Auxiliary analysis method, medium and device for mental disease type based on fNIRS

Abstract

The invention provides an auxiliary analysis method, medium and device for mental disease types based on fNIRS. The auxiliary analysis method comprises the following steps: acquiring first blood oxygen concentration data of a subject corresponding to a concerned brain region when executing a first composite task; comparing the first blood oxygen concentration data with preset second blood oxygen concentration data by using a processor, and performing auxiliary analysis on the mental disease tendency of the subject based on a comparison result; wherein the first composite task comprises at least two types of tasks. Therefore, mental diseases with similar symptoms can be accurately distinguished, and objective indexes are provided for auxiliary analysis of the mental diseases.

Description

Technical Field

[0001] The present application relates to the technical field of near-infrared detection, and specifically relates to an auxiliary analysis method, medium, and device for mental disease types based on fNIRS. Background Art

[0002] Mental diseases seriously affect the life and social functions of patients. They can cause disorders in the brain's functional activities, and these disorders may lead to impairments in multiple functions such as cognition, emotion, behavior, and will. Currently, the diagnosis of mental diseases mainly relies on clinicians to conduct examinations through interviews, observing the behavior of patients, etc. There are also some technical means that use psychological paradigms to detect the emotional state of patients. For example, the VFT paradigm, n-back paradigm, emotional stroop paradigm, etc. Research shows that it can effectively detect the emotional state of patients, which is beneficial for the evaluation and treatment of the psychological state.

[0003] The evaluation and diagnosis of mental diseases usually require experienced psychiatrists to make judgments by combining the clinical symptoms of patients, the descriptions of the patient's condition by their family members, and the results of corresponding scales. However, this diagnosis method has high requirements for the clinician's clinical knowledge and experience, and has strong subjectivity, lacking objective diagnostic indicators. In some cases, it is difficult to distinguish some mental diseases solely based on clinical symptoms. For example, bipolar disorder and unipolar depression are often difficult to distinguish, which is prone to misdiagnosis. Misdiagnosis may lead to a series of problems such as aggravating the patient's symptoms. Therefore, how to accurately distinguish mental diseases with similar symptoms and provide more objective indicators for the diagnosis of mental diseases is a major challenge faced by the field of psychiatry. Summary of the Invention

[0004] In view of the above technical problems existing in the prior art, the present application is proposed. The present application aims to provide an auxiliary analysis method, medium, and device for mental disease types based on fNIRS, which can provide a composite task including several types of tasks for the subject to execute efficiently and conveniently at one time, simplify the task processing process on which the auxiliary analysis depends, and the blood oxygen concentration data corresponding to each type of task can support each other synergistically to efficiently and accurately identify and distinguish mental diseases, especially some mental diseases with similar symptom manifestations, and provide objective indicators for the auxiliary analysis of mental diseases.

[0005] According to the first aspect of the present application, there is provided an auxiliary analysis method for mental illness types based on fNIRS. The auxiliary analysis method includes: obtaining first blood oxygen concentration data of a subject corresponding to a concerned brain region during the execution of a first composite task; using a processor to compare the first blood oxygen concentration data with preset second blood oxygen concentration data, and performing auxiliary analysis on the mental illness predisposition of the subject based on the comparison result; wherein the first composite task includes at least two types of tasks.

[0006] According to the second aspect of the present application, there is provided a computer-readable storage medium storing a computer program which, when executed by a processor, executes the auxiliary analysis method for mental illness types based on fNIRS as described in various embodiments of the present application.

[0007] According to the third aspect of the present application, there is provided a device for auxiliary analysis of mental illness types based on fNIRS. The device includes an interface and a processor. The interface is configured to: obtain first blood oxygen concentration data of a subject corresponding to a concerned brain region during the execution of a first composite task; the processor is configured to: use the processor to compare the first blood oxygen concentration data with preset second blood oxygen concentration data, and perform auxiliary analysis on the mental illness predisposition of the subject based on the comparison result; wherein the first composite task includes at least two types of tasks.

[0008] Compared with the prior art, the beneficial effects of the embodiments of the present application are as follows:

[0009] The auxiliary analysis method based on fNIRS provided by the embodiments of the present application requires the subject to execute a first composite task and collects first blood oxygen concentration data of the subject corresponding to the concerned brain region during the execution of the first composite task. Among them, the first composite task includes at least two types of tasks. By executing these two types of tasks, the subject can analyze the first blood oxygen concentration data obtained during the execution of these two types of tasks with reference to the preset second blood oxygen concentration data representing the reference levels during the processes of these two types of tasks. The present application determines the mental illness predisposition of the subject by comparing the first blood oxygen concentration data obtained from the subject's execution of the first composite task including at least two types of tasks with the second blood oxygen concentration data. Compared with the prior art which only uses examination methods such as interviews, observing the behavior of patients, and scale detection, it can provide an objective index for evaluating whether the subject has a neurological disease predisposition, improve the accuracy of evaluating the mental illness predisposition of the subject, and the present application requires the subject to execute at least two types of tasks instead of one type of task, which can not only further determine whether the subject has a mental illness, but also further effectively distinguish the types of mental illnesses suffered by the subject.

