Calculation of Percent Body Fat by Analyzing Virtual Body Models
Calculation of Percent Body Fat by Analyzing Virtual Body Models
批准号:
9099872
负责人:
JAMES K HAHN
金额:
$19.43万
依托单位国家:
美国
项目类别:
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-07-01 至 2019-05-31
关键词:
AdherenceAgeAirAlgorithmsAreaArtificial IntelligenceBehavior TherapyBeliefBody CompositionBody SizeBody SurfaceBody Weight decreasedBody fatBody mass indexChildChronic DiseaseClientClinicalClinical ResearchDataDatabasesDevelopmentDiagnosisDiseaseEpidemiologic StudiesEquipmentFatty acid glycerol estersFutureGoalsGrowthGuidelinesHealthHealth Care CostsHeart DiseasesHumanHuman bodyImageryIncentivesIndividualInterventionLeadLinkMachine LearningMalignant NeoplasmsMapsMeasurementMeasuresMedicalMethodsModelingMonitorMotionMotivationMuscleNon-Insulin-Dependent Diabetes MellitusObesityOutcomeOverweightParticipantPatientsPatternPerceptionPlethysmographyPublic HealthReportingResearchRiskRoleScanningSelf PerceptionSeriesShapesStrokeSurfaceSystemTechniquesTechnologyTimeTrainingUnderweightVariantVisualWaterWeightWeights and Measuresbasebody densitybody volumecostcost effectivedata miningdensitydisorder risklymphatic circulationnovelnovel strategiesobesity treatmentpreferencepublic health researchreconstructionsexstudy populationtoolvirtualweight loss intervention
中文摘要
英文摘要
DESCRIPTION (provided by applicant): Excess body fat is a key underlying factor in the development of numerous chronic diseases, including type II diabetes, heart disease, stroke, and cancer. The AMA recently declared that obesity, itself, is a disease. Most epidemiologic studies utilize Body Mass Index (BMI) to classify people as underweight, normal, overweight, or obese because it is a convenient and simple method that has been shown to correlate with disease risk. Since the majority of the health risks associated with obesity are more directly linked to an overabundance of body fat than weight, measuring body fat is essential for more precise guidelines. However, accurate methods of assessing body fat are expensive, inconvenient, and require immobile equipment. Consequently, the AMA has called for more cost effective and convenient methods to assess body composition to assist doctors in their assessment and treatment. Virtual modeling of humans in particular has provided ways to scan and analyze the body and its motion. Supervised Machine Learning (SML), a sub-field of artificial intelligence, has made great progress in taking measured data to infer new relationships. It is our belief that virtual modeling and SML can provide the techniques necessary to conveniently and accurately calculate the percentage of body fat (%BF) and to provide new tools in treating obesity based on body shapes. The project will develop a system that uses commercially available depth cameras such as the Microsoft Kinect(r) to capture the surface of the human body. This will be accomplished by developing a new algorithm to perform deformable registration of several RGB-Depth views of the body. A new algorithm that uses SML will be developed to calculate percentage body fat using the surface data. The system will be trained and validated by collecting data from a number of subjects. The surface captured will be used to explore the role of visual body representation in motivation and adherence. The developed systems can be implemented in clinical or personal settings and be utilized as a public health research tool and deployed widely given the low-cost of the hardware required. In addition to the immediate impact that the system will have on managing obesity, the project will have a broad impact on a number of areas. A large database of such shapes captured over time may lead to ways to predict how an individual's body shape will change given a particular intervention. Certain medical conditions that result in body shape change, such as those involving lymphatic circulations, may be diagnosed and tracked more easily. Growth patterns of children may be tracked by change of body shapes. Further research can be conducted to determine the effect of body shape on %BF using data mining techniques.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
DOI:
10.3390/ejihpe10020043
发表时间:
2020-06
期刊:
European journal of investigation in health, psychology and education
影响因子:
--
作者:
[Hudson GM, Lu Y, Zhang X, Hahn J, Zabal JE, Latif F, Philbeck J]
通讯作者:
Philbeck J
Evaluation of performance, acceptance, and compliance of an auto-injector in healthy and rheumatoid arthritic subjects measured by a motion capture system.
