基于事件相关电位技术的花式粗呢面料视觉情绪感知研究OA

With the upgrading of consumer demands for textiles and apparel,the focus has shifted from basic functional satisfaction to emotional experiences.Fabric texture features play a crucial role in consumers'visual perception and emotional arousal.However,traditional subjective evaluation methods are often influenced by individual cognitive differences,leading to potential biases.To address this,event-related potentials(ERP)technology has been introduced to provide an objective quantification of visual emotion perception.This paper investigates the influence of fabric texture features on visual emotion perception by taking fancy tweed fabrics as the research object.It explores the mapping relationship between different texture features and emotional experiences,providing theoretical reference for the emotional design of fabrics and offering new insights into the objective quantification of textile visual emotion evaluation. Focusing on three core texture variables—fancy yarn type,arrangement proportion of fancy to normal yarns,and fabric weave structure—this study conducted an integrated experiment combining subjective emotion scales and neurophysiological measurements.Twenty healthy subjects were recruited to evaluate nine types of black-and-white fancy tweed fabrics.Subjective emotional evaluation was based on the valence-arousal(V-A)model,scoring four dimensions:sad-happy,sleepy-excited,disgusted-satisfied,and tense-relaxed.Synchronously,a 32-channel EEG system was employed to record brain activities.The study systematically analyzed the amplitude and latency characteristics of early visual components(P1,N1)and a late cognitive component(P3)to examine the neural response mechanisms triggered by different texture features and their correlation with subjective emotional perceptions. The main findings of this study are threefold.First,different fancy yarn structures trigger distinct neural response patterns.Loop yarn induces the smallest P1 amplitude but the largest N1 and P3 amplitudes,indicating it requires minimal initial visual processing but sustains strong attention and positive cognitive evaluation.Slub yarn yields the largest P1 amplitude,demonstrating a strong initial visual impact.Wave yarn elicits a lower cognitive load and a more peaceful emotional experience.Second,the arrangement proportion significantly affects visual processing efficiency.A 1:1 tight arrangement induces the largest P1 and P3 amplitudes with the shortest N1 latency,enabling efficient visual capture and strong positive evaluation.A 3:1 moderate arrangement evokes the deepest attention processing,while a 5:1 sparse arrangement results in the lowest neural response.Third,fabric weave structures show significant differences in neural responses and emotional evaluations.Complex jacquard weave elicits the highest P1 and N1 amplitudes,drawing more neural resources,whereas plain weave presents the lowest cognitive load.Correlation analyses reveal that P3 amplitude positively correlates with the"happy"and"excited"dimensions,and shorter P1 latencies correlate significantly with higher positive emotion scores. By introducing ERP technology into the visual emotion evaluation of textiles,this study successfully constructs an objective and quantitative evaluation method that complements subjective scales,revealing the systematic neural response differences caused by varying texture features in early visual processing and late cognitive evaluation stages.Based on these insights,a systematic design framework of"target emotion orientation—texture element matching—objective and subjective combined verification"is proposed to guide the practical application of fancy tweed fabrics.This framework allows textile enterprises to select yarn types,arrangement proportions,and weave structures according to product positioning,thereby enhancing the emotional added value of fabrics and driving the industry's transition towards emotion-driven product development.