Cerebral stroke detection device based on pupil monitoring and control and control method thereof

Abstract

The invention discloses a cerebral apoplexy detection device based on pupil monitoring and control, which comprises a device body, a pupil monitoring module and a main control module, the pupil monitoring module is arranged on the device body and used for collecting pupil state images of a user in real time. And the main control module is in communication connection with the pupil monitoring module and is used for determining the physical state of the user according to the pupil state image. According to the invention, real-time monitoring of the body state of the stroke patient and advanced prediction of the incidence risk can be realized.

Description

Technical Field

[0001] The present invention relates to a field, and in particular to a stroke detection device based on pupil monitoring and control and a control method thereof. Background Art

[0002] With the development of industrialization, urbanization, population aging, and changes in the ecological environment and lifestyle, chronic non-communicable diseases have become the main cause of death among Chinese residents, accounting for more than 70% of the total disease burden, and have become an important factor restricting the improvement of healthy life expectancy. Stroke is an acute cerebrovascular disease caused by sudden rupture of brain blood vessels or blockage of blood vessels that prevents blood from flowing into the brain, causing brain tissue damage. It is the leading cause of death and disability among Chinese residents, and seriously affects my country's economic and social development and national health. Evidence-based medicine has confirmed that rehabilitation is the most effective way to reduce the disability and mortality rate of stroke, and is also an indispensable key link in the organized management model of stroke.

[0003] There are many rehabilitation products for upper or lower limbs in the domestic market. The lower limbs are mainly rehabilitation training chairs and rehabilitation pedal bicycles, while the upper limbs are mainly stretching devices. Although these rehabilitation devices have their own characteristics, there is a significant problem: they are all independent rehabilitation devices for the upper and lower limbs, without an integrated rehabilitation design, and there is no rehabilitation device design that can detect the status of stroke patients in real time.

[0004] However, massage therapy has many benefits for stroke patients. Massage therapy can promote blood circulation, relieve muscle spasms, improve joint mobility, relieve pain and promote nerve recovery for people with stroke. With the development of science and technology, the technical content of massage chairs has been continuously improved, and the consumer group of massage chairs has gradually expanded, but they are all for the general public, and there is no one specifically for people with stroke. Nowadays, the strength and design of most massage chairs in China are not suitable for people with stroke, and there is no massage chair design that can monitor the patient's current state through pupil data in real time. When a stroke occurs, changes in pupil size can reflect the state of the nervous system. Stroke generally affects one side of the brain, which may cause the pupil on the affected side to dilate, while the other side is normal or shrinking; it may also occur in some cases, and the pupils on both sides may become unequal in size, or both dilate. In general, pupil changes are an important indicator for judging the severity and location of stroke. If these changes are observed in real time, the suddenness of stroke can be prevented or correctly judged, and medical help can be sought in time.

[0005] In summary, although the existing massage auxiliary devices can provide a certain degree of comfort and relaxation, their designs still have the following shortcomings in view of the special needs of people with stroke:

[0006] 1. Most massage assistive devices lack real-time monitoring of the status of stroke patients. Stroke attacks are generally sudden and rapid, usually manifesting within a few minutes. The suddenness makes timely diagnosis and treatment crucial, and delayed treatment may lead to more serious consequences. However, existing massage chairs do not have the feature of real-time monitoring of stroke status.

[0007] 2. Existing massage chairs fail to take into account changes in patients and can only provide basic massages with a single force and intensity. They are not suitable for the physical constitution and condition of stroke patients and may pose a risk of accidental injury.

[0008] 3. Many massage chairs are also unable to upload real-time collected data to the cloud through a secure network, and identify risk factors and warning signs related to stroke through cloud data and analysis. Summary of the invention

[0009] In order to overcome the defects of the above-mentioned prior art, the present invention provides a stroke detection device based on pupil monitoring and control and a control method thereof, which can realize real-time monitoring of the physical state of stroke patients and early prediction of the risk of disease onset.

[0010] An embodiment of the present invention provides a stroke detection device based on pupil monitoring and control, comprising a device body, and further comprising: a pupil monitoring module and a main control module;

[0011] The pupil monitoring module is arranged on the device body and is used to collect the pupil status image of the user in real time;

[0012] The main control module is in communication with the pupil monitoring module and is used to determine the user's physical state based on the pupil state image.

[0013] Furthermore, the pupil monitoring module is specifically an infrared eye tracker, and the main control module is specifically a CPU314 module.

