Rehabilitation contents for cognitive impairment based on health care system

Abstract

The present invention relates to a health management system based on cognitive impairment rehabilitation content, and more specifically, to a health management system based on cognitive impairment rehabilitation content that identifies the degree and grade of individual cognitive impairment based on individual biosignals and provides personalized cognitive impairment rehabilitation content corresponding thereto, thereby moving away from conventional uniform educational methods and providing personalized content optimized for each individual, which not only enhances interest and immersion in cognitive impairment rehabilitation content but also further improves the efficiency of cognitive function rehabilitation.

Description

Technology Field

[0001] The present invention relates to a health management system based on cognitive impairment rehabilitation content that identifies the degree and grade of individual cognitive impairment based on individual biosignals and provides personalized cognitive impairment rehabilitation content corresponding thereto, thereby moving away from conventional uniform educational methods and providing personalized content optimized for each individual, which not only enhances interest and immersion in cognitive impairment rehabilitation content but also further improves the efficiency of cognitive function rehabilitation. Background Technology

[0002] Generally, cognitive impairment refers to a state in which memory, attention, language ability, visuospatial ability, and judgment are impaired. The severity varies from very mild to severe, and in cases of severe cognitive dysfunction, it can interfere with daily life and social activities.

[0003] In other words, cognitive impairment is a brain disorder characterized by impairment of overall cognitive function while conscious, usually caused by chronic or progressive brain disease, and is a syndrome in which impairment occurs in multiple higher cerebral functions such as memory, thinking, understanding, calculation, learning, and language judgment.

[0004] On the other hand, mild cognitive impairment refers to a condition where cognitive function, particularly memory, is lower than that of the same age group, but the ability to perform daily activities is preserved. This can be considered an intermediate stage between normal and severe cognitive impairment; as the earliest stage detectable through testing, it is known to maximize the effectiveness of treatment.

[0005] Recently, various programs such as puzzle games, drawing, and storytelling to activate the brain have been proposed as measures to prevent and treat cognitive impairment-related diseases.

[0006] However, despite these efforts, conventional cognitive training programs aimed at preventing and treating various cognitive impairments are failing to generate interest among patients and are mostly conducted using uniform educational methods, so they are not achieving effective results. Prior art literature

[0007] Patent Document 1: Korean Published Patent No. 10-2019-0074563 The problem to be solved

[0008] The present invention aims to solve the above-mentioned problems by identifying the degree and grade of individual cognitive impairment based on individual biosignals and providing personalized cognitive impairment rehabilitation content corresponding thereto, thereby moving away from conventional uniform educational methods and providing personalized content optimized for each individual. As a result, it is possible to not only improve interest and immersion in cognitive impairment rehabilitation content but also further enhance the efficiency of cognitive function rehabilitation.

[0009] The problems that the present invention aims to solve are not limited to those mentioned above, and other problems that the present invention aims to solve that are not mentioned herein will be clearly understood by those skilled in the art to which the present invention belongs from the description below. means of solving the problem

[0010] The present invention comprises: a brainwave signal measuring unit (100) for measuring a user's brainwave signal; a state judgment unit (200) for receiving a brainwave signal measured by the brainwave signal measuring unit (100) and determining the user's cognitive ability based on the received brainwave signal; and a health management server (300) for generating cognitive impairment rehabilitation content based on information determined by the state judgment unit (200) and providing it to a user terminal (160). The brainwave signal measuring unit (100) comprises: a brainwave measuring means (110) for measuring a user's brainwave signal; a brainwave signal receiving unit (120) for receiving a brainwave signal from the brainwave measuring means (110); a brainwave signal processing unit (130) for supplying the brainwave signal received from the brainwave signal receiving unit (120) to a brainwave signal storage unit (140); and a brainwave signal storage unit (140) for receiving the brainwave signal supplied from the brainwave signal processing unit (130), converting it into data, and storing it. and a first communication unit (150) that communicates with the state determination unit (200) and provides the brainwave signal stored in the brainwave signal storage unit (140) to the state determination unit (200); wherein the state determination unit (200) includes: a second communication unit (210) that communicates with the first communication unit (150) and receives the brainwave signal; a determination unit (220) that determines the user's cognitive ability based on the received brainwave signal; and a third communication unit (230) that communicates with the health management server (300) and provides the user cognitive ability information determined by the determination unit (220) to the health management server (300); and wherein the health management server (300) includes a fourth communication unit (310) that communicates with the third communication unit (230) of the state determination unit (200) and receives the user cognitive ability information determined by the state determination unit (200); A content generation unit (320) that generates cognitive impairment rehabilitation content based on the received cognitive ability information and according to the content generation classification information for each classified state information; and a fifth communication unit (330) that provides the generated cognitive impairment rehabilitation content to a user terminal (160);A health management system based on cognitive impairment rehabilitation content, characterized by including [...], is used as a means of solving the problem.

