1. Shaanxi Engineering Laboratory for Industrial Design, Northwestern Polytechnical University, Xi'an 710072, China 2. China Aviation Industry First Aircraft Design Institute, Xi'an 710089, China
The raw data with sampling density of 32×32 was spatially filtered to eliminate noise, in order to enhance the continuity of data distribution between independent sensors. Then sampling density of data was decreased to 24×24, 16×16, and 8×8, respectively. Four common features (mean pressure, maximum pressure, mean pressure gradient, and maximum pressure gradient) were calculated at each sampling density. The one-way ANOVA analysis showed that the differences of mean values between 32×32 sampling density and 24×24 as well as 16×16 sampling densities were small (1.1 mmHg, 2.6 mmHg), but the difference of mean value between 32×32 and 8×8 sampling densities was big (9.0 mmHg). Spearman correlation analysis revealed that the four common features of 32×32 sampling density had high correlation with that of 24×24, 16×16, and 8×8 sampling densities (P<0.05). The highest was the peak pressure correlation (0.99,P<0.05) between the 32 ×32 and 24 ×24 sampling densities, and the lowest was the mean pressure gradient correlation (0.55,P<0.05) between the 32×32 and 8×8 sampling densities. The test results showed that the pressure mat with the sampling density of 24×24 and 16×16 can provide accurate body pressure distribution characteristics.
Chuan ZHAO,Sui-huai YU,Lei WANG,Wen-hua LI. Body pressure distribution characteristics in different sampling densities. Journal of ZheJiang University (Engineering Science), 2019, 53(2): 268-274.
Tab.1Anthropometric dimensions of volunteers included in study
Fig.1Aircraft cabin simulation scenario and experiment process
Fig.2Pressure mat sensor distribution map
Fig.3Spatial filtering processing results of pressure mat data
Fig.4Pressure mapping image of body pressure distribution data
座椅间距/cm
32×32
24×24
pmax/ mmHg
pmean/ mmHg
Gmax/ (mmHg·m?1)
Gmean/ (mmHg·m?1)
pmax/ mmHg
pmean/ mmHg
Gmax/ (mmHg·m?1)
Gmean/ (mmHg·m?1)
71.12
32.13
25.72
10.11
8.21
31.93
27.65
12.47
9.99
76.20
32.23
27.65
10.38
7.48
32.46
25.63
12.48
9.15
81.28
35.62
28.47
10.54
8.21
35.97
28.14
14.20
9.87
86.36
36.26
28.41
11.69
8.34
36.16
28.40
14.23
10.13
91.44
37.33
29.87
12.36
8.48
37.68
28.89
15.00
10.29
座椅间距/cm
16×16
8×8
pmax/ mmHg
pmean/ mmHg
Gmax/ (mmHg·m?1)
Gmean/ (mmHg·m?1)
pmax/ mmHg
pmean/ mmHg
Gmax/ (mmHg·m?1)
Gmean/ (mmHg·m?1)
71.12
32.72
28.39
15.98
12.70
34.78
29.67
24.41
19.60
76.20
34.12
26.24
16.51
11.94
38.02
27.07
26.44
18.79
81.28
38.48
28.96
19.35
12.81
40.85
30.57
28.95
20.31
86.36
39.09
29.41
19.20
13.17
41.12
30.65
29.21
21.56
91.44
39.16
30.13
20.08
13.46
43.76
31.99
29.67
21.57
Tab.2Pressure distribution parameters
对照组 采样密度
试验组 采样密度
pmean均值差
P
95%置信区间
下限
上限
注：1) 与对照组比较，P<0.05
32×32
8×8
?9.01)
0.03
?17.18
?0.78
32×32
16×16
?2.6
0.66
?11.78
4.63
32×32
24×24
?1.1
0.99
?9.26
7.14
Tab.3Results of one-way ANOVA of average pressure at different sampling intensities
32×32体压分布采样密度 对应特征值
24×24
16×16
8×8
pmax
pmean
Gmax
Gmean
pmax
pmean
Gmax
Gmean
pmax
pmean
Gmax
Gmean
注：与对照组比较，均有P<0.05
pmax
0.99
0.88
0.76
0.84
0.94
0.88
0.70
0.81
0.85
0.88
0.78
0.76
pmean
0.85
0.99
0.55
0.94
0.76
0.98
0.48
0.89
0.61
0.96
0.60
0.86
Gmax
0.78
0.55
0.99
0.59
0.78
0.56
0.94
0.58
0.74
0.56
0.88
0.55
Gmean
0.84
0.96
0.61
0.99
0.76
0.94
0.57
0.96
0.63
0.92
0.68
0.92
Tab.4Spearman correlation analysis results of pressure distribution
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