[0010] The above description is only an overview of the technical solution of the present application. In order to be able to more clearly understand the technical means of the present application, it can be implemented in accordance with the content of the specification. And in order to make the above description, other purposes, features and advantages of the present application more obvious and understandable, the specific embodiments of the present application are specifically given below. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In the drawings which are not necessarily drawn to scale, the same reference numerals may describe similar components in different views. Similar reference numerals with alphabetical suffixes or different alphabetical suffixes may represent different examples of similar components. The drawings generally illustrate various embodiments by way of example and not by way of limitation, and are used together with the specification and the claims to explain the disclosed embodiments. Such embodiments are illustrative and exemplary and are not intended to be an exhaustive or exclusive embodiment of the method, apparatus, system or non-transitory computer-readable medium having instructions for implementing the method.

[0012] Figure 1 A flowchart showing the auxiliary analysis method according to an embodiment of the present application is shown.

[0013] Figure 2 An execution sequence diagram of a second composite task according to an embodiment of the present application is shown.

[0014] Figure 3 A schematic structural diagram of the apparatus for auxiliary analysis according to an embodiment of the present application is shown. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] To enable those skilled in the art to better understand the technical solution of the present application, the present application will be described in detail below in conjunction with the drawings and specific embodiments. The embodiments of the present application will be further described in detail below in conjunction with the drawings and specific examples, but this is not a limitation to the present application.

[0016] The "first", "second" and similar terms used in the present application do not denote any order, quantity or importance, but are only used for distinction. The terms "including" or "comprising" and the like used in the present application mean that the elements before the term cover the elements listed after the term, and do not exclude the possibility of also covering other elements. In the present application, the arrows shown in the figures for each step are only examples of the execution order and not limitations. The technical solution of the present application is not limited to the execution order described in the embodiments. Each step in the execution order can be executed together, can be decomposed, and can be reordered as long as the logical relationship of the execution content is not affected.

[0017] All terms used in this application (including technical or scientific terms) have the same meaning as understood by those of ordinary skill in the art to which this application pertains, unless otherwise specifically defined. It should also be understood that terms defined in a general dictionary, for example, should be interpreted as having a meaning consistent with their meaning in the context of the relevant art, and should not be interpreted in an idealized or overly formal sense, unless specifically defined as such here. Technologies and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such technologies and devices should be regarded as part of the specification.

[0018] The auxiliary analysis method for mental illness types based on fNIRS provided by an embodiment of this application includes Figure 1 the steps S101 - S102 shown. In step S101, first blood oxygen concentration data of corresponding attention brain regions of a subject during the execution of a first composite task is obtained. In step S102, a processor is used to compare the first blood oxygen concentration data with preset second blood oxygen concentration data, and based on the comparison result, an auxiliary analysis is performed on the mental illness predisposition of the subject; wherein, the first composite task includes at least two types of tasks.

[0019] The "type" in the two types of tasks can be understood as the type of task paradigm. Among them, the task paradigm can be a resting-state task, a VFT task, an N-back task, etc. Only this is used as an exemplary illustration and is not limited thereto.

[0020] The first composite task can, for example, include a resting-state task and a task of other paradigms, or can also be two different paradigms of tasks other than the resting-state task. Exemplarily, in the case where the first composite task includes a resting-state task and a VFT task, the subject first performs the resting-state task to adjust their state during detection, and then can smoothly enter the VFT task when performing the VFT task. Therefore, the subject can efficiently and conveniently perform the first composite task.

[0021] The preset second blood oxygen concentration data can be the blood oxygen concentration data of a healthy subject obtained in advance during the execution of the first composite task, or, simultaneously collect the near-infrared data of a healthy subject during the execution of the first composite task and obtain the blood oxygen concentration data based on the near-infrared data, that is, the preset healthy reference. At this time, the first blood oxygen concentration data of the corresponding attention brain region of the subject during the execution of the first composite task is compared with the second blood oxygen concentration data at the healthy level. If the comparison result shows that the deviation between the first blood oxygen concentration data and the second blood oxygen concentration data is large, it can be considered that the subject has a mental illness predisposition.

[0022] Alternatively, the preset second blood oxygen concentration data may not be the blood oxygen concentration data at a healthy level, or may be the blood oxygen concentration data obtained by the subject with a mental illness when performing the first composite task, that is, the preset disease reference. At this time, the first blood oxygen concentration data is compared with the preset second blood oxygen concentration data. If the comparison result shows that the difference between the first blood oxygen concentration data and the preset second blood oxygen concentration data is not significant, it can be considered that the subject has a tendency to suffer from mental illness.

[0023] Alternatively, the preset second blood oxygen concentration data can also be understood as the blood oxygen concentration data summarized or induced based on clinical experimental data. The preset second blood oxygen concentration data can be the blood oxygen concentration data representing different preset ranges with a tendency to suffer from one and / or more mental illnesses. For example, if through comparison, the first blood oxygen concentration data is within the first range of the second blood oxygen concentration data, it is considered that the subject has a tendency to suffer from a certain neurological disease (such as depression). If the first blood oxygen concentration data is within the second range of the second blood oxygen concentration data, it is considered that the subject has a tendency to suffer from another neurological disease (such as bipolar disorder).

[0024] Taking this as an example only, there is no limitation on the preset second blood oxygen concentration data, and it can be set by the doctor himself.

[0025] In this embodiment, the brain regions of interest can be selected from one or more of the prefrontal lobe, temporal lobe, occipital lobe, parietal lobe, and inferior frontal gyrus. The brain regions of interest can be determined according to the specific tasks in the first composite task performed by the subject. Taking this as an example only.