[0011] Here, the brainwave measuring means (110) may include: a body part (111) formed in a semicircular shape to contact the user's forehead; a band fastening part (112) provided on both sides of the body part (111) to allow a band member to be fastened to secure the body part (111) to the head; and a plurality of brainwave sensors (113) attached at equal intervals in a row on the forehead contact area inside the body part (111).

[0012] And the above judgment unit (220) may include: a learning module (221) that stores and learns brainwave signal information measured by the brainwave signal measuring unit (100) for a certain period; and a judgment module (222) that determines the user's cognitive ability by comparing the brainwave signal information learned by the learning module (221) with the brainwave signal information generated in real time by the brainwave signal measuring unit (100).

[0013] In addition, the judgment module (222) may include: a brainwave signal data storage unit (222-1) in which learned brainwave signal information and real-time generated brainwave signal information are stored; a change value calculation unit (222-2) that calculates a change value by substituting the real-time generated brainwave signal information into the learned brainwave signal information; and a state derivation unit (222-3) that determines the user's cognitive ability by grade by substituting the change value into previously learned state classification information.

[0014] Meanwhile, the above-mentioned cognitive impairment rehabilitation content includes spatial perception enhancement content, memory enhancement content, attention enhancement content, association ability enhancement content, numerical ability enhancement content, and drawing content that are stored in the above-mentioned content generation unit (320), and each of the above-mentioned content may have multiple difficulty levels according to the cognitive ability grade.

[0015] In addition, the brainwave measuring means (110) is equipped with a control unit (111a) that transmits a signal sensed by the brainwave sensor (113) inside the body part (111) to a brainwave signal receiving unit (120). The control unit (111a) filters the brainwave signal acquired by the brainwave sensor (113) into an effective range using a bandpass filter, and if electromyography noise generated by the movement of the user's neck and face exceeds a preset standard and is mixed into the brainwave signal information, it treats the entire brainwave signal information for that time as noise and deletes it; and if the brainwave sensor (113) is temporarily detached or has poor contact due to the user's movement, it interprets it as temporary detachment and treats the entire brainwave signal information for that time as noise and deletes it. It also includes a noise removal module (111a-1); and an amplification module (111a-2) that amplifies the brainwave signal from which noise has been removed through the noise removal module (111a-1). and may include an ADC module (111a-3) that converts the brainwave signal amplified through the amplification module (111a-2) into a digital brainwave signal.

[0016] Additionally, the body part (111) is formed by using a protrusion (111b) and an air flow path (111c) in an alternating manner in the direction of skin contact, and the protrusion (111b) may be formed with a height (L) of 1 to 5 mm.

[0017] Additionally, the body part (111) has a silicone pad attached in the direction of skin contact, and the pad has a protrusion (111b) and an air flow path (111c) formed in an alternating manner in the direction of skin contact, and the protrusion (111b) is formed with a height (L) of 1 to 5 mm, and a plurality of air cells (111b-1) may be formed inside the protrusion (111b). Effects of the invention

[0018] The present invention identifies the degree and grade of individual cognitive impairment based on individual biosignals and provides personalized cognitive impairment rehabilitation content corresponding thereto, thereby moving away from conventional uniform educational methods and providing personalized content optimized for each individual. As a result, it has the effect of not only improving interest and immersion in cognitive impairment rehabilitation content but also further enhancing the efficiency of cognitive function rehabilitation. Brief explanation of the drawing

[0019] FIG. 1 is a block diagram showing the overall configuration of a health management system based on cognitive impairment rehabilitation content according to the present invention. FIG. 2 is a block diagram illustrating a health management system based on cognitive impairment rehabilitation content according to the present invention. FIG. 3 is a block diagram embodying a brainwave measurement means according to the present invention. FIG. 4 is a block diagram illustrating a control unit according to the present invention. FIG. 5 is a cross-sectional view illustrating a body portion according to the present invention. FIG. 6 is a cross-sectional view illustrating a projection according to the present invention. FIG. 7 is a block diagram embodying a judgment unit according to the present invention. FIG. 8 is a block diagram embodying a judgment module according to the present invention. FIG. 9 is a drawing showing examples of each content according to the present invention. Specific details for implementing the invention

[0020] The advantages and features of the embodiments of the present invention, and the methods for achieving them, will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below but may be implemented in various different forms. These embodiments are provided merely to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention, and the present invention is defined only by the scope of the claims. Throughout the specification, the same reference numerals refer to the same components.

