Memory training method and device, electronic equipment and computer readable storage medium

Abstract

The application discloses a memory training method and device, electronic equipment and computer readable storage medium, and relates to the technical field of intelligent medical treatment. The specific implementation manner comprises the following steps: acquiring the memory condition of a target object; acquiring training content matched with the memory condition from multiple training contents according to the memory condition, wherein the training content comprises audio content and video content; showing the acquired training content to the target object for memory training; acquiring interaction data of the target object and the acquired training content during the memory training process, and acquiring brain hot zone imaging data of the target object during the interaction; and determining the memory improvement result of the target object according to the interaction data and the brain hot zone imaging data. The scheme is beneficial to improving the effect of memory training and the accuracy of the memory improvement result.

Description

Technical Field

[0001] This application relates to the field of computer technology, specifically to the field of smart healthcare technology, and more particularly to a memory training method, device, electronic device, and computer-readable storage medium. Background Technology

[0002] Currently, methods for improving patients' memory rely on training with fixed props and images, and the results are determined through manual observation. This approach fails to meet the diverse needs of different patients, resulting in inappropriate training content and impacting the effectiveness of memory improvement. Furthermore, the reliance on manual observation cannot eliminate the influence of individual differences in experience, making it impossible to accurately and uniformly determine the results, leading to inaccurate and unstable outcomes. Summary of the Invention

[0003] To address the technical problems of poor memory improvement effects and inaccurate memory improvement results in existing technologies, a memory training method, device, electronic device, and computer-readable storage medium are provided.

[0004] According to the first aspect, a memory training method is provided, including:

[0005] Obtain the memory status of the target object;

[0006] Based on the memory status, training content matching the memory status is obtained from multiple training contents, wherein the training content includes audio content and video content;

[0007] The acquired training content is displayed to the target object to train memory skills;

[0008] During the memory training process, interaction data between the target object and the acquired training content is obtained, and brain thermal imaging data of the target object during the interaction is obtained.

[0009] Based on the interaction data and the brain thermal imaging data, the memory improvement results of the target subject are determined.

[0010] According to the second aspect, a memory training device is provided, comprising:

[0011] The memory status acquisition module is used to acquire the memory status of the target object;

[0012] The training content determination module is used to obtain training content that matches the memory status from multiple training contents based on the memory status, wherein the training content includes audio content and video content;

[0013] The display module is used to display the acquired training content to the target object for memory training.

[0014] The data acquisition module is used to acquire interaction data between the target object and the acquired training content during the memory training process, and to acquire brain thermal imaging data of the target object during the interaction.

[0015] The memory improvement result determination module is used to determine the memory improvement result of the target subject based on the interaction data and the brain thermal imaging data.

[0016] According to a third aspect, an electronic device is provided, comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any embodiment of the memory training method.

[0017] According to a fourth aspect, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the method as described in any embodiment of the memory training method.

[0018] According to the solution proposed in this application, training content matching the target's memory ability is selected from multiple training materials based on the target's memory ability. This allows for flexible and personalized selection of training content that suits each target's memory ability, enabling flexible and personalized memory training methods and thus improving the effectiveness of memory training. Simultaneously, during the memory training process, interaction data between the target and the acquired training content is acquired, along with brain thermal imaging data of the target during the interaction. Based on the interaction data and the brain thermal imaging data, the memory improvement result of the target is determined. Since the interaction data and the brain thermal imaging data reflect the target's mental state and cognitive memory ability during responses from different perspectives, and the memory improvement result is determined based on factual data, compared with the existing method of manual observation, the memory improvement result can be determined objectively and with a unified standard, thereby improving the accuracy and stability of the memory improvement result. Attached Figure Description

[0019] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0020] Figure 1 This is an exemplary system architecture diagram in which some embodiments of this application can be applied;

[0021] Figure 2This is a flowchart of one embodiment of the memory training method according to this application;

[0022] Figure 3 This is a flowchart of yet another embodiment of the memory training method according to this application;

[0023] Figure 4 This is a schematic diagram of an application scenario of the memory training method according to this application;

[0024] Figure 5 This is a schematic diagram of the structure of one embodiment of the memory training device according to this application;

[0025] Figure 6 This is a block diagram of an electronic device used to implement the memory training method of the embodiments of this application. Detailed Implementation

[0026] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of this application, including various details to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0027] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0028] Figure 1 An exemplary system architecture 100 is shown, in which embodiments of the memory training method or memory training device of this application can be applied.