[0026] By comparing the first blood oxygen concentration data obtained by the subject performing the first composite task including at least two types of tasks with the second blood oxygen concentration data, the present application determines the tendency of the subject to suffer from mental illness. Compared with the existing technologies that only use examination methods such as interviews, observing the behavior of patients, and scale detection, it can provide an objective index for evaluating whether the subject has a tendency to suffer from neurological diseases, can improve the accuracy of evaluating the tendency of the subject to suffer from mental illness, and the present application requires the subject to perform at least two types of tasks instead of one type of task, which can not only further determine whether the subject suffers from mental illness, but also effectively distinguish the types of mental illnesses suffered by the subject.

[0027] In some embodiments of the present application, at least one type of task in the first composite task is selected from one of a resting-state task, a VFT task, an N-back task, and an emotional Stroop task. In other embodiments, at least one type of task in the first composite task may also be selected from other tasks, such as a CPT task. Among them, the resting-state task may include tasks of rest and relaxation, that is, tasks performed under the condition that the subject is in a static state (i.e., not performing tasks such as calculation, recognition, and movement), etc. The resting-state task refers to an independent task paradigm, rather than being in a resting state. The VFT task may include tasks of counting numbers and forming words. For example, the task of counting numbers may be to require the subject to repeat counting "12345" within a limited time, and the task of forming words may be to require the subject to form words with single characters such as "white", "north", or "big" within a specified time.

[0028] The N-back task may include a number 1-back task and / or an emotion 1-back task. Among them, the number 1-back task may be to sequentially display a number on a display interface and let the subject determine whether the next displayed number is the same as the previous number, and the emotion 1-back task may be to sequentially display an emoticon picture on the display interface and let the subject determine whether the next displayed emoticon picture is the same as the previous emoticon picture. The emotional Stroop task may be to sequentially display emoticon pictures on a display interface and present emotion description words on the emoticon pictures, and let the subject determine whether the displayed emoticon picture and the emotion description word on the emoticon picture are the same.

[0029] This is only an illustrative example and does not constitute a limitation on the specific task content.

[0030] The above-mentioned resting-state task, VFT task, N-back task, and emotional Stroop task can reflect the brain function conditions of different brain regions and are some tasks applicable to a wide range of subjects. These tasks can be used as basic tasks, and other task paradigms can be adapted according to the specific situation of the subject to obtain the first composite task suitable for the subject.

[0031] In some embodiments of the present application, the first composite task is determined through the following processing, specifically including: obtaining the third blood oxygen concentration data of the corresponding attention brain regions of various mental illness patients when performing the second composite task, such as Figure 2As shown, the second composite task includes a resting-state task 201, a VFT task 202, an N-back task 203, and an emotional Stroop task 204 that are executed in sequence. The resting-state task 201 can be used to judge the activity coordination information between the left and right brains of the subject, and for the subject, performing the resting-state task 201 is relatively easy compared to performing other tasks. Therefore, it is easier for the subject to enter the state during the execution of the resting-state task 201. Subsequently, by performing the VFT task 202, the doctor can understand the brain function state of the subject in a relatively short time, and can distinguish between healthy subjects and subjects with mental illnesses.

[0032] Some typical symptoms of mental illnesses (such as pathological rumination and anhedonia) are highly correlated with impairments in working memory. An N-back task 203 can be set after the VFT task 202, which helps the doctor further understand the brain function status of the subject. There are defects and abnormalities in the brain regions related to emotions in patients with mental illnesses, and the cortical systems involved in emotion regulation and emotion-cognition interaction may be particularly disturbed. Patients with mental illnesses consume too much attention when performing tasks, so they are prone to being involved in the induced negative situations and cannot effectively regulate negative emotions, thus affecting their processing of cognitive tasks. Therefore, setting the emotional Stroop task 204 after the N-back task 203 helps to further analyze whether the subject is affected by negative emotions and affects the execution of the previous tasks, and further distinguish more refined types of mental illnesses.

[0033] The processor is used to compare the third blood oxygen concentration data with the fourth blood oxygen concentration data within a preset healthy reference level range to determine the type of the first task included in the first composite task, so that the first composite task can be used at least to distinguish whether the subject has a mental illness. Among them, the third blood oxygen concentration data is collected based on various types of mental illness patients when they perform the second composite task. Due to the wide range of the collection objects and the comprehensiveness of the second composite task, the third blood oxygen concentration data of various types of mental illness patients can be widely collected. The second composite task includes a resting-state task, a VFT task, an N-back task, and an emotional Stroop task that are executed in sequence, and can comprehensively consider various types of mental illnesses. Therefore, the second composite task plays an important role in judging whether the subject has a mental illness, which is beneficial to improving the accuracy of identifying whether the subject has a mental illness. Specifically, by comparing the third blood oxygen concentration data corresponding to a single task in the second composite task performed by the subject with the fourth blood oxygen concentration data within a preset healthy reference level range, a first task that can be used to distinguish whether the subject has a mental illness or has a tendency to suffer from a mental illness can be determined. Among them, when a mental illness patient sequentially performs a resting-state task, a VFT task, an N-back task, and an emotional Stroop task, the third blood oxygen concentration data for each type of task can be obtained respectively, and the third blood oxygen concentration data obtained for each type of task is respectively compared with the fourth blood oxygen concentration data within the preset healthy reference level range corresponding to the task. For example, the third blood oxygen concentration data and the fourth blood oxygen concentration data under the resting-state task, the third blood oxygen concentration data and the fourth blood oxygen concentration data under the VFT task, the third blood oxygen concentration data and the fourth blood oxygen concentration data under the N-back task, and the third blood oxygen concentration data and the fourth blood oxygen concentration data under the emotional Stroop task are respectively compared. The first task and the priority of the first task are determined according to the differences in the comparison results for each type of task. Among them, the task type with a relatively large difference in the comparison results can be used as the first task. At this time, based on the first task, it can be effectively distinguished whether the subject is a mental illness patient or a healthy person. For example, compared with other types of tasks, the third blood oxygen concentration data of the inferior frontal gyrus of a mental illness patient when performing a resting-state task is obtained. By comparing it with the fourth blood oxygen concentration data within a preset healthy reference level range, it is found that the functional connectivity strength of the inferior frontal gyrus of the mental illness patient is relatively poor compared with the preset healthy reference level range. At this time, the resting-state task can be used as the type of the first task in the first composite task, so that based on the first task, it can be used at least to distinguish whether the subject has a mental illness. This is only an example and does not constitute a limitation on the specific solution.