通过运动捕捉系统测量健康和类风湿关节炎受试者的自动注射器的性能、接受度和依从性的评估。
DOI:
10.2147/ppa.s160394
发表时间:
2018
期刊:
Patient preference and adherence
影响因子:
2.2
作者:
[Xiao,Xiao, Li,Wei, Clawson,Corbin, Karvani,David, Sondag,Perceval, Hahn,JamesK]
通讯作者:
Hahn,JamesK
Advancing 3D optical body surface scan technology to assess physiological and psychological effects in highly obese population
-
批准号:10455037
-
项目类别:
-
资助金额:$58.6万
-
财政年份:2021
-
负责人:JAMES K HAHN
-
依托单位:
Advancing 3D optical body surface scan technology to assess physiological and psychological effects in highly obese population
-
批准号:10680550
-
项目类别:
-
资助金额:$56.48万
-
财政年份:2021
-
负责人:JAMES K HAHN
-
依托单位:
Advancing 3D optical body surface scan technology to assess physiological and psychological effects in highly obese population
-
批准号:10280172
-
项目类别:
-
资助金额:$59.3万
-
财政年份:2021
-
负责人:JAMES K HAHN
-
依托单位:
Neonatal Endotracheal Intubation: Enhancing Training Through Computer Simulation and Automated Evaluation
-
批准号:10194566
-
项目类别:
-
资助金额:$31.49万
-
财政年份:2017
-
负责人:JAMES K HAHN
-
依托单位:
国内基金
海外基金
登录
查看更多内容
补阳还五汤通过AGE-RAGE通路调控脓毒症免疫失衡的机制与转化研究
-
批准号:JCZRLH202601523
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2026
-
负责人:
-
依托单位:
靶向递送一氧化碳调控AGE-RAGE级联反应促进糖尿病创面愈合研究
-
批准号:JCZRQN202500010
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2025
-
负责人:
-
依托单位:
对香豆酸抑制AGE-RAGE-Ang-1通路改善海马血管生成障碍发挥抗阿尔兹海默病作用
-
批准号:2025JJ70209
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2025
-
负责人:雷芬芳
-
依托单位:
AGE-RAGE通路调控慢性胰腺炎纤维化进程的作用及分子机制
-
批准号:--
-
项目类别:面上项目
-
资助金额:--
-
批准年份:2024
-
负责人:万荣
-
依托单位:
甜茶抑制AGE-RAGE通路增强突触可塑性改善小鼠抑郁样行为
-
批准号:2023JJ50274
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2023
-
负责人:贺志明
-
依托单位:
蒙药额尔敦-乌日勒基础方调控AGE-RAGE信号通路改善术后认知功能障碍研究
-
批准号:--
-
项目类别:地区科学基金项目
-
资助金额:33万元
-
批准年份:2022
-
负责人:都义日
-
依托单位:
补肾健脾祛瘀方调控AGE/RAGE信号通路在再生障碍性贫血骨髓间充质干细胞功能受损的作用与机制研究
-
批准号:--
-
项目类别:面上项目
-
资助金额:52万元
-
批准年份:2022
-
负责人:叶宝东
-
依托单位:
LncRNA GAS5在2型糖尿病动脉粥样硬化中对AGE-RAGE 信号通路上相关基因的调控作用及机制研究
-
批准号:
-
项目类别:省市级项目
-
资助金额:10.0万元
-
批准年份:2022
-
负责人:于海兵
-
依托单位:
围绕GLP1-Arginine-AGE/RAGE轴构建探针组学方法探索大柴胡汤异病同治的效应机制
-
批准号:81973577
-
项目类别:面上项目
-
资助金额:55.0万元
-
批准年份:2019
-
负责人:辛贵忠
-
依托单位:
AGE/RAGE通路microRNA编码基因多态性与2型糖尿病并发冠心病的关联研究
-
批准号:81602908
-
项目类别:青年科学基金项目
-
资助金额:18.0万元
-
批准年份:2016
-
负责人:刘括
-
依托单位: