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Original Article

Development of urination recognition technology based on Support Vector Machine using a smart band

첫 페이지 보기
  • 발행기관
    한국운동재활학회 바로가기
  • 간행물
    JER SCOPUS KCI 등재 바로가기
  • 통권
    Vol.17 No.4 (2021.08)바로가기
  • 페이지
    pp.287-292
  • 저자
    Hyun Seok Na, Khae Hawn Kim
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A398427

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원문정보

초록

영어
The purpose of this study was to explore the feasibility of a urination management system by developing a smart band-based algorithm that recognizes the urination interval of women. We designed a device that recognizes the time and interval of urination based on the patient’s spe-cific posture and posture changes. The technology used for recognition applied the Radial Basis Function kernel-based Support Vector Ma-chine, a teaching and learning method that facilitates multidimensional analysis by simultaneously judging the characteristics of complex learning data. In order to evaluate the performance of the proposed recognition technique, we compared actual urination and device- sensed urination. An experiment was performed to evaluate the perfor-mance of the recognition technology proposed in this study. The effica-cy of smart band monitoring urination was evaluated in 10 female pa-tients without urination problems. The entire experiment was performed over a total of 3 days. The average age of the participants was 28.73 years (26–34 years), and there were no signs of dysuria. The final accuracy of the algorithm was calculated based on clinical guidelines for urologists. The experiment showed a high average accuracy of 91.0%, proving the robustness of the proposed algorithm. This urination behavior recogni-tion technique shows high accuracy and can be applied in clinical set-tings to characterize urination patterns in female patients. As wearable devices develop and become more common, algorithms that detect specific sequential body movement patterns that reflect specific physi-ological behaviors could become a new methodology to study human physiological behavior.

목차

ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
Optimize parameters for upgrading classification boundaries
Statistical analysis
RESULTS
DISCUSSION
CONFLICT OF INTEREST
ACKNOWLEDGMENTS
REFERENCES

키워드

Female urinary patient Urination recognition Urination management system Mobile voiding chart Support vector machine

저자

  • Hyun Seok Na [ Department of Urology, Chungnam National University Hospital, Chungnam National University College of Medicine, Daejeon, Korea ]
  • Khae Hawn Kim [ Department of Urology, Chungnam National University Sejong Hospital, Chungnam National University College of Medicine, Sejong, Korea ] Corresponding Author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    한국운동재활학회 [Korean Society of Exercise Rehabilitation]
  • 설립연도
    2004
  • 분야
    의약학>재활의학
  • 소개
    한국운동재활학회는 사회적, 정신적, 신체적 통합건강복지 이론의 학술연구와 회원 상호간 학술교류 증진을 장려함으로써 학문적 발전을 도모하고 나아가 건강복지선진국 발전에 이바지함을 목적으로 한다.

간행물

  • 간행물명
    JER [Journal of Exercise Rehabilitation]
  • 간기
    격월간
  • pISSN
    2288-176X
  • eISSN
    2288-1778
  • 수록기간
    2013~2026
  • 등재여부
    SCOPUS,KCI 등재
  • 십진분류
    KDC 517 DDC 613

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