[0034] In some embodiments of the present application, the first composite task is determined based on the obtained third blood oxygen concentration data, and further includes using a processor to perform a comparative analysis on the third blood oxygen concentration data of various types of mental illness patients, and determining the type of the second task included in the first composite task according to the comparative analysis result, so that the second task can be used to distinguish at least two types of mental illnesses. Specifically, the third blood oxygen concentration data corresponding to each single task in the second composite task can be obtained for various types of mental illness patients respectively, the third blood oxygen concentration data of different types of mental illness patients performing the same type of task can be compared, and the task type with a relatively large difference in the comparison result can be used as the second task. At this time, the disease type of the subject can be distinguished based on the second task. For example, by comparing and analyzing the third blood oxygen concentration data of the frontal lobe or temporal lobe of a patient with major depressive disorder when performing the VFT task with the third blood oxygen concentration data of the frontal lobe or temporal lobe of a patient with schizophrenia when performing the VFT task, schizophrenia and major depressive disorder can be distinguished according to the difference between the third blood oxygen concentration data of the two. At this time, the VFT task can be used as the type of the second task in the first composite task, so that at least two types of mental illnesses can be distinguished based on the second task. This is only an example and does not constitute a limitation on the specific solution.

[0035] Among them, when performing the detection on the first task and / or the second task of the first composite task obtained according to the foregoing method, it is not necessary to make the subject perform all the task types that can be used as the first task and all the task types that can be used as the second task. For example, when the subject performs the first task, only the tasks with relatively low difficulty and capable of distinguishing whether the subject is a mental illness patient or a healthy person can be performed, and the second task performed by the subject can be selected according to the possible type of mental illness.

[0036] In some embodiments of the present application, the auxiliary analysis method further includes: when the first composite task includes a first task capable of distinguishing whether the subject has a mental illness and a second task capable of distinguishing at least two types of mental illnesses, the execution priority of the first task is higher than that of the second task. Specifically, for example, the first composite task includes a VFT task, a resting state task, and an emotional Stroop task, and the resting state task is used as the first task, and the VFT task and the emotional Stroop task are used as the second tasks. At this time, the subject is required to perform the first task (i.e., the resting state task) first, and then perform the second tasks (i.e., the VFT task and the emotional Stroop task, and the execution priority of the VFT task and the emotional Stroop task is not limited) after completing the first task.

[0037] This application takes the task of being able to distinguish whether the subject is a healthy person or a mental illness patient as the first priority, with the highest priority. Secondly, the task of being able to distinguish two types of mental illnesses with relatively high similarity is taken as the second priority. When judging whether the subject has a mental illness, that is, identifying the "presence" or "absence" of the subject's mental illness, and then further distinguishing between two mental illnesses, it can help accurately judge the type of mental illness the subject has. For example, when there is a difference between the first blood oxygen concentration data and the second blood oxygen concentration data obtained when the subject performs the VFT task, it does not only mean that the subject may have schizophrenia, but may also have other mental illnesses. In the embodiments of this application, the type of the first task is determined by first identifying the "presence" or "absence" of the subject's mental illness, and then based on the comparative analysis results, the type of the second task that can distinguish at least two mental illnesses is determined, so as to obtain the first composite task. By acquiring the first blood oxygen concentration data of the subject when performing the first composite task, the type of mental illness the subject has can be judged more accurately. By requiring the subject to perform the first task first, it is beneficial for the doctor to preliminarily judge whether the subject has a tendency to suffer from mental illness or whether the subject has a mental illness based on the first blood oxygen concentration data of the subject when performing the first task. Secondly, after the subject finishes performing the first task and then performs the second task, it is beneficial for the doctor to further distinguish the type of mental illness the subject has based on the first blood oxygen concentration data of the subject when performing the second task. For example, further judge whether the subject has schizophrenia, unipolar depression, bipolar disorder, anxiety disorder or other mental illnesses. In this way, the accuracy of the doctor's diagnosis of the type of mental illness of the subject is improved, and mental illnesses with similar onset symptoms can be accurately and objectively distinguished.

[0038] In addition, the execution priority of the first task is higher than that of the second task, that is, the subject is required to perform the first task first and then the second task, so as to first judge whether the subject has a mental illness and then judge the specific type of mental illness. In this way, the workload of analyzing the type of mental illness the subject has can be reduced and the analysis efficiency can be improved. The execution complexity and difficulty of the subject performing the first task are lower than those of performing the second task. Therefore, the execution priority of the first task being higher than that of the second task can enable the subject to maintain a relatively high level of attention and interest to perform the second task. On the contrary, if the execution priority of the second task is higher than that of the first task, since the subject needs to consume more attention when performing the second task, it is very likely that the attention will decrease when performing the first task and the execution effect will be poor. For example, when the second task is the emotional Stroop task and the first task is the resting state task, if the emotional Stroop task is performed first, the blood oxygen concentration level of the subject has already increased, and without reverse inhibition, the blood oxygen concentration data of the resting state task cannot be obtained accurately when performing the resting state task.