[0021] In describing the embodiments of the present invention, specific descriptions of known functions or configurations will be omitted if it is determined that such detailed descriptions could unnecessarily obscure the essence of the invention. Furthermore, the terms described below are defined in consideration of their functions in the embodiments of the present invention, and these definitions may vary depending on the intentions or practices of the user or operator. Therefore, such definitions should be based on the content throughout this specification.

[0022] Hereinafter, preferred embodiments of the present invention will be described with reference to the attached drawings.

[0023] FIG. 1 is a block diagram showing the overall configuration of a health management system based on cognitive impairment rehabilitation content according to the present invention, FIG. 2 is a block diagram showing the health management system based on cognitive impairment rehabilitation content according to the present invention, FIG. 3 is a block diagram showing the brainwave measurement means according to the present invention, FIG. 4 is a block diagram showing the control unit according to the present invention, FIG. 5 is a cross-sectional view showing the body unit according to the present invention, FIG. 6 is a cross-sectional view showing the protrusion unit according to the present invention, FIG. 7 is a block diagram showing the judgment unit according to the present invention, FIG. 8 is a block diagram showing the judgment module according to the present invention, and FIG. 9 is a diagram showing examples of each content according to the present invention.

[0024] Referring to FIGS. 1 to 9, the cognitive impairment rehabilitation content-based health management system according to the present invention includes a brainwave signal measuring unit (100), a state determination unit (200), and a health management server (300).

[0025] The above brainwave signal measuring unit (100) is a means for measuring a user's brainwave signal and includes a brainwave measuring means (110), a brainwave signal receiving unit (120), a brainwave signal processing unit (130), a brainwave signal storage unit (140), and a first communication unit (150). More specifically, the brainwave signal of the user is measured at the brainwave measuring means (110), and after the brainwave signal from the brainwave measuring means (110) is received at the brainwave signal receiving unit (120), the brainwave signal received at the brainwave signal receiving unit (120) is supplied to the brainwave signal storage unit (140) through the brainwave signal processing unit (130). Then, the brainwave signal supplied from the brainwave signal processing unit (130) is received, converted into data, and stored in the brainwave signal storage unit (140), and the brainwave signal stored in the brainwave signal storage unit (140) is provided to the state determination unit (200) through the first communication unit (150) which communicates with the state determination unit (200).

[0026] Here, the brainwave measuring means (110) may be composed of a body part (111) formed in a semicircular shape to contact the user's forehead, a band fastening part (112) provided on both sides of the body part (111) to allow a band member to be fastened to secure the body part (111) to the head, and a plurality of brainwave sensors (113) attached at equal intervals in a row on the forehead contact area inside the body part (111).

[0027] More specifically, the brainwave measuring means (110) is equipped with a control unit (111a) that transmits a signal sensed by the brainwave sensor (113) to a brainwave signal receiving unit (120) inside the body part (111), and the control unit (111a) includes a noise removal module (111a-1), an amplification module (111a-2), and an ADC module (111a-3).

[0028] More specifically, the noise removal module (111a-1) is intended to improve reliability by removing noise that may be included in the brainwave signal. It filters the brainwave acquired by the brainwave sensor (113) into an effective range using a bandpass filter. If electromyography noise generated by the user's neck and face movements exceeds a preset standard and is mixed into the brainwave signal information, the entire brainwave signal information for that time is treated as noise and deleted. Additionally, if the brainwave sensor (113) is temporarily detached or has poor contact due to the user's movement, it is interpreted as temporary detachment, and the entire brainwave signal information for that time is treated as noise and deleted.

[0029] Then, the brainwave signal from which noise has been removed through the noise removal module (111a-1) is amplified through the amplification module (111a-2) and then converted into a digital brainwave signal through the ADC module (Analog Digital Converter, 111a-3) and transmitted to the brainwave signal receiving unit (120).

[0030] Meanwhile, the above body part (111) has a silicone pad attached in the direction of skin contact to improve the wearing comfort.

