Body volume estimation equation for male laborers in Taiwan.

The purpose of this study was to develop a body volume (BV) estimation equation for male laborers in Taiwan with body weight (W) and stature height (H) as initial estimators. A three-dimensional (3D) body scanner and a 3D foot scanner were used to measure the 3D range data of 100 male laborers in this study. Subjects' BV was extracted from the 3D body model, and H and W were used as independent variables in regression analysis. The results show that the final BV estimation equation is BV = 1122.927 × W0.972, with R2 = 0.949. Thirty extra male subjects were scanned to compare this BV estimation equation with those in previous studies. The results show that this BV estimation equation had the smallest absolute mean difference at 1.1458 L and the smallest standard error of the estimate at 2.48% in comparison.

A Pilot Study of Five Types of Maximum Hand Strength among Manufacturing Industry Workers in Taiwan.

Background: The purpose of this study is to collect five types of maximum hand strength among workers in the manufacturing industry in Taiwan. Methods: This study is a cross sectional study with a stratified and convenient sample of workers on the production line in manufacturing industries in Central Taiwan. In total, we recruited 198 healthy subjects to participate in this study. Five types of hand strength were measured in both hands three times with 3 min rests between trials. Results: The strength of females for these five types of hand exertions were 52.0% to 67.6% of the strength of males (p < 0.001). For both genders, there was a main effect for the types of hand strength for the right hand (p < 0.001) and the left hand (p < 0.001). In general, the hand strength in U.S. and EU countries was 1.2 to 1.7 times greater than the strength among the three types of hand exertions in this study. Conclusion: These results can be used to evaluate the musculoskeletal burdens on the upper extremities in the manufacturing industry and could also be used for tool and job design and job modifications.

Evaluation of a proposed chair with an arm support for wiring terminal blocks on a vertical plane.

To reduce the muscular exertion of an operator wiring terminal blocks on a vertical plane, a chair with a unique back that can be used as a back support or arm support is proposed in this study. A digital version of the chair was first developed based on anthropometric data and tested with a digital anthropometric subject using the Jack software before the physical chair was developed. To evaluate the effects of the physical chair, an experiment of wiring terminal blocks was conducted with 12 subjects to test whether the use of the arm support can reduce muscular exertion. The results showed that (1) exertion on the anterior deltoid, upper trapezium, and erector spinae muscles decreased with decrease in terminal block height; (2) using the arm support reduced exertion on the anterior deltoid and upper trapezium muscles; and (3) the subjects reported less self-perceived fatigue in the wrist, elbow, and shoulder regions when the arm support was used. These results confirm that the proposed chair can reduce muscular workload in the shoulder muscle over a proper range of working heights. However, using the arm support may restrict certain working postures and lead to force generation in upper extremity muscles.

Hand surface area estimation formula using 3D anthropometry.

Hand surface area is an important reference in occupational hygiene and many other applications. This study derives a formula for the palm surface area (PSA) and hand surface area (HSA) based on three-dimensional (3D) scan data. Two-hundred and seventy subjects, 135 males and 135 females, were recruited for this study. The hand was measured using a high-resolution 3D hand scanner. Precision and accuracy of the scanner is within 0.67%. Both the PSA and HSA were computed using the triangular mesh summation method. A comparison between this study and previous textbook values (such as in the U.K. teaching text and Lund and Browder chart discussed in the article) was performed first to show that previous textbooks overestimated the PSA by 12.0% and HSA by 8.7% (for the male, PSA 8.5% and HSA 4.7%, and for the female, PSA 16.2% and HSA 13.4%). Six 1D measurements were then extracted semiautomatically for use as candidate estimators for the PSA and HSA estimation formula. Stepwise regressions on these six 1D measurements and variable dependency test were performed. Results show that a pair of measurements (hand length and hand breadth) were able to account for 96% of the HSA variance and up to 98% of the PSA variance. A test of the gender-specific formula indicated that gender is not a significant factor in either the PSA or HSA estimation.

Human body surface area database and estimation formula.

This study established human body surface area (BSA) database and estimation formula based on three-dimensional (3D) scanned data. For each gender, 135 subjects were drawn. The sampling was stratified in five stature heights and three body weights according to a previous survey. The 3D body surface shape was measured using an innovated 3D body scanner and a high resolution hand/foot scanner, the total body surface area (BSA) and segmental body surface area (SBSA) were computed based on the summation of every tiny triangular area of triangular meshes of the scanned surface; and the accuracy of BSA measurement is below 1%. The results of BSA and sixteen SBSAs were tabulated in fifteen strata for the Male, the Female and the Total (two genders combined). The %SBSA data was also used to revise new Lund and Browder Charts. The comparison of BSA shows that the BSA of this study is comparable with the Du Bois and Du Bois' but smaller than that of Tikuisis et al. The difference might be attributed to body size difference between the samples. The comparison of SBSA shows that the differences of SBSA between this study and the Lund and Browder Chart range between 0.00% and 2.30%. A new BSA estimation formula, BSA=71.3989 x H(.7437) x W(.4040), was obtained. An accuracy test showed that this formula has smaller estimation error than that of the Du Bois and Du Bois'; and significantly better than other BSA estimation formulae.

Foot surface area database and estimation formula.

The purpose of this study is to establish a foot surface area (FSA) database and estimation formula based on 3-D foot scan data. For each gender, 135 subjects stratified in five statures and three body weights were drawn. The foot was measured using a high-resolution 3-D foot scanner, of which the precision and accuracy is within 1%. The FSA was computed by the triangular mesh summation method and five 1-D foot measurements were extracted automatically to be used as candidate estimators for FSA estimation formula. The results of the FSA measurements are tabulated on fifteen strata for the Male, the Female and the Total (the two genders combined). The comparison of these FSA measurements with previous studies shows that previous studies underestimated the FSA approximately 4.06% for the Total (for the Male, 6.93%; for the Female, 0.82%). Regression analyses using these five 1-D foot measurements were performed. The results show that foot-length and ball-girth are effective estimators of FSA for the total (FSA=1.043 x foot-length x ball-girth, R(2)=95.4%). A test on the necessity of gender-specific formula indicated that no gender-specific formula is needed, and the formula for the total is good for both genders.

Determination of hand surface area as a percentage of body surface area by 3D anthropometry.

This study investigates the hand surface area (HSA) and palm surface area (PSA) percentages of body surface area (BSA). The HSA and PSA of 135 men and 135 women were measured by scanner and incorporated into an existing BSA database to derive %HSA/BSA and %PSA/BSA using five stature heights and three body weights in accordance with population distribution. Allowing for various degrees of specificity, the mean %HSA/BSA and mean %PSA/BSA were found to be 2.29% (0.24%) and 0.89% (0.09%), respectively. Gender and body weight group were significant factors.