Abstract: Disclosed is a method of identifying dementia by at least one processor of a device. The method includes performing a first task that causes a first object to be displayed on a first region of a screen displayed on a user terminal; and when a preset condition is satisfied, performing a second task that causes at least one object, which induces the user's gaze, to be displayed instead of the first object on the screen of the user terminal.

Abstract: A diabetic foot management system according to one aspect includes a diabetic foot monitoring apparatus configured to measure user's foot condition information; and a diabetic foot analysis apparatus configured to determine a degree of progression of user's diabetic foot ulcer from the measured foot condition information using a machine learning-based diabetic foot determination model.

Abstract: A method of identifying dementia is disclosed that includes causing a user terminal to display an N-th screen including a plurality of objects. The user terminal may further display an N+1-th screen with the objects rearranged at positions on the N+1-th screen which are different from positions of the objects included in the N-th screen when an N-th selection input of selecting any one from among the objects included in the N-th screen is received. When an N+1-th selection input for selecting any one from among the objects included in the N+1-th screen is received, a third task of determining whether an answer of the N+1-th selection input is correct is performed based on whether the object selected from the N+1-th selection input is the same as at least one object selected from at least one previous selection input including the N-th selection input.

Abstract: A method for identifying mild cognitive impairment by at least one processor of an apparatus according to some embodiments of the present disclosure is disclosed. the method comprises performing a task of acquiring digital biomarker data for identifying mild cognitive impairment of a user of a user terminal; performing a preliminary task to allow the user to check the task before performing the task; and acquiring gaze information of the user in conjunction with performing the task and the preliminary task; wherein the gaze information is used when determining displayed information in the preliminary task, and used when identifying mild cognitive impairment of the user in the task.

Abstract: Disclosed is a method of training the dementia identification model. More particularly, the method may include obtaining test result data through at least one of a first task related to Stroop test, a second task related to a computational power test, and a third task related to a memory test; and labeling the test result data with a score value to train the dementia identification model.

Abstract: Disclosed is a method of identifying, by at least one processor of a device, a cognitive function state of a user. The method may include inputting user information, at least one voice data, and speech time information related to the at least one voice data to a cognitive function state identification model, and identifying a cognitive function state of the user based on first output data that is output by the cognitive function state identification model.

Abstract: Disclosed is a method of identifying, by at least one processor of a device, a cognitive function state of a user. The method may include inputting user information, at least one voice data, and speech time information related to the at least one voice data to a cognitive function state identification model, and identifying a cognitive function state of the user based on first output data that is output by the cognitive function state identification model.

Abstract: Disclosed is a method of identifying dementia by at least one processor of a device. The method may include obtaining content analysis information and voice activity analysis information by using a plurality of first voice data and second voice data which have been obtained by performing a plurality of tasks in a user terminal, and identifying dementia by inputting the content analysis information and the voice activity analysis information to a dementia identification model.

Abstract: Disclosed is a method of identifying dementia by at least one processor of a device according to some embodiments of the present disclosure. The method may include obtaining a plurality of result data of a user obtained by performing a plurality of tests through a user terminal, calculating a score value by inputting the plurality of result data to a dementia identification model, and determining whether the user has dementia based on whether the score value is greater than a first threshold value.

Abstract: Disclosed is a method of identifying dementia by at least one processor of a device. The method includes performing a first task that causes a first object to be displayed on a first region of a screen displayed on a user terminal; and when a preset condition is satisfied, performing a second task that causes at least one object, which induces the user's gaze, to be displayed instead of the first object on the screen of the user terminal.

Abstract: Disclosed is a method of identifying dementia using at least one processor of a device according to some embodiments of the present disclosure. More particularly, the method may include performing a first task of causing for a user terminal to display a first screen including a sentence; performing a second task of causing for the user terminal to acquire an image including user’s eyes in association with displaying a moving object instead of the first screen; and performing a third task of causing for the user terminal to acquire a recording file in association with displaying a second screen in which the sentence is hidden, wherein the first task includes a sub-task of causing color of at least one word constituting the sentence included in the first screen to be sequentially changed.

Abstract: Disclosed is a method of training the dementia identification model. More particularly, the method may include obtaining test result data through at least one of a first task related to Stroop test, a second task related to a computational power test, and a third task related to a memory test; and labeling the test result data with a score value to train the dementia identification model.

Abstract: A thermoelectric module with high efficiency is provided. The thermoelectric module may include a first substrate including a plurality of first electrodes, a second substrate provided opposite the first substrate and including a plurality of second electrodes, a plurality of thermoelectric devices provided between the first substrate and the second substrate and electrically connected to the first electrodes and the second electrodes, and a wire connection hole configured to penetrate through at least one of the first substrate and the second substrate and expose a portion of at least one surface of the first electrodes and the second electrodes.

Abstract: A thermoelectric module with high efficiency is provided. The thermoelectric module may include a first substrate including a plurality of first electrodes, a second substrate provided opposite the first substrate and including a plurality of second electrodes, a plurality of thermoelectric devices provided between the first substrate and the second substrate and electrically connected to the first electrodes and the second electrodes, and a wire connection hole configured to penetrate through at least one of the first substrate and the second substrate and expose a portion of at least one surface of the first electrodes and the second electrodes.

Abstract: A photovoltaic apparatus includes a support substrate; a back electrode layer on the support substrate; a light absorbing layer on the back electrode layer; and a front electrode layer on the light absorbing layer, wherein the support substrate comprises: a base layer; a first stepped portion on the base layer; and a second stepped portion disposed aside the first stepped portion on the base layer, and wherein the second stepped portion is thicker than the first stepped portion.

Abstract: A photovoltaic apparatus includes a support substrate; a back electrode layer on the support substrate; a light absorbing layer on the back electrode layer; and a front electrode layer on the light absorbing layer, wherein the support substrate comprises: a base layer; a first stepped portion on the base layer; and a second stepped portion disposed aside the first stepped portion on the base layer, and wherein the second stepped portion is thicker than the first stepped portion.