[0031] At this time, when the above-mentioned brainwave measuring means (110) is worn for a long time, the wearing position may shift or discomfort may occur due to sweat, etc., so it is necessary to provide breathability.

[0032] Accordingly, protrusions (111b) and air flow paths (111c) are formed in an alternating manner on the surface of the silicone pad in the direction of skin contact, thereby improving comfort during wear through air flow.

[0033] To this end, it is preferable that the above-mentioned protrusion (111b) be formed with a height (L) of 1 to 5 mm. If the height (L) is less than 1 mm, there is a concern that the breathability effect may be insufficient, and if it exceeds 5 mm, there is a concern that the wearing comfort may be reduced.

[0034] Meanwhile, a plurality of air cells (111b-1) are formed inside the above-mentioned protrusion (111b), thereby physically lowering the hardness of the protrusion (111b) and further improving the wearing comfort.

[0035] Here, to form the air cell (111b-1), 1 to 4 parts by weight of dicumyl peroxide, a crosslinking agent, and azodicarbonamide, a foaming agent, can be added to 100 parts by weight of silicone resin, respectively. If the above content is exceeded, the foaming efficiency may decrease, and there is a concern that the air cell (111b-1) may not be properly formed.

[0036] The above state determination unit (200) receives a brainwave signal measured by the brainwave signal measurement unit (100) and determines the user's cognitive ability based on the received brainwave signal, and includes a second communication unit (210), a determination unit (220), and a third communication unit (230). More specifically, it receives a brainwave signal through the second communication unit (210) which communicates with the first communication unit (150), determines the user's cognitive ability in the determination unit (220) based on the received brainwave signal, and provides the user cognitive ability information determined by the determination unit (220) to the health management server (300) through the third communication unit (230) which communicates with the health management server (300).

[0037] Meanwhile, the judgment unit (220) determines the user's cognitive ability through the learning module (221) and the judgment module (222). More specifically, it stores brainwave signal information measured by the brainwave signal measuring unit (100) for a certain period and learns through the learning module (221), and then compares the brainwave signal information learned by the learning module (221) with the brainwave signal information generated in real time by the brainwave signal measuring unit (100) in the judgment module (222) to determine the user's cognitive ability.

[0038] The above judgment module (222) includes a brainwave signal data storage unit (222-1), a change value calculation unit (222-2), and a state derivation unit (222-3). More specifically, the learned brainwave signal information and the real-time generated brainwave signal information are stored through the brainwave signal data storage unit (222-1), and the real-time generated brainwave signal information is substituted into the learned brainwave signal information in the change value calculation unit (222-2) to calculate a change value. Then, the change value is substituted into the previously learned state classification information to determine the user's cognitive ability by grade in the state derivation unit (222-3).

[0039] Here, the classification information is information that is pre-learned to classify a state into A state when the range of the change value is A according to the change value, for example, when the change value is 5, it refers to information that classifies a state such as 'user cognitive ability grade B'.

[0040] Meanwhile, the learning module (221) and the judgment module (222) can use known Artificial Intelligence (AI) modules. That is, it is possible to build an AIoT (Artificial Intelligence of Things) based system through the fusion of the various sensors and the AI ​​modules.

[0041] Here, the artificial intelligence module may be a CNN (Convolutional Neural Networks) model that includes an Inception module in a GAP (Global Average Pooling) layer.

[0042] The artificial intelligence module can produce desired data by learning the weights of multiple inputs through deep learning. In addition, various models such as RNN (Recurrent Neural Network), DNN (Deep Neural Network), and DRNN (Dynamic Recurrent Neural Network) can be utilized as artificial intelligence network models for this learning.

[0043] Here, RNN is a deep learning technique that considers current and past data simultaneously, and a Recurrent Neural Network (RNN) represents a neural network in which the connections between units constituting the artificial neural network form a directed cycle. Furthermore, various methods can be used for structures that can construct a Recurrent Neural Network (RNN); for example, representative examples include the Fully Recurrent Network, Hopfield Network, Elman Network, Echo State Network (ESN), Long Short-Term Memory Network (LSTM), Bi-directional RNN, Continuous-Time RNN (CTRNN), Hierarchical RNN, and Second-Order RNN. Additionally, methods such as Gradient Descent, Hessian Free Optimization, and Global Optimization Method can be used to train the Recurrent Neural Network (RNN).