[0039] In some embodiments of the present application, the auxiliary analysis method further includes: making a preliminary judgment on the disease condition of the subject. For example, the subject can be asked to complete a scale, or the doctor can make a preliminary judgment on the tendency of the subject to suffer from mental illness by means of observation, inquiry, etc. Only as an example, the specific manner of making the preliminary judgment is not specifically limited. Determining the type and / or priority of each task in the first composite task according to the result of the preliminary judgment, specifically including at least one of the following methods:

[0040] Method 1: When the preliminary judgment result of the subject's disease condition is that the subject has a depressive tendency, the first composite task at least includes the N-back task and the emotional Stroop task, and the execution priority of each task is: N-back task > emotional Stroop task. For example, when it is determined that the subject has a depressive tendency, by asking the subject to perform the N-back task first and then the emotional Stroop task, the working memory ability and inhibitory control ability of the subject when performing these two tasks can be analyzed. If the degree of impairment of the working memory ability of the subject when performing the N-back task is relatively high, the subject may suffer from depression or bipolar disorder. Since bipolar disorder is manifested by alternating manic and depressive episodes, there is a certain similarity between bipolar disorder and depression, and it is impossible to determine whether the subject has depression or bipolar disorder only based on the N-back task. Therefore, a further judgment is made based on the emotional Stroop task. If the inhibitory control ability when performing the emotional Stroop task is even worse, it can be further determined that the subject may have bipolar disorder. The N-back task is relatively simple compared to the emotional Stroop task, and the execution priority of the N-back task is higher than that of the emotional Stroop task, making it easier for the subject to accept the relatively simple task.

[0041] Method 2: When the preliminary judgment result of the disease condition of the subject is that the subject has schizophrenia or manic tendency, the first composite task at least includes the VFT task, the N-back task, and the emotional Stroop task. The execution priorities of each task are: VFT task > emotional Stroop task > N-back task. There are many similarities in the clinical manifestations of schizophrenia and manic tendency patients, but their pathogenesis is different. The applicant found that by enabling the subject to sequentially perform the VFT task, the emotional Stroop task, and the N-back task, the type of disease suffered by the subject can be judged more accurately. For example, by performing the VFT task, the subject can obtain the brain activation status of the prefrontal lobe. If the brain activation status is poor, it can be confirmed that the subject has schizophrenia. By further performing the emotional Stroop task and the N-back task, the abnormalities of the subject in working memory and cognitive control can be further studied. When performing the emotional Stroop task, schizophrenia patients may show lower inhibitory control ability and higher error rate. Moreover, schizophrenia patients may show abnormal brain region activation patterns when performing the N-back task, such as abnormal activities in regions such as the prefrontal lobe and parietal lobe. Thus, it helps to further judge whether the subject has schizophrenia.

[0042] Method 3: When the preliminary judgment result of the disease condition of the subject is that the subject has anxiety tendency, the first composite task at least includes the VFT task and the N-back task. The execution priorities of each task are: VFT task > N-back task. Since anxiety disorder and depression are not easy to distinguish, when it is preliminarily judged that the subject has anxiety tendency, the subject is required to first perform the VFT task and then perform the N-back task. If, when performing the VFT task, it is analyzed that the brain activation status of the frontal lobe of the subject is poor, and the error rate is high and the reaction time is long when performing the N-back task, it can be judged that the subject has anxiety disorder rather than depression. If the subject performs the N-back task first, it will cause the emotions of patients with anxiety disorder to be disturbed, which is not conducive to distinguishing different mental diseases based on the VFT task.

[0043] Method 4: When the preliminary judgment result of the disease condition of the subject is that the subject has an ADHD tendency, the first composite task at least includes the N-back task, the emotional Stroop task, and the CPT task, and the execution priorities of each task are: CPT task > emotional Stroop task > N-back task. For a subject with an ADHD tendency, first, during the execution of the CPT task, the error rate is relatively high and the reaction time is relatively long, and the first blood oxygen concentration data is abnormal compared with the preset second blood oxygen concentration data. When performing the emotional Stroop task, the brain activation degree of the prefrontal lobe of ADHD patients is relatively high, and when performing the N-back task, the brain activation degree of the temporal lobe is relatively high. In this way, the ADHD tendency can be distinguished from other mental diseases. Moreover, for patients with an ADHD tendency, the execution priority of the emotional Stroop task is greater than that of the N-back task. By stimulating the subject with the more difficult emotional Stroop task, it is beneficial to make the difference degree of the first blood oxygen concentration data of the subject higher when performing the emotional Stroop task and the N-back task, which is more conducive to distinguishing whether the subject has ADHD or other mental diseases.

[0044] The above is only an exemplary illustration and does not constitute a limitation on the specific solution.

[0045] In addition, Method 1, Method 2, Method 3, and Method 4 can be presented to the doctor in the form of optional items. Specifically, for example, the doctor preliminarily judges the possible mental disease tendency of the subject based on the behavioral data, and then selects from Method 1, Method 2, Method 3, and Method 4 according to the preliminary judgment result, which helps to further judge the mental disease tendency of the subject.

