不同感官模态对织物湿感觉的影响

doi:10.13475/j.fzxb.20230203901

纺织学报 ›› 2024, Vol. 45 ›› Issue (06): 82-88.doi: 10.13475/j.fzxb.20230203901

不同感官模态对织物湿感觉的影响

谭轶丹¹, 张昭华¹^,²(), 李诗涵¹

1.东华大学服装与艺术设计学院, 上海 200051
2.东华大学高性能纤维及制品教育部重点实验室, 上海 201620

收稿日期:2023-02-17 修回日期:2023-10-12 出版日期:2024-06-15 发布日期:2024-06-15
通讯作者: 张昭华(1977—),女,副教授,博士。主要研究方向为服装舒适性与功能。E-mail:zhangzhaohua@dhu.edu.cn。
作者简介:谭轶丹(1999—),女,硕士生。主要研究方向为服装舒适性与功能。
基金资助:
上海市自然科学基金面上项目(22ZR1403100);中央高校基本科研业务费专项资金资助项目(2232023G-02)

Effect of different sensory modalities on wetness perception of fabrics

TAN Yidan¹, ZHANG Zhaohua¹^,²(), LI Shihan¹

1. College of Fashion and Design, Donghua University, Shanghai 200051, China
2. Key Laboratory of High Performance Fibers & Products, Ministry of Education, Donghua University, Shanghai 201620, China

Received:2023-02-17 Revised:2023-10-12 Published:2024-06-15 Online:2024-06-15

摘要/Abstract

摘要：

为探究触觉、视觉、听觉的多感官模态是否比单触觉模态具有更高的湿感觉辨别能力,分别采用视觉模拟评分和信号检测论的方法评价织物的湿感觉强度与敏感度。21名受试者分别在3种感官模态(触觉单模态、视触觉双模态和视触听三模态)下触摸湿织物,同时记录受试者的指温和湿感觉大小。结果表明:在敏感度评价中,多感官模态(视触觉双模态、视触听三模态)比单感官模态的湿敏感度更高,更易辨别织物间湿度差异;在强度评价中,感官模态对湿感觉强度没有显著影响(p >0.05),织物类型与加湿量之间有显著的交互作用(p <0.05),在高水平加湿量下,对Coolmax^® 的湿强度评分明显最低。研究结果丰富了湿感觉多感官成因的理论基础并为人机交互的舒适性设计提供指导。

关键词: 湿感觉, 感官模态, 织物性能, 信号检测论, 动态接触

Abstract:

Objective Wetness perception is an important sensation to evaluate whether the human body is comfortable or not. In recent years, in order to clarify the factors affecting wetness perception, scholars have mostly analyzed from two aspects, temperature and mechanical stimulation, while ignoring the influence of sensory modality on wetness perception. Therefore, in order to clarify the relationship between sensory modality and wetness perception, this paper conducts wetness perception evaluation experiments by selecting fabrics with different properties based on dynamic contact between skin and fabric.

Method For the experiment, three fabrics with comparable thickness but distinct moisture transfer properties were selected: fabric 1^#, a 100% cotton sweatband with a weft flat knit construction, exhibiting excellent moisture-wicking properties; fabric 2^#, 100% Coolmax^®, featuring a double jacquard construction and a modified polyester with a radial 6-groove structure, renowned for its superior moisture transfer capability; Fabric 3^#, a polyester-ammonia blend sweatband with a weft flat knit construction, characterized by poor moisture-wicking performance. The samples were subjected to three levels of wetness: low (L), representing 20% of the saturated water content; medium (M), at 50% of the saturated water content; and high (H), reaching 80% of the saturated water content. Among them, the experimental fabric with the level of L was used as the standard stimulus. In a subjective evaluation experiment, 21 female participants with a mean age of approximately 22 years dynamically interacted with fabrics through touch under three sensory modalities (tactile unimodal, visual-tactile bimodal, and audio-visual-tactile trimodal), and the assessments of the perceived magnitude of wetness sensation were obtained.

Results According to three-way repeated measures ANOVA, there were no significant effect of sensory modality [F (2,40) =2.463,p =0.098]and fabric type [F (2,40) =2.989,p = 0.062]on wetness perception, while a significant effect of water content [F (1.217,24.335) =109.627,p <0.001]or interactions between fabric and water content[F (2.697,53.942) =4.276,p =0.011]was found. Bonferroni's post hoc analysis displayed significant difference between the two water contents (p <0.001), with the humidity levels increasing with increasing water content in the knitted fabrics. At low level of water content, there was no significant difference on wetness perception score among fabrics; at medium level of water content, the wetness perception score of fabric 3^# (polyester) was significantly lower than other fabrics; at high level of water content, the wetness perception score of fabric 2^# (Coolmax^®) was significantly lower than fabric 3^#, while no significant difference between other fabrics. The wetness perception scores in the different sensory modalities were as follows: tactile unimodal: (4.767 ± 0.070); visual-tactile bimodal: (4.730 ± 0.052); and audiovisual-tactile trimodality: (4.941 ± 0.053). The multisensory modalities (visual-haptic bimodal and audiovisual-tactile trimodality) of moisture discrimination were greater than the tactile unimodality. Furthermore, the moisture discrimination was greater at low level than at high level humidification capacity. In addition, applying multiple regression analysis, regression equations with sensory modality, water content, and fabric type as independent variables and moisture discrimination (d') as the dependent variable is established. The results show that water content had the highest influence weight, followed by fabric type, and finally sensory modality. Together, the three independent variables explained 34% of the total variance, which was statistically significant (p = 0.032).