[0014] Furthermore, the device also includes a massage module;

[0015] The massage module is connected to the main control module and is used to adjust the massage intensity and massage position according to the control signal output by the main control module.

[0016] Furthermore, the device also includes an alarm module;

[0017] The alarm module is connected to the external preset cloud device for outputting an alarm signal to the external preset cloud device.

[0018] Another embodiment of the present invention provides a method for controlling a stroke detection device based on pupil monitoring and control, comprising the following steps:

[0019] During the user's use, the user's pupil status image is collected in real time;

[0020] Extracting user's pupil feature data according to the pupil state image;

[0021] The user's physical condition is determined based on the pupil feature data.

[0022] Furthermore, during the use of the device by the user, real-time collection of the user's pupil state image specifically includes:

[0023] The user's pupil status images are collected in real time through a preset pupil monitoring module, and all the pupil status images collected within a preset continuous time length are output.

[0024] Furthermore, extracting the user's pupil feature data according to the pupil state image specifically includes:

[0025] Extracting the user's pupil size data from all the pupil state images respectively;

[0026] The variation range of the pupil size is determined according to the pupil size data.

[0027] Preferably, after acquiring the pupil size data, the method further includes:

[0028] The pupil size data is denoised by using a preset low-pass filter and variational mode decomposition.

[0029] Further, determining the user's physical state according to the pupil feature data specifically includes:

[0030] When the variation ranges of the pupil sizes corresponding to the two pupils of the user are both smaller than the preset variation range threshold, it is determined that the user's physical condition is normal;

[0031] When the variation range of the pupil size corresponding to the user's pupil is greater than a preset variation range threshold, it is determined that the user is at risk of stroke.

[0032] Furthermore, the method further comprises:

[0033] Determining a user's pupil position according to the pupil state image, and determining a user's pupil focal point according to the pupil position;

[0034] The massage intensity at the pupil focal point is increased by a preset massage module.

[0035] Compared with the prior art, the beneficial effects of the present invention are:

[0036] By equipping the detection device with an integrated high-precision pupil monitoring sensor, the user's pupil size data can be collected in real time. By analyzing the changing trend of pupil size data, the user's physical condition can be judged, and the risk of stroke can be predicted in advance. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A schematic structural diagram of a stroke detection device based on pupil monitoring and control provided by one embodiment of the present invention.

[0038] Figure 2 A schematic flow chart of a method for controlling a stroke detection device based on pupil monitoring and control provided in another embodiment of the present invention. DETAILED DESCRIPTION

[0039] The drawings are for illustrative purposes only and should not be construed as limiting the present patent;

[0040] It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0041] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0042] Reference Figure 1 , is a schematic structural diagram of a stroke detection device based on pupil monitoring and control provided by an embodiment of the present invention, including a device body, and also including: a pupil monitoring module and a main control module;

[0043] The pupil monitoring module is arranged on the device body and is used to collect the pupil status image of the user in real time;

[0044] The main control module is in communication with the pupil monitoring module and is used to determine the user's physical state based on the pupil state image.

[0045] Furthermore, the pupil monitoring module is specifically an infrared eye tracker, and the main control module is specifically a CPU314 module.

[0046] In a preferred embodiment, the pupil monitoring module specifically uses an infrared eye tracker, which uses an infrared light source and a sensor to track eye movements, and is suitable for applications under various lighting conditions. The eye tracker can measure the size and reaction speed of the pupil in real time, help evaluate the health of the nervous system, and record the movement trajectory of the eye, analyze the visual focus and attention distribution. It is used to evaluate the status of stroke patients and the effect of their treatment. The eye tracker has the advantages of being able to provide accurate eye movement data, real-time monitoring, and facilitating dynamic evaluation. In addition, in addition to the infrared eye tracker, a camera-based eye tracker sensor can also be used to replace the infrared eye tracker sensor in this article. It can also capture eye images through a high-resolution camera and analyze eye movement data through computer vision technology.

[0047] The main control module is the control core of the detection device, responsible for coordinating the operation of each module, including receiving the output image of the pupil monitoring module. In this preferred embodiment, the main control module is specifically CPU314, which can be used in situations where high processing power and response speed are required. It has a built-in 128KB high-speed RAM, and its loading memory is a micro memory card with a maximum of 8MB, allowing projects to be stored in the CPU. It processes each binary instruction in approximately 60ns, and each floating point budget time is 0.59ns. The I / O module is 6 AC input modules, 4 AC output modules and 1 DC output module; it can be expanded to a maximum of 32 modules in a 4-row structure, 512 switch I / Os or 64 analog channels.

