KR-20260065090-A - Apparatus and methods for supporting child development assessment

KR20260065090AKR 20260065090 AKR20260065090 AKR 20260065090AKR-20260065090-A

Abstract

An apparatus and method for evaluating child development by analyzing images captured by a user through an artificial neural network are disclosed. A child development evaluation support apparatus according to one embodiment may include a communication unit that communicates with a user terminal; and an analysis unit that analyzes at least one of survey data and image data received through the communication unit through an artificial neural network to analyze the level of child development.

Inventors

임재현

Assignees

루먼랩 주식회사

Dates

Publication Date: 20260508
Application Date: 20241031

Claims (16)

A communication unit that performs communication with a user terminal; and A child development assessment support device comprising an analysis unit that analyzes at least one of the survey data and image data received through the communication unit through an artificial neural network to analyze the child development level.
In Article 1, The above analysis unit A child development assessment support device that analyzes the above survey data to generate linked question data for question items with specific answers entered and transmits it to a user terminal.
In Article 1, The above analysis unit A child development assessment support device that transmits video recording guide information for analyzing the child development level to the user terminal.
In Paragraph 3, The above analysis unit A child development evaluation support device that determines an evaluation area based on the results of the child development level analyzed through the above survey data, and transmits video shooting guide information for the determined evaluation area to the user terminal.
In Article 1, The artificial neural network above A pose estimation neural network trained to estimate human pose from video data, A neural network for estimating facial expressions trained to estimate human facial expressions and A child development assessment support device, comprising at least one of a picture estimation neural network for estimating picture similarity.
In Article 4, The above analysis unit A child development assessment support device that generates additional question data based on video shooting guide information for the above-determined assessment area and transmits it to a user terminal.
In Article 1, The above analysis unit A child development assessment support device that transmits survey data, video data, and analysis results to an evaluator user terminal when the analysis result of the child's development level is above a predetermined standard.
In Article 7, The above analysis unit A child development assessment support device that receives feedback data from the above-mentioned evaluator user terminal and generates final result data based on the feedback data.
One or more processors, and A method performed in a computing device having a memory for storing one or more programs executed by one or more processors, wherein A step of receiving at least one of survey data and image data from a user terminal; and A child development assessment support method comprising the step of analyzing at least one of the received survey data and image data through an artificial neural network to analyze the child development level.
In Article 9, The above analysis step A child development assessment support method that analyzes the above survey data to generate linked question data for question items with specific answers entered and transmits it to a user terminal.
In Article 9, The above analysis step A child development assessment support method that transmits video recording guide information for analyzing the child development level to the user terminal.
In Article 11, The above analysis step A child development assessment support method that determines an assessment area based on the results of the child development level analyzed through the above survey data, and transmits video shooting guide information for the determined assessment area to the user terminal.
In Article 9, The artificial neural network above A pose estimation neural network trained to estimate human pose from video data, A neural network for estimating facial expressions trained to estimate human facial expressions and A child development assessment support method, comprising at least one picture estimation neural network for estimating picture similarity.
In Article 12, The above analysis step A child development assessment support method that generates additional question data based on video recording guide information for the above-determined assessment area and transmits it to a user terminal.
In Article 9, The above analysis step A child development assessment support method that transmits survey data, video data, and analysis results to an evaluator user terminal when the analysis result of the child development level is above a predetermined standard.
In Article 15, The above analysis step A child development assessment support method that receives feedback data from the above-mentioned evaluator user terminal and generates final result data based on the feedback data.

Description

Apparatus and methods for supporting child development assessment The present invention relates to a device and method for evaluating child development by analyzing images captured by a user through an artificial neural network, as a technology to support child development evaluation. Traditional child development assessments have primarily been conducted offline through face-to-face interactions between caregivers, children, and professionals, or by simply converting existing offline surveys to an online format. These methods suffer from low user accessibility and a lack of speed. Furthermore, there is a significant risk that children may exhibit developmental states different from their usual behavior due to tension and stress caused by undergoing testing in an unfamiliar environment. Additionally, as caregivers respond to the survey based on their own experiences, there is a possibility that their responses may differ from the facts, and evaluation criteria may vary among examiners, which poses a risk of reduced objectivity and reliability of the results. To address these issues, the need was raised to develop a new form of evaluation method. FIG. 1 is a configuration diagram of a child development assessment support device according to one embodiment. FIGS. 2 to 4 are exemplary diagrams for explaining the operation of a child development assessment support device according to one embodiment. FIG. 5 is a flowchart illustrating a child development assessment support method according to one embodiment. Hereinafter, an embodiment of the present invention will be described in detail with reference to the attached drawings. In describing the present invention, specific descriptions of related known functions or configurations will be omitted if it is determined that such detailed descriptions may unnecessarily obscure the essence of the present invention. Furthermore, the terms described below are defined considering their functions in the present invention, and these may vary depending on the intentions or conventions of the user or operator. Therefore, their definitions should be based on the content throughout this specification. Hereinafter, embodiments of a child development assessment support device and method will be described in detail with reference to the drawings. FIG. 1 is a configuration diagram of a child development assessment support device according to one embodiment. Referring to FIG. 1, a child development assessment support device (100) may include a communication unit (110) that communicates with a user terminal and an analysis unit (120) that analyzes at least one of the survey data and image data received through the communication unit (110) through an artificial neural network to analyze the child development level. Traditional child development assessments have primarily been conducted offline through face-to-face meetings involving caregivers, children, and experts, or by simply converting existing offline surveys into an online format. This approach presents the problem of low accessibility, as development assessment centers are concentrated in Seoul and the metropolitan area. Furthermore, it lacks speed as a single assessment takes several hours to complete, and there is a high likelihood that the reliability of the results will be compromised since the child is being tested in an unfamiliar environment. In particular, various issues can arise depending on the specific participants, such as the testing environment, caregivers, and the assessors. For example, due to issues with the testing environment, children often feel tension and stress in unfamiliar surroundings, making it difficult for them to demonstrate their typical developmental status. In particular, when undergoing long-duration testing (2-3 hours or more) at a developmental center, children can easily become fatigued, making it difficult to assess their usual developmental progress. Furthermore, regarding the caregiver, they evaluate a child's developmental status based on their own experiences. While there is no issue with clearly good or bad aspects, there is a high likelihood that they will provide inaccurate responses regarding ambiguous areas of development. In addition, if the survey is conducted under tight time constraints, accuracy may be compromised due to the pressure to hastily select answers. In addition, there is a problem of subjective variation depending on the examiner. Ideally, child development tests should be administered by the same examiner according to consistent standards, but with existing technology, variations occur among examiners, posing a risk of reduced objectivity in the results. For example, a child development assessment support device (100) can assess a child's developmental level online based on video and an artificial neural network (AI). The child development assessment support device (100) can combine child development-related survey data collected through caregivers (data collecti