast sensitivity in the elderly according to claim 1, characterized in that, The training process control module analyzes the training effectiveness of the previous trial and determines the specific process control method for the training parameters in the next trial as follows: S3-1. If, during the presentation of the training images in the previous trial, the training process control module receives an abnormal status prompt signal from the monitoring device in the human-computer interaction module, then the previous trial is determined to be invalid, and a control signal is sent to the training image generation module to determine that in the next trial, the contrast of the main training frequency in the training image will not be adjusted, and the contrast of the previous trial will continue to be used; otherwise, it is determined to be valid, and proceeds to S3-2. S3-2. If the training individual correctly identified the training stimulus image in the previous trial, the contrast of the main training frequency will decrease by 1 minimum change unit in the next trial; if the identification result was incorrect in the previous trial, the contrast of the main training frequency will increase by a first specified number of minimum change units in the next trial; where the first specified number is a positive integer greater than 1; if the number of secondary training frequencies determined by the training frequency evaluation module is greater than 1, proceed to S3-3. S3-3. Determine the secondary training frequency to be used in the next trial.

5. A training system for improving spatial contrast sensitivity in the elderly according to claim 1, characterized in that, Also includes: The data recording and analysis module can analyze and adjust the contrast corresponding to the sub-training frequency in the next training session based on the completion status of each training session. Specific methods include: S4-1. Based on the spatial contrast sensitivity curves of all individuals trained before the start of training and the preset standard spatial contrast sensitivity curve, calculate the difference in contrast sensitivity at the main training frequency and each sub-training frequency. S4-2. Based on the contrast sensitivity threshold obtained at the main training frequency after the end of this training, calculate the difference in contrast sensitivity between the spatial contrast sensitivity curves before the start of all training and the preset standard spatial contrast sensitivity curve at the main training frequency. S4-3. Following the principle of proportionally increasing the contrast sensitivity at each secondary training frequency after the training period, calculate the difference between the contrast sensitivity at that secondary training frequency and the preset standard spatial contrast sensitivity curve. ; S4-4, Based on And the contrast sensitivity of the preset standard spatial contrast sensitivity curve at this sub-training frequency, calculate the contrast sensitivity at the sub-training frequency after this training. ; S4-5, will The reciprocal of is set as the sub-training frequency in the next training iteration. The corresponding contrast.

6. A training system for improving spatial contrast sensitivity in older adults according to claim 3, characterized in that, Main training frequency grating orientation With the sub-training frequency grating orientation The relationship is: and ; in, It is a normal distribution function.

7. A training system for improving spatial contrast sensitivity in older adults according to claim 3, characterized in that, In each trial of training image recognition, it is necessary to distinguish between training images and distracting candidate images; the methods for generating distracting candidate images include: If the training images contain only the main training frequencies, then the interfering candidate images are: ； If a secondary training frequency is set in addition to the primary training frequency in the training images, then the interfering candidate images are: ； in, This represents the brightness at each point (x, y) in the interfering candidate image; Average brightness; The interference frequency has a value range of [0.5, 1.0]. The contrast value corresponding to the interference frequency is taken as the reciprocal of the contrast sensitivity corresponding to the interference frequency on the spatial contrast sensitivity curve of the training individual before training. The viewpoint occupied by each point (x, y) in the image; The orientation of the interference frequency grating; The phase of the interference frequency grating is randomly selected.

8. A training system for improving spatial contrast sensitivity in older adults according to claim 1, characterized in that, Also includes: The human-computer interaction module includes display devices, information input devices, sound prompt devices, and monitoring devices; The refresh rate of the display device is no less than the second value, which can be used to achieve a flickering display of training images up to 40Hz.

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