本文選題：三維掃描 + 人體體積　； 參考：《航天醫(yī)學(xué)與醫(yī)學(xué)工程》2017年05期

【摘要】：目的基于三維掃描的人體測(cè)量技術(shù)建立人體體積的回歸模型。方法通過三維掃描及后續(xù)的修復(fù),使用三維軟件獲取了160名成年男性的137項(xiàng)人體測(cè)量數(shù)據(jù),然后使用因子分析法及回歸分析對(duì)各數(shù)據(jù)與體積的相關(guān)性進(jìn)行了研究。結(jié)果通過因子分析獲取影響人體體積的4項(xiàng)主要指標(biāo):身高、體重、胸上圍與BMI指數(shù),建立了線性、對(duì)數(shù)、乘冪、指數(shù)4個(gè)回歸模型,并使用額外的16名志愿者進(jìn)行模型驗(yàn)證,結(jié)果部分給出了4個(gè)回歸模型的預(yù)測(cè)體積與實(shí)際體積的誤差絕對(duì)值的平均值及誤差百分比的平均值。結(jié)論在三維掃描獲得的大量人體數(shù)據(jù)基礎(chǔ)上建立的人體體積回歸模型計(jì)算方便,預(yù)測(cè)可靠,結(jié)果精度符合工業(yè)設(shè)計(jì)的閾值范圍要求,該方法在傳統(tǒng)空氣置換體積描記法與水下稱重法難以實(shí)施的情況下有著良好的預(yù)測(cè)結(jié)果。
[Abstract]:Objective to establish a regression model of human body volume based on three-dimensional scanning anthropometry. Methods 137 anthropometric data of 160 adult males were obtained by 3D scanning and subsequent restoration. The correlation between the data and volume was studied by factor analysis and regression analysis. Results through factor analysis, four main indexes affecting human body volume were obtained: height, weight, upper chest circumference and BMI index. Four regression models were established, which were linear, logarithmic, power and exponent, and were verified by additional 16 volunteers. Results the average value of the absolute error and the average error percentage of the predicted volume and the actual volume of the four regression models are given. Conclusion the human volume regression model established on the basis of a large amount of human body data obtained by 3D scanning is convenient to calculate and reliable to predict, and the precision of the result is in line with the threshold range of industrial design. This method has good prediction results when the traditional air displacement method and underwater weighing method are difficult to implement.
【作者單位】： 北京科技大學(xué)機(jī)械工程學(xué)院;中國(guó)標(biāo)準(zhǔn)化研究院;
【基金】：國(guó)家自然科學(xué)基金(51005016) 國(guó)家質(zhì)量檢驗(yàn)檢疫總局資助項(xiàng)目(201510042) 國(guó)家留學(xué)基金委公派出國(guó)留學(xué)資助項(xiàng)目(201208110144) 中央高校基本科研業(yè)務(wù)費(fèi)專項(xiàng)資金(FRF-TP-14-026A2)
【分類號(hào)】：R318
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本文編號(hào)：1953675