[0029] like Figure 1 As shown, system architecture 100 may include terminal devices 101, 102, and 103, a network 104, and a server 105. Network 104 serves as the medium for providing communication links between terminal devices 101, 102, and 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0030] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as video applications, live streaming applications, instant messaging tools, email clients, social media platform software, etc.

[0031] The terminal devices 101, 102, and 103 here can be either hardware or software. When terminal devices 101, 102, and 103 are hardware, they can be various electronic devices with displays, including but not limited to smartphones, tablets, e-book readers, laptops, and desktop computers. When terminal devices 101, 102, and 103 are software, they can be installed in the electronic devices listed above. They can be implemented as multiple software programs or software modules (e.g., multiple software programs or software modules used to provide distributed services) or as a single software program or software module. No specific limitations are imposed here.

[0032] Server 105 can be a server that provides various services, such as a backend server that supports terminal devices 101, 102, and 103. The backend server can analyze and process the received interactive data, brain thermal imaging data, and other data, and feed back the processing results (such as memory improvement results) to the terminal devices.

[0033] It should be noted that the memory training method provided in this application embodiment can be executed by server 105 or terminal devices 101, 102, 103, and correspondingly, the memory training device can be set in server 105 or terminal devices 101, 102, 103.

[0034] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0035] Continue to refer to Figure 2 The diagram illustrates a flow 200 of an embodiment of the memory training method according to this application. The memory training method includes the following steps:

[0036] Step 201: Obtain the target object's memory status;

[0037] Step 202: Based on the memory status, obtain training content that matches the memory status from multiple training contents, wherein the training content includes audio content and video content;

[0038] Step 203: Show the acquired training content to the target object for memory training;

[0039] Step 204: During the memory training process, acquire the interaction data between the target object and the acquired training content, and acquire the brain thermal imaging data of the target object during the interaction.

[0040] Step 205: Determine the memory improvement result of the target subject based on the interaction data and the brain thermal imaging data.

[0041] In this embodiment, a method is proposed to select training content that matches the target subject's memory ability from multiple training options. This allows for flexible and personalized selection of training content tailored to each target subject's memory capacity, enabling flexible and personalized memory training methods and thus improving the effectiveness of memory training. Simultaneously, during the memory training process, interaction data between the target subject and the acquired training content is acquired, along with brain thermal imaging data of the target subject during the interaction. Based on the interaction data and the brain thermal imaging data, the memory improvement result of the target subject is determined. Since the interaction data and the brain thermal imaging data reflect the activity state of brain functional areas and cognitive memory status of the target subject during responses from different perspectives, and the memory improvement result is determined based on factual data, compared with the existing method of manual observation, the memory improvement result can be determined objectively and with a unified standard, thereby improving the accuracy and stability of the memory improvement result.

[0042] In some optional implementations of this embodiment, in order to achieve a more intuitive memory training effect on the target object, the training content may include content in the form of audio and video content, so as to provide the target object with more intuitive visual and auditory information.

[0043] In some optional implementations of this embodiment, to meet the memory training needs of different target groups, the training content can be of different durations, such as 10 minutes, 20 minutes, and 30 minutes. Target groups with greater memory improvement difficulty require longer training content. The difficulty of memory improvement can be determined based on the specific memory situation of the target group. For example, if the difficulty includes different individual levels such as easy, medium, and difficult, then the easy level can correspond to a 10-minute training content program, the medium level to a 20-minute program, and the difficult level to a 30-minute program. Different training content can also correspond to different playback frequencies and other information.

