KIPS Transactions on Software and Data Engineering (정보처리학회논문지:소프트웨어 및 데이터공학)

Korea Information Processing Society (한국정보처리학회)
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Feedback-RFC Model to Individualize Heartbeat Standards

개인별 심박수 기준을 설정하기 위한 피드백-RFC 모델

  • Received : 2016.03.28
  • Accepted : 2016.07.14
  • Published : 2017.02.28
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Abstract

Many of the wearable smart fitness devices provide services related to users' heartbeat rates. These services use fixed standards which have been pre-determined based on statistical data. However, because body conditions significantly differ between individuals, the services applying fixed standards to all individuals are not reliable. This paper proposes the Feedback-RFC model which adapts heartbeat standards to individual users' exercise abilities and also proposes a method to implement the model. This paper also shows the effectiveness of the Feedback-RFC model by collecting heartbeat data from 12 participants and evaluating the model with the data.

많은 웨어러블 스마트 피트니스 장치들이 심박수와 관련된 서비스를 제공한다. 이러한 서비스는 통계를 기반으로 사전 결정한 고정 수치를 기준으로 이용한다. 그러나 사람들의 신체조건은 개개인마다 다르기 때문에, 모든 개개인을 같은 기준으로 적용하는 서비스는 신뢰성이 낮다. 본 논문에서는 사용자의 운동 능력에 맞추어 심박수의 기준이 변동하는 피드백-RFC 모델과, 모델을 구현하는 방법을 제안한다. 그리고 12명의 실험참가자들로부터 심장박동 데이터를 수집하여 모델을 평가함으로써 제안 모델의 효용성을 보인다.

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References

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