[0046] In some embodiments of the present application, the auxiliary analysis of the mental disease tendency of the subject based on the comparison result specifically includes at least one of the following methods:

[0047] Method 1: Compare the first blood oxygen concentration data of the subject during the execution of the resting state task with the second blood oxygen concentration data, and determine the activity coordination information and brain function connection strength between the left brain and the right brain of the patient to analyze the mental disease tendency of the subject. That is to say, through comparison, if it is found that there is serious activity disorder between the left brain and the right brain of the subject, and the brain function connection strength is relatively poor, it can be judged that the subject has a mental disease tendency.

[0048] Method 2: Compare the first blood oxygen concentration data and the second blood oxygen concentration data of the subject when performing the VFT task, and determine the activation of the brain regions of interest to analyze the tendency of the subject to have mental illness. Specifically, by comparing the first blood oxygen concentration data and the second blood oxygen concentration data of the subject, if there is a large difference between the two and the first blood oxygen concentration data shows obvious abnormalities, it can be judged that the subject has a tendency to have mental illness. For example, if the comparison result shows that the activation degree of the prefrontal cortex of the subject is lower, it can be judged that the subject may have a tendency to have bipolar depression, unipolar depression or schizophrenia; or, if the brain activation degree of the temporal lobe sub-region of the subject is lower, it can be judged that the subject has a tendency to have unipolar depression or schizophrenia.

[0049] Method 3: Compare the first blood oxygen concentration data and the second blood oxygen concentration data of the subject when performing the N-back task, and combine the behavioral data of the patient when performing the N-back task to determine the activity pattern of the brain regions of interest to analyze the tendency of the subject to have mental illness. Among them, the activity pattern can be summarized from the brain activity rules of clinical patients, or can be obtained by collecting large-scale clinical data analysis. For example, whether the activity pattern of the prefrontal lobe of the subject when performing the N-back task belongs to positive activation or negative activation is not limited to the specific acquisition method. Specifically, the difference between the first blood oxygen concentration data and the second blood oxygen concentration data of the subject when performing the N-back task can be compared to analyze the damage status of the brain regions of interest of the subject, and combined with the behavioral data of the subject when performing the N-back task, such as the correct rate, error rate, etc., to further determine the activity pattern of the brain regions of interest of the subject. In this way, it helps to judge whether the subject has a tendency to have schizophrenia, ADHD, depressive disorder or mild cognitive impairment.

[0050] Method 4: Compare the first blood oxygen concentration data and the second blood oxygen concentration data of the subject when performing the emotional Stroop task, and combine the behavioral data of the patient when performing the emotional Stroop task to analyze the tendency of the subject to have mental illness. Among them, the emotional Stroop task can include a familiarization task stage and a formal task stage. In the familiarization task stage, the subject familiarizes with the task under the guidance of the doctor. In the formal task stage, the subject completes the task according to the instructions. After the task is completed, the doctor collects behavioral data such as near-infrared data, scale data, evaluation labels, and behavioral statistics tables (including the correct rate and reaction time).

[0051] Based on the first blood oxygen concentration data, scale data, labels and other behavioral data obtained when the subject performs the emotional Stroop task, the characteristics of the first blood oxygen concentration data (such as activation integral value, central value, mean value, functional connection strength, etc.) can be extracted. Based on the above characteristics, compare and analyze with the preset characteristics extracted from the second blood oxygen concentration data to obtain the brain activity differences and the brain activity change status of the subject, so as to help judge the mental illness tendency of the subject. For example, the tendency of bipolar disorder and unipolar disorder can be further distinguished by analyzing the first blood oxygen concentration data and behavioral data obtained when the subject performs the emotional Stroop task.

[0052] The above is only an exemplary illustration and does not constitute a limitation on the specific solution.

[0053] In some embodiments of the present application, the auxiliary analysis method further includes obtaining the electroencephalogram data collected by the subject when performing the first composite task; based on the comparison result, combining the electroencephalogram data of the subject when performing the first composite task to assist in analyzing the mental illness tendency of the subject. Specifically, the changes in electroencephalogram activity can be recorded by electroencephalogram (EEG) to assist the comparison result of blood oxygen concentration data to help diagnose various mental illnesses, such as attention deficit hyperactivity disorder (ADHD), schizophrenia, depression, etc. The analysis of electroencephalogram data can reveal the differences in electroencephalogram activity among patients with different mental illnesses. For example, researchers can analyze electroencephalogram data to find biomarkers related to specific mental illnesses, so as to better understand the pathogenesis of the disease and provide more accurate methods for disease prevention and treatment.

[0054] For example, the subject can be required to wear a near-infrared-electroencephalogram dual-modal headgear to collect the near-infrared data and electroencephalogram data of the subject when performing the emotional Stroop task. Among them, the electroencephalogram data has the characteristics of high time resolution and can make up for the lack of information of near-infrared data in the time dimension to a certain extent, so as to assist doctors to make a more accurate judgment on the mental illness tendency of the subject.

[0055] In some embodiments of the present application, the brain regions of interest at least include the frontal lobe and the temporal lobe, and the auxiliary analysis method at least includes at least one of the following situations

[0056] Situation 1, when the subject performs the resting state task, the brain region of interest is the inferior frontal gyrus. Specifically, the tendency of the subject to suffer from schizophrenia can be assisted in judgment by analyzing the brain functional connection strength of the inferior frontal gyrus.

[0057] In Case 2, when the subject is performing the VFT task, the brain regions of interest are the prefrontal lobe and / or the temporal lobe. Specifically, it is possible to determine whether the subject has schizophrenia, unipolar disorder, or bipolar disorder by analyzing the brain activation status of the prefrontal lobe. Alternatively, it is possible to determine whether the subject has a tendency to develop unipolar disorder or schizophrenia by analyzing the brain activation of the temporal lobe.

