KIPS Transactions on Computer and Communication Systems (정보처리학회논문지:컴퓨터 및 통신 시스템)

Korea Information Processing Society (한국정보처리학회)
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Eating Activity Detection and Meal Time Estimation Using Structure Features From 6-axis Inertial Sensor

6축 관성 센서에서 구조적 특징을 이용한 식사 행동 검출 및 식사 시간 추론

  • Received : 2017.11.23
  • Accepted : 2018.07.13
  • Published : 2018.08.31
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Abstract

In this study, we propose an algorithm to detect eating activity and estimation mealtime using 6-axis inertial sensor. The eating activity is classified into three types: food picking, food eating, and lowering. The feature points of the gyro signal are selected for each gesture, and the eating activity is detected when each feature point appears in the sequence. Morphology technique is used to post-process to detect meal time. The proposed algorithm achieves the accuracy of 94.3% and accuracy of 84.1%.

본 연구에서는 6축 센서를 이용하여 식사 행동을 검출하고 식사 시간을 추론하는 알고리즘을 제안한다. 식사 행동을 음식을 집는 동작, 음식을 먹는 동작, 팔을 내려놓는 동작으로 분류하고, 각 동작 별로 자이로 신호의 특징점을 선정하고 특징점이 순서대로 나타날 경우 식사 행동을 검출한다. 제안한 알고리즘은 정확도 94.3%와 정밀도 84.1%를 달성하였다.

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References

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