不同采样密度下体压分布特征

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.