[0044] Furthermore, conventional CNNs suffer from the problem of high processing speed and computational load. Since the present invention requires iterative computation using immediate additional data, a lighter algorithm is necessary. Therefore, Global Average Pooling (GAP) layers and Inception modules can be applied to the CNN model. Generally, CNNs stack many convolution layers, resulting in a large number of filters. A large number of filters implies that feature maps accumulate accordingly. In other words, it means that the dimensionality of the CNN is very high.

[0045] Handling high dimensions requires a large number of parameters capable of handling them. However, if the number of parameters becomes too large, problems such as overfitting can occur during training. Therefore, a method is needed to reduce dimensionality by decreasing the number of parameters used in the filters. The layer in CNNs that performs this role is the pooling layer.

[0046] In this case, GAP solves this problem by extracting the average from each feature and moving it directly to the classification layer. Consequently, because it directly associates features with categories while preserving the spatial information of the previous feature maps, it can generate a confidence map (= feature map) that indicates which parts of the obtained feature maps played a major role in classifying them into a specific class. Since it does not require separate parameter optimization, it has the advantage of low computational load and the ability to prevent overfitting.

[0047] The Inception architecture is a form in which a small neural network is added inside a neural network, and the small neural network inside is called the Inception module. The Inception module can reduce the feature map through 1x1 convolution, making it effective in terms of processing speed and computational load.

[0048] Accordingly, the above artificial intelligence module may apply a CNN model including an Inception module to the GAP (Global Average Pooling) layer.

[0049] In addition, each communication unit described above or below may utilize Bluetooth, ZigBee, Ultra WideBand (UWB), or Wi-Fi.

[0050] The above health management server (300) is a means for generating cognitive impairment rehabilitation content based on information determined by the state determination unit (200) and providing it to a user terminal (160), and includes a fourth communication unit (310), a content generation unit (320), and a fifth communication unit (330), more specifically

[0051] A fourth communication unit (310) communicating with a third communication unit (230) of the above-mentioned state determination unit (200) receives user cognitive ability information determined by the state determination unit (200), and based on the received cognitive ability information, a content creation unit (320) creates cognitive impairment rehabilitation content according to the content creation classification information for each classified state information, and provides the created cognitive impairment rehabilitation content to a user terminal (160) through a fifth communication unit (330).

[0052] Here, the content creation classification information based on the classified state information means information classified to display content of difficulty level A when the state is A according to the state information, for example, to create and provide 'spatial perception enhancement content of difficulty level 5' when the state information is 'user cognitive ability grade B'.

[0053] To this end, the cognitive impairment rehabilitation content includes spatial perception enhancement content, memory enhancement content, attention enhancement content, association ability enhancement content, numerical ability enhancement content, and drawing content stored in the content generation unit (320), and each of the content has multiple difficulty levels according to the cognitive ability grade.

[0054] In other words, the present invention identifies the degree and grade of individual cognitive impairment based on individual biosignals as described above and provides personalized cognitive impairment rehabilitation content corresponding thereto, thereby moving away from conventional uniform educational methods and providing personalized content optimized for each individual. As a result, it is possible to not only improve interest and immersion in cognitive impairment rehabilitation content but also further enhance the efficiency of cognitive function rehabilitation.

[0055] The present invention is not limited to the embodiments described above and has a diverse scope of application. Furthermore, it is understood that anyone with ordinary knowledge in the field to which the present invention pertains can make various modifications without departing from the essence of the invention as claimed in the claims. Explanation of the symbols

[0056] 100 : Brainwave signal measurement unit 110: Brainwave measuring means 111 : Body 111a : Control unit 111a-1 : Noise removal module 111a-2 : Amplification Module 111a-3: ADC Module 111b : projection 111b-1 : Air cell 111c: Air flow path 112 : Band fastening part 113 : Brainwave sensor 120 : Brainwave signal receiver 130 : Brainwave signal processing unit 140 : Brainwave signal storage unit 150 : 1st Communications Unit 160 : User terminal 200 : State determination unit 210 : 2nd Communications Unit 220 : Judgment section 221 : Learning Module 222 : Judgment Module 222-1 : Brainwave signal data storage unit 222-2 : Change Value Calculation Unit 222-3 : State Derivation Section 230 : 3rd Communications Division 300 : Health Management Server 310: 4th Communications Division 320 : Content Creation Section 330 : 5th Communications Division