Conclusion This article analyzes the effects of sensory (three levels), fabric (three levels) and water addition (three levels) on skin wetting. Studies have shown that fabric and water addition have an interactive effect on skin wetness, and wettability classes increase with increasing moisture content. The audiovisual-tactile trimodality was higher on wetness perception score compared to other modalities (tactile unimodality and visual-haptic bimodal), but not statistically difference. The multisensory modalities of wetness sensitivity were greater than the tactile unimodality. By evaluating the effect of sensory modality on skin wetness sensation, the theoretical basis of multisensory genesis was enriched. In addition, the study of the effect of different interaction methods on wetness sensation can provide a reference for the comfort design of human-computer interaction. It can also be applied to fields such as sports and medicine to improve the wetness sensation experience of clothing comfort.

Key words: wetness perception, sensory modality, fabric property, theory of signal detection, dynamic contact

中图分类号:

TS941.16

谭轶丹, 张昭华, 李诗涵. 不同感官模态对织物湿感觉的影响[J]. 纺织学报, 2024, 45(06): 82-88.

TAN Yidan, ZHANG Zhaohua, LI Shihan. Effect of different sensory modalities on wetness perception of fabrics[J]. Journal of Textile Research, 2024, 45(06): 82-88.

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链接本文: http://www.fzxb.org.cn/CN/10.13475/j.fzxb.20230203901

http://www.fzxb.org.cn/CN/Y2024/V45/I06/82

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编号	纤维成分/%	组织结构	面密度/ (g·m^-2)	厚度/ mm	透气率/ (mm·s^-1)
1^#	棉(100%)	纬平针	153.9	0.69	295.84
2^#	Coolmax^® (100%)	双面提花	137.4	0.64	794.17
3^#	涤纶/氨纶 (92%/8%)	纬平针	213.5	0.67	63.88

编号	液态水管理性能										表面性能
	润湿时间/s		吸湿率/(%·s^-1)		最大润湿半径/mm		扩散速度/ (mm·s^-1)		单向传递能力/%	整体水分管理能力	d_SMD/ μm	d_MIU
	反面	正面	反面	正面	反面	正面	反面	正面	单向传递能力/%	整体水分管理能力	d_SMD/ μm	d_MIU
1^#	8.837±2.25	7.459±2.29	51.379±7.06	82.101±14.05	16±2.24	16±2.24	1.693±0.51	1.851±0.41	245.401±36.14	0.599±0.51	8.052±5.87	0.208±0.01
2^#	3.000±0.15	3.094±0.15	33.291±1.50	46.786±2.31	20±0.00	20±0.00	4.149±0.24	4.173±0.18	167.977±14.27	0.595±0.02	2.948±1.36	0.234±0.04
3^#	3.078±0.06	3.094±0.07	31.054±1.46	48.752±0.86	20±0.00	20±0.00	4.031±0.06	4.128±0.07	234.310±8.43	0.674±0.01	1.978±0.19	0.261±0.02

感官模态	织物类型	加湿量水平H 为信号刺激		加湿量水平L 为信号刺激
感官模态	织物类型	湿度辨别力 (d')	反应偏向 (β)	湿度辨别力 (d')	反应偏向 (β)
触觉单模态	织物1^#	0.44	1.101 6	0.69	1.066 8
	织物2^#	0.42	1.156 3	0.86	1.112 4
	织物3^#	0.30	0.969 6	0.41	0.939 0
视触觉双模态	织物1^#	0.68	1.156 3	1.19	0.947 6
	织物2^#	0.12	1.024 5	0.75	1.024 5
	织物3^#	0.67	1.017 8	0.72	1.000 0
视触听三模态	织物1^#	1.14	1.087 6	1.08	1.115 3
	织物2^#	0.12	1.024 5	0.89	0.839 6
	织物3^#	0.44	0.907 8	0.13	0.992 1

自变量	未标准化系数		标准化系数		Sig.	F	r²
自变量	系数 B	标准误差	β	t	Sig.	F	r²
(常数)	0.527	0.305		1.726	0.106
感官模态	0.057	0.080	0.140	0.711	0.489	3.922	0.034
加湿量	0.266	0.130	0.402	2.039	0.061
织物类型	-0.213	0.080	-0.525	-2.665	0.018

不同感官模态对织物湿感觉的影响

Effect of different sensory modalities on wetness perception of fabrics

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