[0048] Furthermore, the device also includes a massage module;

[0049] The massage module is connected to the main control module and is used to adjust the massage intensity and massage position according to the control signal output by the main control module.

[0050] In a preferred embodiment, the main control module is also connected to the massage module of the detection device itself to control the massage strength and massage position of the massage module. The user can interact with the detection device through a preset display screen, including but not limited to selecting a massage mode, strength and temperature. After obtaining the interaction data, the main control module can control the massage module to massage the user according to the interaction data.

[0051] At the same time, the massage module also includes a number of sensors, which are used to collect the user's massage preference data during the user's use, and output the massage preference data to the main control module. The main control module can further analyze the massage preference data to improve the user's use experience.

[0052] In a specific embodiment, the detection device includes a pupil monitoring module, a communication module, a massage module and a main control module; wherein the communication module can be a Bluetooth or WiFi communication module.

[0053] After the user starts massaging, the pupil monitoring module is started synchronously, and the collected data is transmitted to the main control module through the communication module.

[0054] In addition, the main control module is also connected to the cloud for two-way communication. The main control module can obtain data for analyzing the user's physical condition from the cloud, and can also transmit the user's physical condition to the cloud.

[0055] Furthermore, the device also includes an alarm module;

[0056] The alarm module is communicatively connected to an external preset cloud device and is used to output an alarm signal to the external preset cloud device.

[0057] In a preferred embodiment, before determining the user's physical condition, it is necessary to normalize the average size of the user's pupils using the user's normal pupil state images pre-stored in a preset database, and then extract features from the denoised data. The corresponding pupil change range of the user when normal is calculated through machine learning and data mining methods, that is, to determine the preset change range threshold.

[0058] Therefore, when one or both pupils of the user are abnormally dilated or constricted, it can be determined that the user is at risk of stroke, and a warning signal is output to the preset external cloud device of the family or other guardians, so as to achieve early prediction of the risk of stroke. In addition, the massage module can be controlled by the main control module to reduce the massage intensity of the user to avoid injury to the user.

[0059] Reference Figure 2 , is a flow chart of a method for controlling a stroke detection device based on pupil monitoring and control provided by another embodiment of the present invention, comprising the following steps:

[0060] S1: During the user's use, the user's pupil status image is collected in real time;

[0061] S2: extracting the user's pupil feature data according to the pupil state image;

[0062] S3: Determine the user's physical condition based on the pupil feature data.

[0063] For step S1, specifically, collecting the user's pupil state image in real time during the user's use process specifically includes:

[0064] The user's pupil status images are collected in real time through a preset pupil monitoring module, and all the pupil status images collected within a preset continuous time length are output.

[0065] In a preferred embodiment, the preset continuous duration is not a fixed value, and the specific duration can be adjusted according to the actual situation of the user. After the acquisition is completed, all the pupil state images acquired are output to a preset main control module.

[0066] For step S2, specifically, extracting the user's pupil feature data according to the pupil state image specifically includes:

[0067] Extracting the user's pupil size data from all the pupil state images respectively;

[0068] The variation range of the pupil size is determined according to the pupil size data.

[0069] In a preferred embodiment, when a stroke occurs, changes in pupil size can reflect the state of the nervous system. A stroke generally affects one side of the brain, which may cause the pupil on the affected side to dilate while the other side is normal or constricted. In some cases, the pupils on both sides may become unequal in size or both dilate. In general, pupil changes are an important indicator for determining the severity and location of a stroke.

[0070] Therefore, it is necessary to analyze the collected pupil state image to obtain the user's pupil size variation range to further determine the user's physical state.

[0071] Preferably, after acquiring the pupil size data, the method further includes:

[0072] The pupil size data is denoised by using a preset low-pass filter and variational mode decomposition.

[0073] In a preferred embodiment, the pupil feature data belongs to a low-frequency signal, and a low-pass filter is first used to filter the multi-device noise. The low-pass filter has the function of passing low frequencies and blocking high frequencies, and the characteristics of the low-pass filter allow signals with frequencies below the set critical value to pass normally, while signals with frequencies above the set critical value are blocked and attenuated. Then, variational mode decomposition (VMD) is used for further denoising. VMD uses a completely non-recursive mode decomposition, and its main steps are as follows:

[0074] Suppose the signal to be decomposed is x(t), and we want to decompose it into multiple modes u k (t), each mode corresponds to a center frequency f k .