[0058] In Case 3, when the subject is performing the N-back task, the brain region of interest is the prefrontal lobe. Specifically, it is possible to determine whether the subject has a tendency to develop ADHD, depressive disorder, or mild cognitive impairment by analyzing the activity pattern of the prefrontal lobe in combination with behavioral data.

[0059] In Case 4, the activation of the determined brain regions of interest when the subject is performing the VFT task includes determining the activation of the frontal lobe and / or the temporal lobe.

[0060] In the present application, it is possible to adaptively adjust the brain regions of interest to be detected based on the type of task to be performed by the subject, so as to more efficiently and accurately determine the disease tendency of the subject.

[0061] Among them, the above-mentioned processor may be a processing device including more than one general-purpose processing device, such as a microprocessor, a central processing unit (CPU), a graphics processing unit (GPU), etc. More specifically, the processor may be a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a processor running other instruction sets, or a processor running a combination of instruction sets. The processor may also be more than one dedicated processing device, such as an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), a system-on-chip (SoC), etc.

[0062] The present application describes various operations or functions, which can be implemented as software code or instructions or defined as software code or instructions. Such content may be source code that can be directly executed or differential code ("incremental" or "patch" code) ("object" or "executable" form). The software code or instructions may be stored in a computer-readable storage medium, and when executed, may cause a machine to perform the described functions or operations, and include any mechanism for storing information in a form accessible to a machine (e.g., a computing device, an electronic system, etc.), such as a recordable or non-recordable medium (e.g., read-only memory (ROM), random access memory (RAM), magnetic disk storage medium, optical storage medium, flash device, etc.).

[0063] The exemplary methods described in this application can be implemented at least in part by a machine or a computer. In some embodiments, a computer-readable storage medium stores computer program instructions that, when run by a processor, cause the processor to execute the fNIRS-based auxiliary analysis method for mental illness types described in various embodiments of this application.

[0064] The implementation of such a method may include software code, such as microcode, assembly language code, high-level language code, etc. Various software programming techniques can be used to create various programs or program modules. For example, a program part or a program module can be designed using or with the help of Java, Python, C, C++, assembly language, or any known programming language. One or more of such software parts or modules can be integrated into a computer system and / or a computer-readable medium. Such software code can include computer-readable instructions for executing various methods. This software code can form part of a computer program product or a computer program module. Additionally, in an example, the software code can be tangibly stored on one or more volatile, non-transitory, or non-volatile tangible computer-readable media, such as during execution or at other times. Examples of such tangible computer-readable media can include, but are not limited to, hard disks, removable disks, removable optical discs (such as optical discs and digital video discs), cassette tapes, memory cards or memory sticks, random access memory (RAM), read-only memory (ROM), etc.

[0065] Figure 3 The structural schematic diagram of the auxiliary analysis device according to an embodiment of this application is shown. The auxiliary analysis device 300 includes an interface 301 and a processor 302. The interface 301 is configured to obtain the first blood oxygen concentration data of the corresponding concerned brain regions of the subject during the execution of the first composite task. The processor 302 is configured to compare the first blood oxygen concentration data with the preset second blood oxygen concentration data, and perform auxiliary analysis on the mental illness predisposition of the subject based on the comparison result; wherein, the first composite task includes at least two types of tasks. In this way, mental illnesses with similar symptoms can be accurately distinguished, and an objective index can be provided for the auxiliary analysis of mental illnesses.

[0066] In some embodiments, the processor 302 in the above-mentioned auxiliary analysis device 300 in this application can also execute the steps of the fNIRS-based auxiliary analysis method for mental illness types described in the foregoing embodiments.

[0067] In addition, although exemplary embodiments have been described herein, the scope includes any and all embodiments based on the present application that have equivalent elements, modifications, omissions, combinations (e.g., schemes that cross various embodiments), adaptations, or alterations. The elements in the claims will be broadly construed based on the language employed in the claims and are not limited to the examples described in this specification or during the implementation of the present application, and the examples will be construed as non-exclusive. Thus, this specification and the examples are intended to be considered only as examples, and the true scope and spirit are indicated by the following claims and the full scope of their equivalents.

[0068] The above description is intended to be illustrative rather than restrictive. For example, the above examples (or one or more of their aspects) can be used in combination with each other. For example, those of ordinary skill in the art can use other embodiments when reading the above description. Additionally, in the above detailed description, various features can be grouped together to simplify the present application. This should not be construed as an intention that a disclosed feature that is not claimed is necessary for any claim. On the contrary, the subject matter of the present application can be less than all the features of a particular disclosed embodiment. Thus, the claims are incorporated herein as examples or embodiments into the detailed description, where each claim independently serves as a separate embodiment, and it is contemplated that these embodiments can be combined with each other in various combinations or permutations. The scope of the present application should be determined with reference to the appended claims and the full scope of the equivalent forms empowered by these claims.

[0069] The above embodiments are only exemplary embodiments of the present application and are not used to limit the present application. The protection scope of the present application is defined by the claims. Those skilled in the art can make various modifications or equivalent substitutions within the essence and protection scope of the present application, and such modifications or equivalent substitutions should also be regarded as falling within the protection scope of the present application.