[0044] In some optional implementations of this embodiment, the training content may include different categories of content, such as common sense (e.g., content related to tools, items, fruits, food, etc. in daily life), sports, numbers, etc.

[0045] In some optional implementations of this embodiment, the target object can be any person who needs to train and improve their memory, such as a person with cognitive impairment and memory problems caused by age, disease, brain injury or other reasons.

[0046] In some optional implementations of this embodiment, to improve the effectiveness of memory training, the training content may include interactive content with the target object. This allows for interaction with the target object during the process of presenting the acquired training content for memory training. This interaction can improve the target object's interest and attention to the training content, increase their participation, and stimulate their mental activity for better memory training. For example, the interactive content may involve asking the target object questions based on the displayed training content (e.g., asking for the names and uses of displayed items, tools, etc.), and collecting the target object's responses (e.g., voice messages, text messages, etc.).

[0047] In some optional implementations of this embodiment, in order to further improve the training effect, it is also proposed to display the training content using colors that the target object's vision is good at recognizing. For example, the vision of the target object is obtained; based on the vision, the color that the target object's eyes can recognize is determined; and the obtained training content is displayed to the target object using the color to perform memory training.

[0048] In some optional implementations of this embodiment, the aforementioned visual acuity can be determined based on information such as age, aging or degeneration of eye function. For example, different visual acuity conditions corresponding to different age groups can be determined based on existing relevant data, and different aging or degeneration of eye function corresponds to different visual acuity conditions. Then, based on existing relevant data, colors that different visual acuity conditions are good at and easy to recognize can be determined, and the determined colors can be used to display training content.

[0049] In some optional implementations of this embodiment, in order to accurately determine the effect of memory training and improvement, it is proposed to acquire interaction data between the target object and the acquired training content during the memory training process, and acquire brain thermal imaging data of the target object during the interaction. Then, based on the interaction data and the brain thermal imaging data, the memory improvement result of the target object can be determined. This allows the effect of memory training and improvement to be evaluated based on the memory improvement result, and provides data basis for further adjusting the training content and timely understanding of the target object's memory status.

[0050] In some optional implementations of this embodiment, to further improve the accuracy and efficiency of assessing memory improvement results, this embodiment obtains interaction data between the target object and the acquired training content in the following manner:

[0051] During the memory training process, the voice data of the target object answering questions about the acquired training content is acquired;

[0052] A speech recognition algorithm is used to determine the answer given by the target object from the speech data;

[0053] Determine whether the answer given by the target object is correct. If yes, record the first identifier; otherwise, record the second identifier.

[0054] For example, the target's answer is compared with a pre-stored answer to determine whether the target's answer is correct. If it is correct, the target's answer is recorded as a first identifier; if it is incorrect, the target's answer is recorded as a second identifier. The first and second identifiers can be any form of identifier (such as numbers, letters, characters, etc.) that can distinguish between the two cases of whether the answer is correct or not. For example, the number 1 can be used to represent the first identifier and the number 0 can be used to represent the second identifier.

[0055] In some optional implementations of this embodiment, in order to further improve the accuracy of the assessment of memory improvement results, in this embodiment, during the process of acquiring the brain thermal imaging data of the target object during interaction, the temperature value deep in the brain of the target object during interaction can be acquired. The change in the temperature value deep in the brain can reflect the target object's brain usage and mental activity status.

[0056] In some optional implementations of this embodiment, in order to ensure that the temperature value deep within the brain can accurately and effectively reflect the state of mental activity and mental exertion, the temperature value deep within the brain can be obtained through the following steps:

[0057] The first temperature value of the hippocampus in the frontal lobe, the second temperature value of the striatum, and the third temperature value of the cerebellum of the target object were obtained during the interaction.

[0058] Calculate the first temperature value, the first temperature value, and the average temperature value of the first temperature value, and determine the average temperature value as the temperature value deep in the brain.