[0075] Define the energy function, the goal is to minimize the following energy function:

[0076]

[0077] Among them, α is the tuning parameter and K is the number of modes.

[0078] Introducing the Lagrange multiplier λ k To handle the orthogonality constraints of the modes, construct the Lagrangian function:

[0079]

[0080] By varying the Lagrangian function, we can obtain k (t) and λ k The partial differential equation is:

[0081] and

[0082] By solving these equations, expressions for the modes and their center frequencies are obtained.

[0083] Use optimization algorithms such as the alternating direction multiplier method to iteratively update the modal u k (t) and center frequency f k Until convergence.

[0084] Finally, all modes are added together to obtain the reconstructed signal and the denoising process is completed.

[0085] Preferably, the denoising method is not limited to VMD, and other signal denoising methods can be selected to denoise the pupil feature data according to actual conditions.

[0086] For step S3, specifically, determining the user's physical state according to the pupil feature data specifically includes:

[0087] When the variation ranges of the pupil sizes corresponding to the two pupils of the user are both smaller than the preset variation range threshold, it is determined that the user's physical condition is normal;

[0088] When the variation range of the pupil size corresponding to the user's pupil is greater than a preset variation range threshold, it is determined that the user is at risk of stroke.

[0089] Furthermore, the method further comprises:

[0090] Determining a user's pupil position according to the pupil state image, and determining a user's pupil focal point according to the pupil position;

[0091] The massage intensity at the pupil focal point is increased by a preset massage module.

[0092] In a preferred embodiment, the area where the patient's attention is focused (i.e., the pupil focal point) can also be determined by the position characteristics of the pupil, and then the main control center sends a control signal to the massage module so that the massage module controls the massage components of the corresponding area and focuses on massaging this part.

[0093] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the embodiments here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A stroke detection device based on pupil monitoring and control, comprising a device body, characterized in that: Also includes: Pupil monitoring module and main control module; The pupil monitoring module is arranged on the device body and is used to collect the pupil status image of the user in real time; The main control module is in communication with the pupil monitoring module and is used to determine the user's physical state based on the pupil state image.

2. The stroke detection device based on pupil monitoring and control as claimed in claim 1, characterized in that: The pupil monitoring module includes an infrared eye tracker, and the main control module includes a CPU314 module.

3. The stroke detection device based on pupil monitoring and control as claimed in claim 1, characterized in that: The device also includes a massage module; The massage module is connected to the main control module and is used to adjust the massage intensity and massage position according to the control signal output by the main control module.

4. The method for controlling a stroke detection device based on pupil monitoring and control as claimed in claim 1, characterized in that: The device also includes an alarm module; The alarm module is communicatively connected to an external preset cloud device and is used to output an alarm signal to the external preset cloud device.

5. A method for controlling a stroke detection device based on pupil monitoring and control, characterized in that: The following steps are involved: During the user's use, the user's pupil status image is collected in real time; Extracting user's pupil feature data according to the pupil state image; The user's physical condition is determined based on the pupil feature data.

6. The method for controlling a stroke detection device based on pupil monitoring and control as claimed in claim 5, characterized in that: The real-time collection of the user's pupil state image during the user's use process specifically includes: The user's pupil status images are collected in real time through a preset pupil monitoring module, and all the pupil status images collected within a preset continuous time length are output.

7. The method for controlling a stroke detection device based on pupil monitoring and control as claimed in claim 6, characterized in that: The extracting the user's pupil feature data according to the pupil state image specifically includes: Extracting the user's pupil size data from all the pupil state images respectively; The variation range of the pupil size is determined according to the pupil size data.

8. The method for controlling a stroke detection device based on pupil monitoring and control as claimed in claim 7, characterized in that: After acquiring the pupil size data, the method further includes: The pupil size data is denoised by using a preset low-pass filter and variational mode decomposition.

9. The method for controlling a stroke detection device based on pupil monitoring and control as claimed in claim 7, characterized in that: Determining the user's physical state according to the pupil feature data specifically includes: When the variation ranges of the pupil sizes corresponding to the two pupils of the user are both smaller than the preset variation range threshold, it is determined that the user's physical condition is normal; When the variation range of the pupil size corresponding to the user's pupil is greater than a preset variation range threshold, it is determined that the user is at risk of stroke.

10. The method for controlling a stroke detection device based on pupil monitoring and control as claimed in claim 5, characterized in that: The method further comprises: Determining a user's pupil position according to the pupil state image, and determining a user's pupil focal point according to the pupil position; The massage intensity at the pupil focal point is increased by a preset massage module.

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