Claims

1. An auxiliary analysis method for mental illness types based on fNIRS, characterized in that, The auxiliary analysis method includes: obtaining first blood oxygen concentration data of a brain region of interest corresponding to a subject during the execution of a first composite task; using a processor to compare the first blood oxygen concentration data with preset second blood oxygen concentration data, and performing auxiliary analysis on the tendency of the subject to have a mental illness based on the comparison result; wherein, the first composite task includes at least two types of tasks.

2. The auxiliary analysis method according to claim 1, wherein At least one type of task in the first composite task is selected from one of a resting state task, a VFT task, an N-back task, and an emotional Stroop task.

3. The auxiliary analysis method according to claim 1, wherein The first composite task is determined through the following processing, specifically including: obtaining third blood oxygen concentration data of a brain region of interest corresponding to patients with various mental illnesses during the execution of a second composite task, the second composite task including a resting state task, a VFT task, an N-back task, and an emotional Stroop task executed in sequence; using a processor to compare the third blood oxygen concentration data with fourth blood oxygen concentration data within a preset healthy reference level range to determine the type of a first task included in the first composite task, such that the first composite task can at least be used to distinguish whether the subject has a mental illness.

4. The auxiliary analysis method according to claim 1 or 3, characterized in that, The first composite task is determined based on the obtained third blood oxygen concentration data, and further includes: using a processor to perform a comparative analysis on the third blood oxygen concentration data among patients with various mental illnesses, and determining the type of a second task included in the first composite task according to the result of the comparative analysis, such that the second task can at least be used to distinguish at least two mental illnesses.

5. The auxiliary analysis method according to claim 1, wherein The auxiliary analysis method further includes: in the case where the first composite task includes a first task that can at least be used to distinguish whether the subject has a mental illness and a second task that can at least be used to distinguish at least two mental illnesses, the execution priority of the first task is higher than that of the second task.

6. The auxiliary analysis method according to any one of claims 1-3, characterized in that The auxiliary analysis method further includes: making a preliminary judgment on the illness condition of the subject, and determining the type and / or priority of each task in the first composite task according to the result of the preliminary judgment, specifically including at least one of the following methods: Method 1, in the case where the preliminary judgment result of the subject's illness condition is that the subject has a depressive tendency, the first composite task at least includes an N-back task and an emotional Stroop task, and the execution priority of each task is: N-back task > emotional Stroop task; Method 2, in the case where the preliminary judgment result of the subject's illness condition is that the subject has a schizophrenia or manic tendency, the first composite task at least includes a VFT task, an N-back task, and an emotional Stroop task, and the execution priority of each task is: VFT task > emotional Stroop task > N-back task; Method 3, in the case where the preliminary judgment result of the subject's illness condition is that the subject has an anxiety tendency, the first composite task at least includes a VFT task and an N-back task, and the execution priority of each task is: VFT task > N-back task; Method Four: When the preliminary judgment result of the disease condition of the subject indicates that the subject has an ADHD tendency, the first composite task at least includes the N-back task, the Emotional Stroop task, and the CPT task, and the execution priority of each task is: CPT task > Emotional Stroop task > N-back task.

7. The auxiliary analysis method according to claim 1, wherein, The auxiliary analysis of the mental illness tendency of the subject based on the comparison result specifically includes at least one of the following methods: Method One: Compare the first blood oxygen concentration data and the second blood oxygen concentration data of the subject when performing the resting-state task, and determine the activity coordination information and brain functional connection strength between the left and right brains of the patient to analyze the mental illness tendency of the subject; Method Two: Compare the first blood oxygen concentration data and the second blood oxygen concentration data of the subject when performing the VFT task, and determine the activation of the attention brain area to analyze the mental illness tendency of the subject; Method Three: Compare the first blood oxygen concentration data and the second blood oxygen concentration data of the subject when performing the N-back task, and combine the behavioral data of the patient when performing the N-back task to determine the activity pattern of the attention brain area to analyze the mental illness tendency of the subject; Method Four: Compare the first blood oxygen concentration data and the second blood oxygen concentration data of the subject when performing the Emotional Stroop task, and combine the behavioral data of the patient when performing the Emotional Stroop task to analyze the mental illness tendency of the subject.

8. The auxiliary analysis method according to claim 1, characterized in that It further includes: Obtain the electroencephalogram data collected by the subject during the execution of the first composite task; Based on the comparison result, combined with the electroencephalogram data of the subject during the execution of the first composite task, assist in analyzing the mental illness tendency of the subject.

9. The auxiliary analysis method according to claim 1, characterized in that The attention brain area at least includes the frontal lobe and the temporal lobe, and the auxiliary analysis method at least includes at least one of the following situations, Situation One: When the subject performs the resting-state task, the attention brain area is the inferior frontal gyrus; Situation Two: When the subject performs the VFT task, the attention brain area is the prefrontal lobe and / or the temporal lobe; Situation Three: When the subject performs the N-back task, the attention brain area is the prefrontal lobe; Situation Four: Determining the activation of the attention brain area when the subject performs the VFT task includes determining the activation of the frontal lobe and / or the temporal lobe.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it executes the auxiliary analysis method for the type of mental illness based on fNIRS according to any one of claims 1-9.

11. An apparatus for assisting in the analysis of mental illness types based on fNIRS, characterized in that, The device includes an interface and a processor, The interface is configured to: obtain the first blood oxygen concentration data of the attention brain area of the subject during the execution of the first composite task; The processor is configured to: compare the first blood oxygen concentration data with preset second blood oxygen concentration data, and assist in analyzing the tendency of the subject to have a mental illness based on the comparison result; wherein, the first composite task includes at least two types of tasks.

Images