[0059] In practice, while playing the video content (i.e. the training content mentioned above), the temperature value deep in the brain can be collected simultaneously through devices such as thermal infrared sensors and / or electrodes. For example, the first temperature value of the hippocampus in the frontal lobe, the second temperature value of the striatum, and the third temperature value of the cerebellum can be recorded separately, and then the average temperature value of the three can be calculated.

[0060] In some optional implementations of this embodiment, after obtaining whether the target object's answer is correct, the first or second identifier of the answer can be stored in correspondence with the temperature value deep in the brain at the corresponding time, so that the memory improvement result can be determined based on the stored data later. For example, if the first question is answered correctly, it is recorded as the first identifier 1, and the temperature deep in the brain at the corresponding time is 30°, so the two can be stored as (1-30°); if the second question is answered correctly, it is also recorded as the first identifier 1, and the temperature deep in the brain at the corresponding time is 32°, so the two can be stored as (1-32°); the interaction data of other times are similar.

[0061] In some optional implementations of this embodiment, after acquiring the interaction data and brain thermal imaging data, in order to intuitively and accurately determine the memory improvement results, the memory improvement results of the target object can be determined in the following ways:

[0062] According to the time sequence of the target object's answers, each first identifier and the temperature value corresponding to each first identifier are traversed sequentially. It is determined whether the temperature value corresponding to the current first identifier is greater than the temperature value corresponding to the previous first identifier. If so, the memory value is incremented by 1. If not, the memory value is not incremented by 1. The memory value after the memory training process ends is determined as the memory improvement result.

[0063] For example, if the first question is answered correctly, it is recorded as the first identifier 1. The temperature deep in the brain at that moment is 30°C, so the two can be stored as (1-30°C). At this time, the memory value is incremented by 1. The initial value of the memory value is 0, and the current memory value is 1 after the increment. If the second question is answered correctly, it is also recorded as the first identifier 1. The temperature deep in the brain at that moment is 32°C, so the two can be stored as (1-32°C). At this time, the temperature is higher than the temperature when the first question was answered, so the memory value is incremented by 1 again, and the current memory value is 2, and so on.

[0064] In some optional implementations of this embodiment, the memory value can be set to a range of 0 to 100. The higher the value, the better the effect of the playback content (i.e., the training content) on improving the memory of the target object.

[0065] In some optional implementations of this embodiment, the process of determining the memory improvement result of the target object based on interactive data and brain thermal imaging data can be implemented by a dynamic time warping algorithm.

[0066] In some optional implementations of this embodiment, after the target object has been trained, the numerical value of the memory improvement result can be regarded as the target object's memory status after training. Therefore, the training content can be automatically and intelligently adjusted based on the numerical value of the memory improvement result to continue training with suitable content, thereby improving the training effect. For example, it can be determined whether the numerical value of the memory improvement result is greater than a preset threshold; if not, based on the numerical value of the memory improvement result, training content is re-acquired from the multiple training contents, and the re-acquired training content is displayed to the target object for memory training; if yes, then no adjustment of the training content is needed.

[0067] Specifically, the aforementioned preset threshold can be determined based on the specific training situation or the specific memory capacity of the target object. For example, the preset threshold could be 60.

[0068] In some optional implementations of this embodiment, when the target object uses the training content for the first time, information items such as the target object's age, gender, factors affecting memory (such as Alzheimer's disease and other conditions affecting memory, brain damage causing memory impairment, etc.), and degree of memory cognitive impairment (such as mild, moderate, severe cognitive impairment) can be obtained. Then, the target object's memory value is determined based on these information items, and this memory value is regarded as the target object's initial memory status. Then, training content can be automatically and intelligently selected based on the memory value so that training can continue with appropriate training content.

[0069] In some optional implementations of this embodiment, the process of determining the memory value of the target object based on the information items can be to input each information item into the trained model to obtain the memory value; or the memory value can be determined based on the pre-stored correspondence between the information items and the memory value.

