Journal of Textile Research ›› 2019, Vol. 40 ›› Issue (04): 111-116.doi: 10.13475/j.fzxb.20180601407

• Apparel Engineering • Previous Articles     Next Articles

Application of BP neural network in prediction of shapewear pressure

ZHOU Jie(), MA Qiurui   

  1. Apparel & Art Design College, Xi'an Polytechnic University, Xi'an, Shaanxi 710048, China
  • Received:2018-06-01 Revised:2019-01-07 Online:2019-04-15 Published:2019-04-16

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Abstract:

In order to predict underwear pressure when wearing shapewear, a prediction method based on neural network was proposed. A total of 26 female college students wore the shapewear of the same brand, and were asked to perform four poses. The pressure values at 20 body points of each subject were measured, respectively. Two different BP neural network toolbox functions were used to establish the pressure prediction models. The relationships between the pressure values and five body measurements were analyzed. The prediction results were tested and compared while using the two different toolbox functions and different input values. The results show that the method based on neural network does not need complicated calculation process. By this method, five body measurement values can be directly used to predict the pressure value of shapewear. The prediction accuracy of the newff function is superior to that of the feedforwardnet function. The accuracy of the prediction of pressure in the two standing poses is better than that in the two sitting poses. When taking the pressure values of standing pose and five body measurements as input values, the pressure values of the other three poses can be predicted with the accuracy over 82%.

Key words: shape wear, underwear pressure, BP neural network, pressure prediction model

CLC Number: 

  • TS941.763.5

Fig.1

Pressure test points for body shaper and girdle. (a) Front of body shaper; (b)Behind of body shaper; (c)Front of girdle; (d)Behind of girdle"

Tab.1

Reasons for pressure test points"

身体
部位		 压力点 选择的原因
腰
背
夹		 肩中点(S1) 肩带承受乳房的重力,压力较大
腋下点(S2) 此处收纳副乳、脂肪堆积和赘肉,为评价塑型效果关键点
胃部中点(S3) 收纳脂肪,评价塑型效果关键点
前侧腰中点(S4) 鱼骨所在位置,该点压力相对较大
侧腰处(S5) 收纳脂肪,评价塑型效果关键点
后侧腰中点(S6) 鱼骨所在位置,该点压力相对较大
底边前中点(S7) 收纳脂肪,该点压力相对较大,评价塑型效果关键点
底边侧中点(S8) 腹围线和侧缝线的交点,压力较大
底边后侧中点(S9) 该点压力相对较大
肩胛骨处(S10) 收紧肩胛赘肉,提拉背部肌肉的关键部位,评价塑型效果关键点
提
臀
束
裤		 腹凸点(P1) 腹部赘肉,评价塑型效果关键点
前侧臀点(P2) 脂肪堆积,评价塑型效果关键点
侧臀点(P3) 此处为髂骨处,骨骼凸起易对人体产生压力
腹股沟点(P4) 影响健康关键点
大腿前凸点(P5) 评价塑型效果关键点
大腿侧(P6) 评价塑型效果关键点
大腿后凸点(P7) 评价塑型效果关键点
臀凸点(P8) 容易受力,评价塑型效果关键点
前腰中点(P9) 评价塑型效果关键点
侧腰中点(P10) 评价塑型效果关键点

Fig.2

Test poses. (a)Standing; (b)Standing forward; (c)Sitting; (d)Sitting forward"

Fig.3

newff function predicts pressure value of wearing shaper. (a)Standing; (b)Standing forward; (c)Sitting; (d)Sitting forward"

Fig.4

newff function predicts pressure value of wearing girdle. (a)Standing; (b)Standing forward; (c)Sitting; (d)Sitting forward"

Fig.5

feedforwardnet function predicts pressure value of wearing shaper. (a)Standing; (b)Standing forward; (c)Sitting; (d)Sitting forward"

Fig.6

feedormwardnet function predicts pressure value of wearing girdle. (a)Standing; (b)Standing forward; (c)Sitting; (d)Sitting forward"

Tab.2

Forecasting accuracy%"

姿势 feedforwardnet函数 newff函数 平均值
腰背夹 提臀束裤 腰背夹 提臀束裤
站姿 75.14 72.37 75.29 74.34 74.92
站姿前倾 74.18 76.54 77.28 74.25
坐姿 68.34 69.19 76.56 69.79 69.56
坐姿前倾 62.17 62.54 72.28 75.59
平均值 70.06 74.42

Fig.7

Prediction diagram wearing shaper. (a)Standing forward; (b)Sitting; (c)Sitting forward"

Fig.8

Prediction diagram wearing girdle. (a)Standing forward; (b)Sitting; (c)Sitting forward"

Tab.3

Forecasting accuracy of newff function%"

姿势 腰背夹 提臀束裤 平均值
站姿前倾 91.64 88.81 90.23
坐姿 83.24 82.15 82.70
坐姿前倾 84.67 82.88 83.78
平均值 86.52 84.61 85.57
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