Claims

Claim 1 A brainwave signal measuring unit (100) for measuring a user's brainwave signal; a state judgment unit (200) for receiving a brainwave signal measured by the brainwave signal measuring unit (100) and determining the user's cognitive ability based on the received brainwave signal; and a health management server (300) for generating cognitive impairment rehabilitation content based on information determined by the state judgment unit (200) and providing it to a user terminal (160); wherein the brainwave signal measuring unit (100) comprises: a brainwave measuring means (110) for measuring a user's brainwave signal; a brainwave signal receiving unit (120) for receiving a brainwave signal from the brainwave measuring means (110); a brainwave signal processing unit (130) for supplying the brainwave signal received from the brainwave signal receiving unit (120) to a brainwave signal storage unit (140); and a brainwave signal storage unit (140) for receiving the brainwave signal supplied from the brainwave signal processing unit (130), converting it into data, and storing it. and a first communication unit (150) that communicates with the state determination unit (200) and provides the brainwave signal stored in the brainwave signal storage unit (140) to the state determination unit (200); wherein the state determination unit (200) includes: a second communication unit (210) that communicates with the first communication unit (150) and receives the brainwave signal; and a determination unit (220) that determines the user's cognitive ability based on the received brainwave signal. The system includes a third communication unit (230) that communicates with the health management server (300) and provides user cognitive ability information determined by the judgment unit (220) to the health management server (300); wherein the health management server (300) includes: a fourth communication unit (310) that communicates with the third communication unit (230) of the state judgment unit (200) and receives user cognitive ability information determined by the state judgment unit (200); a content creation unit (320) that creates cognitive impairment rehabilitation content according to content creation classification information for each pre-classified state information based on the received cognitive ability information; and a fifth communication unit (330) that provides the created cognitive impairment rehabilitation content to a user terminal (160); and wherein the brainwave measurement means (110) includes a body part (111) formed in a semicircular shape to contact the user's forehead;A band fastening part (112) provided on both sides of the body part (111) to allow a band member to be fastened for fixing the body part (111) to the head; and a plurality of brainwave sensors (113) attached at equal intervals in a row on the forehead contact area inside the body part (111); wherein the judgment part (220) includes a learning module (221) that stores and learns brainwave signal information measured by the brainwave signal measuring part (100) for a certain period; The method includes a judgment module (222) that determines the user's cognitive ability by comparing the brainwave signal information learned by the learning module (221) with the brainwave signal information generated in real time by the brainwave signal measurement unit (100); wherein the judgment module (222) comprises: a brainwave signal data storage unit (222-1) in which learned brainwave signal information and real-time generated brainwave signal information are stored; a change value calculation unit (222-2) that calculates a change value by substituting the real-time generated brainwave signal information into the learned brainwave signal information; and a state derivation unit (222-3) that determines the user's cognitive ability by grade by substituting the change value into previously learned state classification information.The cognitive impairment rehabilitation content includes spatial perception enhancement content, memory enhancement content, attention enhancement content, association ability enhancement content, numerical ability enhancement content, and drawing content stored in the content generation unit (320), and each of the content has multiple difficulty levels according to cognitive ability grades, and the brainwave measurement means (110) is equipped with a control unit (111a) that transmits a signal sensed by the brainwave sensor (113) inside the body unit (111) to the brainwave signal receiving unit (120), and the control unit (111a) filters the brainwave signal acquired by the brainwave sensor (113) into an effective range using a bandpass filter, and if electromyography noise generated due to the movement of the user's neck and face exceeds a preset standard and is mixed into the brainwave signal information, the entire brainwave signal information for that time is treated as noise and deleted, and if the brainwave sensor (113) is temporarily detached or contact is poor due to the user's movement, it is interpreted as temporary detachment and the corresponding A health management system based on cognitive impairment rehabilitation content, comprising: a noise removal module (111a-1) that treats and deletes the entire brainwave signal information of time as noise; an amplification module (111a-2) that amplifies the brainwave signal from which noise has been removed through the noise removal module (111a-1); and an ADC module (111a-3) that converts the brainwave signal amplified through the amplification module (111a-2) into a digital brainwave signal; wherein the body part (111) has a silicone pad attached in the direction of skin contact, and the pad has a protrusion (111b) and an air flow path (111c) formed in an alternating manner in the direction of skin contact, and the protrusion (111b) is formed with a height (L) of 1 to 5 mm, and a plurality of air cells (111b-1) are formed inside the protrusion (111b). 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