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Development of Safety Monitoring Program for Psychiatric Emergency Using Google Teachable Machine

구글 티처블머신을 활용한 정신과적 응급 대상자의 병실 안전 모니터링 프로그램 개발

  • 이은민 (전남대학교 간호대학 간호학과) ;
  • 김태훈 (전남대학교 간호대학 간호학과)
  • Received : 2022.12.15
  • Accepted : 2023.01.09
  • Published : 2023.01.31

Abstract

In this paper, a monitoring program that can automatically determine whether a patient admitted to an isolation room acts out of a stable state through a screen photographed in real time is described. The motion recognition model of this program was built by learning through transfer learning. 900 images were used for the three movements, and this program was developed for the web to support all environments. The model was determined with high accuracy to determine the state of the subject hospitalized in the isolation room, and can be applied by applying it to the existing isolation room monitoring system.

본 논문에서는 실시간으로 촬영된 화면을 통해 격리실에 입원한 대상자가 안정 상태에서 벗어난 행동을 하는지 자동으로 판단할 수 있는 모니터링 프로그램에 대해 설명한다. 본 프로그램의 동작인식 모델은 전이학습(Transfer Learning)을 통해 학습하여 구축되었다. 3개 동작에 대해 900장의 이미지가 사용되었으며, 본 프로그램은 모든 환경을 지원하기 위하여 웹용으로 개발되었다. 모델은 격리실에 입원한 대상자의 상태에 대해 높은 정확도로 판단하였으며, 기존의 격리실 모니터링 시스템에 응용하여 적용가능하다.

Keywords

References

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