[0070] In some optional implementations of this embodiment, during the process of automatically and intelligently selecting training content based on memory value or memory improvement result value (which is the memory value after training), the training content corresponding to different memory values ​​can be determined according to the pre-stored correspondence between the value and the training content, so as to achieve the purpose of selecting and adjusting the training content.

[0071] The above memory training methods can be implemented through device terminals, so that target individuals can conveniently use device terminals to conduct memory training.

[0072] The following combination Figure 3 To describe the process of implementing the above memory training method, the process may include the following steps:

[0073] 1) The target user uses the cognitive impairment memory improvement device, activates the device, and inputs information such as the target user's condition (mild cognitive impairment, Alzheimer's disease), age, gender, memory improvement level (easy, moderate, difficult), and frequency of memory improvement. Based on the information input by the target user, the system automatically matches a plan and determines the training content suitable for the target user.

[0074] 2) The cognitive impairment memory improvement device includes: 1. Training content that can improve the target subject's memory (this training content can be video and audio content combining clinically commonly used short-term memory, number cards, and long-term memory techniques). 2. The ability to collect the target subject's audio information (the device will automatically ask questions while playing the training content, requiring the target subject to answer). 3. The ability to collect temperature changes deep within the target subject's brain using thermal infrared sensors and electrodes. While playing video content, the device simultaneously collects thermal imaging data of the target subject's brain (e.g., temperature changes deep within the brain). This thermal imaging data reflects the temperature changes in the target subject's brain while watching the content, thus reflecting the target subject's brain activity.

[0075] 3) By using the Dynamic Time Warping algorithm, the video information, the audio information emitted by the target object, and the brain thermal imaging data are analyzed to provide the memory improvement value of the target object when training by playing content through the device (i.e., the above memory value). The value range can be 0 to 100. The higher the value, the better the effect of the played content on improving the target object's memory. (Rules for determining memory improvement values: When the device plays a specified video, it guides the target subject to give a voice response. Each video's time required for the target subject to respond is marked with data. Simultaneously, a voice recognition algorithm identifies whether the target subject's response is correct or incorrect; a correct answer is recorded as 1, and an incorrect answer as 0. The corresponding temperature values ​​of the hippocampus, striatum, and cerebellum in the frontal lobe are recorded, and the average temperature of these three areas is calculated. When a question is answered correctly, and the temperature when answering the next question is higher than the temperature when answering the previous question (i.e., the average temperature), the memory improvement value (i.e., the aforementioned memory value) is incremented by 1. For example: if the first question is answered correctly and the temperature is 30°C, the system displays (1-30°C); if the second question is answered correctly and the temperature is 32°C, the system displays (1-32°C), and the memory improvement value is 2. The system collects all parameter data during the video playback time and ultimately provides the memory improvement value.)

[0076] 4) When the playback ends and the displayed memory improvement score is too low (e.g., memory improvement score < 60 points), the system will automatically reselect suitable training content based on the memory improvement score to adjust the playback content; when the memory improvement score is > 60 points, the system will stop automatic adjustment and can switch to manual adjustment of the playback content.

[0077] 5) The target person or their family members, caregivers, etc., can manually adjust the video content played by the cognitive impairment memory improvement device (i.e., the training content mentioned above) based on the target person's memory ability in daily life.

[0078] See also Figure 4 , Figure 4 This is a schematic diagram illustrating an application scenario of the memory training method according to this embodiment. Figure 4 In the application scenario, the execution entity 401 acquires the memory status of the target object 402. Based on the memory status 402, the execution entity 401 selects training content 403 that matches the memory status from multiple training contents, wherein the training content includes audio content and video content. The execution entity 401 displays the acquired training content to the target object for memory training. During the memory training process, the execution entity 401 acquires interaction data 404 between the target object and the acquired training content, and acquires brain thermal imaging data 405 of the target object during the interaction. Based on the interaction data and the brain thermal imaging data, the execution entity 401 determines the memory improvement result of the target object 406.

