서브메뉴
검색
Critical Analysis of the Reliability and Prediction Error of a Novel Smartphone Application for Measuring Body Composition- [electronic resource]
Critical Analysis of the Reliability and Prediction Error of a Novel Smartphone Application for Measuring Body Composition- [electronic resource]
상세정보
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20240214100434
- ISBN
- 9798380326186
- DDC
- 612
- 저자명
- Metoyer, Casey.
- 서명/저자
- Critical Analysis of the Reliability and Prediction Error of a Novel Smartphone Application for Measuring Body Composition - [electronic resource]
- 발행사항
- [S.l.]: : The University of Alabama., 2023
- 발행사항
- Ann Arbor : : ProQuest Dissertations & Theses,, 2023
- 형태사항
- 1 online resource(93 p.)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-03, Section: A.
- 주기사항
- Advisor: Esco, Michael R.;Fedewa, Michael V.
- 학위논문주기
- Thesis (Ph.D.)--The University of Alabama, 2023.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 초록/해제
- 요약A smartphone application was recently developed that measures body composition from a 2-dimensional image of a standing person (%FatIMAGE). Three experiments were performed to 1) determine the reliability of %FatIMAGE in two different body positions and days, 2) determine the reliability of %FatIMAGE across different cameras, room lighting levels, and colored backgrounds, and 3) assess the potential sources of error related to %Fat estimation with bioimpedance, skinfold, and IMAGE. In the first study, %FatIMAGE was measured in the anterior (ANTDay1) and posterior (POSTDay1) positions, then again within 48 hours of the first visit (POSTDay2). The ANTDay1 was significantly lower compared to the reference, whereas the POSTDay2 was not. In the second study, %FatIMAGE was estimated in different megapixel cameras (12MP, 8MP, 5MP, and 0.7MP), different room lighting conditions (i.e., low=LL, medium=ML, ambient=AL, and bright light=BL), and different colored backgrounds (White=WB, Black=BB, Green=GnB, Orange=OB, and Gray=GyB). Conditions were compared to a reference (8MP, AL, and WB). The 0.7MP was significantly higher than the reference, whereas the 12MP and 5MP were not. The LL was significantly higher than the reference, whereas the BL and ML were not. The BB, GnB, and GyB were significantly higher than the WB, whereas the OB was not. In a third study, %Fat was measured via bioimpedance, skinfold, %FatIMAGE, and a criterion 4- compartment model. The constant error (CE) was calculated (%Fat condition - criterion) for each method (SKFERROR,BIAERROR., and IMAGEERROR). The CE was correlated with markers of physical activity (PA) and muscular fitness (MF): the International physical activity questionnaire (IPAQT, IPAQV, IPAQM); Perceived functional ability questionnaire (1mileSUB and 3mileSUB); Physical Activity Rating questionnaire (PA-R): handgrip test (HG); and push-up test (PU). SKFERROR displayed a small correlation with PU, while IPAQV, 1mileSUB, 3mileSUB, PA-R, and PU were associated with IMAGEERROR. Regression analyses indicated that only PU contributed to the model for SKFERROR and IMAGEERROR. In conclusion, the IMAGE produced acceptable reliability across different camera, lighting, and background conditions but attention should be paid to clothing color in contrast with background color. In addition, further evaluation of MF measures is recommended, as higher PU were associated with greater IMAGEERROR.
- 일반주제명
- Kinesiology.
- 일반주제명
- Biomedical engineering.
- 일반주제명
- Web studies.
- 키워드
- Body composition
- 키워드
- Image
- 키워드
- Prediction rrror
- 키워드
- Reliability
- 키워드
- Technology
- 기타저자
- The University of Alabama Human Performance
- 기본자료저록
- Dissertations Abstracts International. 85-03A.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
008240612s2023 us |||||||||||||||c||eng d■001000016932254
■00520240214100434
■006m o d
■007cr#unu||||||||
■020 ▼a9798380326186
■035 ▼a(MiAaPQ)AAI30490589
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a612
■1001 ▼aMetoyer, Casey.
■24510▼aCritical Analysis of the Reliability and Prediction Error of a Novel Smartphone Application for Measuring Body Composition▼h[electronic resource]
■260 ▼a[S.l.]:▼bThe University of Alabama. ▼c2023
■260 1▼aAnn Arbor :▼bProQuest Dissertations & Theses, ▼c2023
■300 ▼a1 online resource(93 p.)
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-03, Section: A.
■500 ▼aAdvisor: Esco, Michael R.;Fedewa, Michael V.
■5021 ▼aThesis (Ph.D.)--The University of Alabama, 2023.
■506 ▼aThis item must not be sold to any third party vendors.
■520 ▼aA smartphone application was recently developed that measures body composition from a 2-dimensional image of a standing person (%FatIMAGE). Three experiments were performed to 1) determine the reliability of %FatIMAGE in two different body positions and days, 2) determine the reliability of %FatIMAGE across different cameras, room lighting levels, and colored backgrounds, and 3) assess the potential sources of error related to %Fat estimation with bioimpedance, skinfold, and IMAGE. In the first study, %FatIMAGE was measured in the anterior (ANTDay1) and posterior (POSTDay1) positions, then again within 48 hours of the first visit (POSTDay2). The ANTDay1 was significantly lower compared to the reference, whereas the POSTDay2 was not. In the second study, %FatIMAGE was estimated in different megapixel cameras (12MP, 8MP, 5MP, and 0.7MP), different room lighting conditions (i.e., low=LL, medium=ML, ambient=AL, and bright light=BL), and different colored backgrounds (White=WB, Black=BB, Green=GnB, Orange=OB, and Gray=GyB). Conditions were compared to a reference (8MP, AL, and WB). The 0.7MP was significantly higher than the reference, whereas the 12MP and 5MP were not. The LL was significantly higher than the reference, whereas the BL and ML were not. The BB, GnB, and GyB were significantly higher than the WB, whereas the OB was not. In a third study, %Fat was measured via bioimpedance, skinfold, %FatIMAGE, and a criterion 4- compartment model. The constant error (CE) was calculated (%Fat condition - criterion) for each method (SKFERROR,BIAERROR., and IMAGEERROR). The CE was correlated with markers of physical activity (PA) and muscular fitness (MF): the International physical activity questionnaire (IPAQT, IPAQV, IPAQM); Perceived functional ability questionnaire (1mileSUB and 3mileSUB); Physical Activity Rating questionnaire (PA-R): handgrip test (HG); and push-up test (PU). SKFERROR displayed a small correlation with PU, while IPAQV, 1mileSUB, 3mileSUB, PA-R, and PU were associated with IMAGEERROR. Regression analyses indicated that only PU contributed to the model for SKFERROR and IMAGEERROR. In conclusion, the IMAGE produced acceptable reliability across different camera, lighting, and background conditions but attention should be paid to clothing color in contrast with background color. In addition, further evaluation of MF measures is recommended, as higher PU were associated with greater IMAGEERROR.
■590 ▼aSchool code: 0004.
■650 4▼aKinesiology.
■650 4▼aBiomedical engineering.
■650 4▼aWeb studies.
■653 ▼aBody composition
■653 ▼aImage
■653 ▼aPrediction rrror
■653 ▼aReliability
■653 ▼aSmartphone application
■653 ▼aTechnology
■690 ▼a0575
■690 ▼a0541
■690 ▼a0646
■71020▼aThe University of Alabama▼bHuman Performance.
■7730 ▼tDissertations Abstracts International▼g85-03A.
■773 ▼tDissertation Abstract International
■790 ▼a0004
■791 ▼aPh.D.
■792 ▼a2023
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16932254▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202402▼f2024
