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A Lifelog Posture Estimation Web Program Using Arduino and FSR402 Sensors

  • Ae-Ri Jung (School of Information Security, Daejeon University) ;
  • Min-Seok Song (School of Information Security, Daejeon University) ;
  • Hyun-Seo Shin (School of Information Security, Daejeon University) ;
  • Young-Bok Cho (Dept. of Computer Education, Andong National University)
  • Received : 2024.10.25
  • Accepted : 2024.11.26
  • Published : 2024.11.29

Abstract

In this paper, we propose a posture correction system using the Arduino FSR402 sensor and Skeleton Keypoint artificial intelligence model. In anticipation of the introduction of AI Digital Textbook (AIDT), which will be fully implemented from 2025 under the 2022 curriculum reform, the need for research to raise awareness of the risk of digital diseases among children and adolescents and to prevent them is emphasized. The proposed system learns the correct posture for each user based on their life log information and helps them maintain good posture by determining whether they are using a smart device correctly and guiding them. In particular, for children and adolescents who experience physical changes, it has the advantage of learning the changed body information from the Skeleton Keypoint artificial intelligence model to guide the appropriate posture, and it can be confirmed that the sensor's measurement value operates normally within the error range (average error 2.53%) in measuring the correct posture for each user.

본 논문에서는 아두이노 FSR402 센서와 Skeleton Keypoint 인공지능 모델을 이용한 자세 교정 시스템을 제안한다. 2022교육과정 개편에 따라 2025년부터 시행 예정인 인공지능 디지털교과서(AIDT: AI Digital Textbook)의 도입을 앞두고, 아동 및 청소년들의 디지털 질병 위험에 대한 경각심을 일깨우고, 이를 예방하기 위한 연구의 필요성을 강조되고 있다. 제안하는 시스템은 개인의 라이프 로그 정보를 기반으로 사용자별 올바른 자세를 학습하고, 스마트 디바이스 사용 시 올바른 자세 여부를 판별하여 안내함으로써 바른 자세를 유지할 수 있도록 지원한다. 특히 신체적 변화가 발생하는 아동 및 청소년의 경우, 변화된 신체 정보를 Skeleton Keypoint 인공지능 모델에서 학습하여 적절한 자세를 안내할 수 있는 장점이 있고, 사용자별 올바른 자세 측정에서 센서의 측정값이 오차범위(평균오차 2.53%) 내에서 정상적으로 동작되는 것을 확인할 수 있다.

Keywords

References

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