[0079] Further reference Figure 5 As an implementation of the methods shown in the above figures, this application provides an embodiment of a memory training device, which is similar to... Figure 2 Corresponding to the method embodiment shown, in addition to the features described below, the device embodiment may also include [features related to...]. Figure 2 The method embodiments shown have the same or corresponding features or effects. This device can be specifically applied to various electronic devices.

[0080] like Figure 5As shown, the memory training device 500 of this embodiment includes: a memory status acquisition module 501, a training content determination module 502, a display module 503, a data acquisition module 504, and a memory improvement result determination module 505. The memory status acquisition module 501 is configured to acquire the memory status of a target object; the training content determination module 502 is configured to acquire training content matching the memory status from multiple training contents, wherein the training content includes audio content and video content; the display module 503 is configured to display the acquired training content to the target object for memory training; the data acquisition module 504 is configured to acquire interaction data between the target object and the acquired training content during the memory training process, and acquire brain thermal imaging data of the target object during the interaction; the memory improvement result determination module 505 is configured to determine the memory improvement result of the target object based on the interaction data and the brain thermal imaging data.

[0081] In this embodiment, the specific processing of the memory status acquisition module 501, training content determination module 502, display module 503, data acquisition module 504, and memory improvement result determination module 505 of the memory training device 500, and the resulting technical effects, can be referred to respectively. Figure 2 The relevant descriptions of steps 201, 202, 203, 204 and 205 in the corresponding embodiments will not be repeated here.

[0082] In some optional implementations of this embodiment, the data acquisition module includes:

[0083] The first data acquisition unit is configured to acquire, during the memory training process, the voice data of the target object answering the questions of the acquired training content; use a speech recognition algorithm to determine the answer of the target object from the voice data; determine whether the answer of the target object is correct, and if so, record a first identifier; if not, record a second identifier.

[0084] In some optional implementations of this embodiment, the data acquisition module includes:

[0085] The second data acquisition unit is configured to acquire the temperature value deep within the brain of the target object during the interaction.

[0086] In some optional implementations of this embodiment, the second data acquisition unit is configured to acquire a first temperature value of the hippocampus in the frontal lobe of the target object, a second temperature value of the striatum, and a third temperature value of the cerebellum during interaction; calculate the first temperature value, the first temperature value, and the average temperature value of the first temperature value, and determine the average temperature value as the temperature value deep in the brain.

[0087] In some optional implementations of this embodiment, the memory improvement result determination module is configured to sequentially traverse each first identifier and the temperature value corresponding to each first identifier according to the time order of the target object's answer, determine whether the temperature value corresponding to the current first identifier is greater than the temperature value corresponding to the previous first identifier, and if so, increment the memory value by 1, and determine the memory value after the memory training process ends as the memory improvement result.

[0088] In some optional implementations of this embodiment, the display module is configured to acquire the vision of the target object; determine the color that the target object's eyes recognize based on the vision; and display the acquired training content to the target object using the color to perform memory training.

[0089] In some optional implementations of this embodiment, the training content determination module is further configured to determine whether the value of the memory improvement result is greater than a preset threshold; if not, based on the value of the memory improvement result, re-acquire training content from the plurality of training contents, and display the re-acquired training content to the target object for memory training.

[0090] According to embodiments of this application, this application also provides an electronic device and a readable storage medium.

[0091] like Figure 6 The diagram shown is a block diagram of an electronic device for a memory training method according to an embodiment of this application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present application described and / or claimed herein.

[0092] like Figure 6As shown, the electronic device includes one or more processors 601, a memory 602, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components are interconnected via different buses and can be mounted on a common motherboard or otherwise as required. The processors can process instructions executed within the electronic device, including instructions stored in or on memory to display graphical information of a GUI on an external input / output device (such as a display device coupled to the interface). In other embodiments, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple electronic devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 6 Take the 601 processor as an example.

[0093] The memory 602 is the non-transitory computer-readable storage medium provided in this application. The memory stores instructions executable by at least one processor to cause the at least one processor to execute the memory training method provided in this application. The non-transitory computer-readable storage medium of this application stores computer instructions for causing a computer to execute the memory training method provided in this application.

