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Classification of RR-Interval and Blood Pressure for Different Postures using KNN Algorithm

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJSIP) 바로가기
  • 간행물
    International Journal of Signal Processing, Image Processing and Pattern Recognition 바로가기
  • 통권
    Vol.5 No.1 (2012.03)바로가기
  • 페이지
    pp.13-20
  • 저자
    Indu Saini, Dilbag Singh, Arun Khosla
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A208813

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원문정보

초록

영어
Power spectral analysis of the heart rate and blood pressure variations has commonly used to provide indices of autonomic cardiovascular modulation, but the effect of changing posture from lying to standing on these variations and the interpretation of their power spectra is still largely in dispute. It was due to the reason that till now no study was made yet that clearly outlines the variations in terms of RR-interval and blood pressure series from lying to standing position. Thus the aim of this paper lies in the application of classifying the subjects based on their RR-intervals, systolic and diastolic blood pressure series, prior to spectral analysis, at two different physical activity related postures. In this paper K-Nearest Neighbor algorithm has been proposed as a classifier for classifying the subjects based on lying and standing postures. Here we also studied the classification accuracy achievable with a KNN classifier using three different methods (i) Euclidean (ii) City block and (iii) Correlation of calculating the nearest distance in order to propose the optimal one. Further an attempt has been made to evaluate each of these methods for five different values of K=1, 3, 5, 7 and 9 in order to propose the best fit value of K for classifying the subjects. After performing the comparative analysis between these three methods of distance metrics and for different values of K, it is found that K=1 is the best choice out of 3, 5, 7 and 9 and Correlation has been emerged as one of the optimal method for computing the nearest distance with highest classification accuracy of 98.60 % with K=1 for lying and 99.95 % with K=1 for standing postures.

목차

Abstract
 1. Introduction
 2. Methodology
  2.1 Overview of K-Nearest Neighbors Method
  2.2 Selection of Parameter K and Distance Metric
  2.3 Distance Metrics
 3. Results and Discussion
 4. Conclusion
 References

키워드

Classifier Nearest Neighbor Distance Metrics Postures

저자

  • Indu Saini [ Dr B R Ambedkar National Institute of Technology Jalandhar ]
  • Dilbag Singh [ Dr B R Ambedkar National Institute of Technology Jalandhar ]
  • Arun Khosla [ Dr B R Ambedkar National Institute of Technology Jalandhar ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
  • 설립연도
    2006
  • 분야
    공학>컴퓨터학
  • 소개
    1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업

간행물

  • 간행물명
    International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 간기
    격월간
  • pISSN
    2005-4254
  • 수록기간
    2008~2016
  • 십진분류
    KDC 505 DDC 605

이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.5 No.1

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