[0094] Memory 602, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the memory training method in the embodiments of this application (e.g., attached...). Figure 5 The memory status acquisition module 501, training content determination module 502, display module 503, data acquisition module 504, and memory improvement result determination module 505 are shown. The processor 601 executes various server functions and data processing by running non-transient software programs, instructions, and modules stored in the memory 602, thereby implementing the memory training method in the above method embodiment.

[0095] The memory 602 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the use of the electronic device according to the memory training method. Furthermore, the memory 602 may include high-speed random access memory and may also include non-transient memory, such as at least one disk storage device, flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory 602 may optionally include memory remotely located relative to the processor 601, and these remote memories can be connected to the electronic device of the memory training method via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0096] The electronic device for memory training methods may further include an input device 603 and an output device 604. The processor 601, memory 602, input device 603, and output device 604 can be connected via a bus or other means. Figure 6 Taking the example of a connection between China and Israel via a bus.

[0097] Input device 603 can receive input numerical or character information, as well as key signal input related to user settings and function control of the electronic device for memory training methods, such as a touch screen, keypad, mouse, trackpad, touchpad, joystick, one or more mouse buttons, trackball, joystick, etc. Output device 604 may include a display device, auxiliary lighting device (e.g., LED), and haptic feedback device (e.g., vibration motor). The display device may include, but is not limited to, a liquid crystal display (LCD), a light-emitting diode (LED) display, and a plasma display. In some embodiments, the display device may be a touch screen.

[0098] Various implementations of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, application-specific integrated circuits (ASICs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transferring data and instructions to the storage system, the at least one input device, and the at least one output device.

[0099] These computational programs (also referred to as programs, software, software applications, or code) include machine instructions for a programmable processor and can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. As used herein, the terms “machine-readable medium” and “computer-readable medium” refer to any computer program product, device, and / or apparatus (e.g., disk, optical disk, memory, programmable logic device (PLD)) used to provide machine instructions and / or data to a programmable processor, including machine-readable media that receive machine instructions as machine-readable signals. The term “machine-readable signal” refers to any signal used to provide machine instructions and / or data to a programmable processor.

[0100] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0101] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0102] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other.

[0103] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0104] The units described in the embodiments of this application can be implemented in software or hardware. The described units can also be housed in a processor; for example, a processor can be described as including a memory status acquisition module, a training content determination module, a display module, a data acquisition module, and a memory improvement result determination module. The names of these units and modules do not necessarily limit the specific unit or module; for example, the memory status acquisition module can also be described as a "module for acquiring memory status."

[0105] In another aspect, this application also provides a computer-readable medium, which may be included in the apparatus described in the above embodiments; or it may exist independently and not assembled into the apparatus. The computer-readable medium carries one or more programs that, when executed by the apparatus, cause the apparatus to: acquire the memory status of a target object; acquire training content matching the memory status from multiple training contents, wherein the training content includes audio content and video content; display the acquired training content to the target object for memory training; during the memory training process, acquire interaction data between the target object and the acquired training content, and acquire brain thermal imaging data of the target object during the interaction; and determine the memory improvement result of the target object based on the interaction data and the brain thermal imaging data.

[0106] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A method for determining the improvement results of cognitive memory in a cognitive impairment memory training process, the method comprising: To obtain information on the cognitive impairment and memory status of the target individuals; Based on the cognitive impairment memory status, training content that matches the cognitive impairment memory status is selected from multiple training contents, wherein the training contents include audio content and video content; The selected training content is shown to the target object to train their memory skills for cognitive impairment. During the cognitive impairment memory training process, interaction data between the target object and the selected training content is acquired, and brain thermal imaging data of the target object during the interaction is acquired. Based on the interaction data and the brain thermal imaging data, the cognitive memory improvement result of the target object is determined by the dynamic time warping algorithm, and the training content is reselected based on the cognitive memory improvement result; During the cognitive impairment memory training process, the interaction data between the target object and the selected training content is acquired, including: During the cognitive impairment memory training process, the voice data of the target object answering the questions of the selected training content is acquired; A speech recognition algorithm is used to determine the answer given by the target object from the speech data; Determine whether the answer given by the target object is correct. If yes, record the first identifier; if no, record the second identifier. Acquiring brain thermal imaging data of the target object during interaction, including: Obtain the temperature value deep within the brain of the target object during the interaction; Obtaining the temperature value deep within the target object's brain during interaction, including: The first temperature value of the hippocampus in the frontal lobe, the second temperature value of the striatum, and the third temperature value of the cerebellum of the target object were obtained during the interaction. Calculate the first temperature value, the first temperature value, and the average temperature value of the first temperature value, and determine the average temperature value as the temperature value deep in the brain; Based on the interaction data and the brain thermal imaging data, the improvement in the cognitive memory of the target subject is determined using a dynamic time warping algorithm, including: According to the time sequence of the target object's answers, each first identifier and the temperature value corresponding to each first identifier are traversed sequentially. It is determined whether the temperature value corresponding to the current first identifier is greater than the temperature value corresponding to the previous first identifier. If so, the cognitive memory value is incremented by 1, and the cognitive memory value after the cognitive impairment memory training process ends is determined as the cognitive memory improvement result.

2. The method according to claim 1, wherein, Presenting selected training content to the target subject for cognitive impairment memory training includes: Obtain the vision status of the target object; Based on the described vision, determine the color that the target object's eyes can recognize; The selected training content is displayed to the target object using the color to train memory skills for cognitive impairment.

3. The method according to claim 1, wherein, Also includes: Determine whether the value of the improvement result in cognitive memory is greater than a preset threshold; If not, based on the numerical value of the cognitive memory improvement result, reselect training content from the multiple training contents, and display the reselected training content to the target object for cognitive impairment memory training.

4. A device for determining the improvement result of cognitive memory in the process of cognitive impairment memory training, the device comprising: The cognitive memory status acquisition module is used to acquire the cognitive impairment memory status of the target object; The training content determination module is used to select training content that matches the cognitive impairment memory status from multiple training contents based on the cognitive impairment memory status, wherein the training content includes audio content and video content; The display module is used to display selected training content to the target object for cognitive impairment memory training; The data acquisition module is used to acquire interaction data between the target object and the selected training content during the cognitive impairment memory training process, and to acquire brain thermal imaging data of the target object during the interaction. The cognitive memory improvement result determination module is used to determine the cognitive memory improvement result of the target object based on the interaction data and the brain thermal imaging data through a dynamic time warping algorithm, and to reselect training content based on the cognitive memory improvement result; The data acquisition module includes: The first data acquisition unit is configured to acquire, during the memory training process, the voice data of the target object answering the questions of the selected training content; use a voice recognition algorithm to determine the answer of the target object from the voice data; determine whether the answer of the target object is correct, and if so, record a first identifier; if not, record a second identifier. The data acquisition module includes: The second data acquisition unit is used to acquire the temperature value deep inside the brain of the target object during the interaction. The second data acquisition unit is used to acquire the first temperature value of the hippocampus in the frontal lobe of the target object, the second temperature value of the striatum and the third temperature value of the cerebellum during the interaction; calculate the first temperature value, the first temperature value and the average temperature value of the first temperature value, and determine the average temperature value as the temperature value deep in the brain. The cognitive memory improvement result determination module is used to sequentially traverse each first identifier and the temperature value corresponding to each first identifier according to the time order of the target object's answer, determine whether the temperature value corresponding to the current first identifier is greater than the temperature value corresponding to the previous first identifier, if so, increment the cognitive memory value by 1, and determine the cognitive memory value after the cognitive impairment memory training process ends as the cognitive memory improvement result.

5. An electronic device, comprising: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-3.

6. A computer-readable storage medium having a computer program stored thereon, wherein, When the program is executed by the processor, it implements the method as described in any one of claims 1-3.

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