Volume 5024 of the series Lecture Notes in Computer Science.The aim of this study was to identify the tactile dimensions
in the discrimination of light-weight wool fabrics. The participants
judged the overall similarity between 21 light-weight wool fabrics using
free sorting tasks. The fabrics were evaluated using active touch with limited
exploratory procedure. Multidimensional scaling (MDS) was used to
generate the perceptual space, revealing one dimension of tactile perception.
Finally, through regression analysis we were able to interpret this
dimension, using verbal attributes and physical properties of the fabrics.
We discuss the relevance of the stimuli properties and the associations
between verbal attributes and between physical properties, on the evaluation
of the fabrics, considering its theoretical implications

Albuquerque, Pedro Barbas

Fernandes, Alexandra M.

Universidade do Minho: RepositoriUM

Tactile perceptual dimensions: a study with light-weight wool fabrics

Tactile Perceptual Dimensions:A Study with Light-Weight Wool FabricsAlexandra Fernandes and Pedro B. AlbuquerqueDepartamento de Psicologia, Universidade do MinhoCampus de Gualtar, 4710-057 Braga, Portugal{alexandra.fernandes}@gmail.comAbstract. The aim of this study was to identify the tactile dimen-sions in the discrimination of light-weight wool fabrics. The participantsjudged the overall similarity between 21 light-weight wool fabrics usingfree sorting tasks. The fabrics were evaluated using active touch with lim-ited exploratory procedure. Multidimensional scaling (MDS) was used togenerate the perceptual space, revealing one dimension of tactile percep-tion. Finally, through regression analysis we were able to interpret thisdimension, using verbal attributes and physical properties of the fabrics.We discuss the relevance of the stimuli properties and the associationsbetween verbal attributes and between physical properties, on the eval-uation of the fabrics, considering its theoretical implications.1 IntroductionThe ﬁrst systematic studies on tactile perception were reported in David Katz’sbook “The world of touch” [1]. Katz diﬀerentiates between modiﬁkationen − thequalities of tactile stimuli, like roughness − and speziﬁkationen − the identifyingcharacteristics of the stimuli, like the silkiness of silk.The identifying characteristics can be interpreted as a result of combinationsbetween the stimuli objective qualities, the individual preferences, the descriptiveskills of the evaluator, or even the familiarity with the stimuli. Therefore, theintegration of the physical properties, and how they originate a global perceptionis one of the most relevant aspects in predicting the subject’s tactile sensation.Garner presented a theory concerning the integration of the stimuli properties[2]. He diﬀerentiated the integral properties − related to overlaid dimensions ofthe objects − from the separable properties of the stimuli − well deﬁned di-mensions of the objects which are not perceptually connectible. Nonetheless,the classiﬁcation of stimuli properties as integral or separable is not straightfor-ward. There are several factors that can aﬀect the processing of the properties,facilitating or preventing their integration [3]. Research developed in the project COM4Wool - Design of Light-Weight WoolFabrics; Valorization and Optimization of Total Comfort for High Added ValueClothing. Coordinated by Elisabete C. Silva, PhD. Reference: UMINHO/IDEIA-COM4WOOL/BI/2/05.M. Ferre (Ed.): EuroHaptics 2008, LNCS 5024, pp. 337–342, 2008.c© Springer-Verlag Berlin Heidelberg 2008338 A. Fernandes and P.B. AlbuquerqueResearchers have tried to identify the number of tactile dimensions in theperception of familiar stimuli. Previous studies have used free sorting tasks toanalyze tactile perception [4], [5], [6], [7], [8]. With this task, it is possible torepresent and interpret tactile dimensions through MDS solutions using the sen-sory attributes or the physical properties of the stimuli. MDS studies identiﬁedtwo [4] to four perceptual dimensions [7] that are interpreted similarly by theauthors, but with some diﬀerences according to the type of stimuli evaluated orthe selected exploratory procedure.The apparent incongruence in the number and/or nature of tactile dimensionscan be related not to actual diﬀerences in the processed dimensions, but tovariations in their relevance for the participant [7]. Thus, the speciﬁc propertiesof the stimulus and its variation in the evaluated set determine the salience of thetactile dimensions, contributing to the perceived similarity between the stimuli.The dimensions in tactile perception are not frequently studied, and MDStechniques may improve the comprehension of the tactile perceptive organiza-tion, since they take into account several properties of the stimuli at the sametime.2 MethodParticipants: Twenty-ﬁve volunteers (13 were female), mean age of 24.76 (SD= 3.06), undergraduate and graduate students from University of Minho.Materials and Stimuli: Twenty-one fabric samples (21x21cm) of light-weightwool fabrics with diﬀerences in torsion (Z or S), structure (taﬀeta, twill weave,and twill weave derivate) and ﬁnishing (dyed yarn or dyed piece). For the eval-uation of the eight verbal attributes - delicate, thick, light, smooth, soft, ﬂexible,warm, and resistant - the participants were presented with a 12.7 cm (5 inches)graphic scale, marked in the poles: “nothing” (0 cm) and “very” (12.7 cm). Theparticipants were instructed to mark the point in the scale that better translatedtheir sensation when touching each fabric. These verbal attributes were selectedthrough previous vocabulary procedures [9]. To block the vision of the fabricsduring the task, we used a white placard with two openings for the hands. Theparticipants wore a rubber glove, with the thumb and index ﬁnger completely re-moved. The participants washed their hands with glycerin soap and dried it withpaper towels before the task, and whenever they needed during the procedure.Procedure: Each participant completed a free sorting task with the 21 fabricsamples, repeated in two sessions, in consecutive weeks (M= 7.0 days, SD= 2.7days), without training session. The participants wore the rubber glove on thedominant hand while evaluating the fabrics, and were allowed to rest during theevaluation. They were instructed to create groups of fabric samples based onsimilarity, with no restrictions to the number of groups formed or to the numberof samples allowed in each group. The fabric samples were presented randomlyand individually, with no limitation of time of contact. The ﬁrst sample wasTactile Perceptual Dimensions: A Study with Light-Weight Wool Fabrics 339presented as Sample 1 and it represented the A Group. The second sample,presented as Sample 2, could be added to A Group (if evaluated as similar toSample 1 ), or used to form the B Group (if evaluated as diﬀerent from Sample1 ). After the evaluation of all the samples, the generated groups were presentedto the participant, following the same order by which the fabric samples weregathered in each group. The participants were allowed to touch any sample atany time during the evaluation, but always one sample at a time. Before theﬁnal presentation of the groups, the participants were told they could join ordivide the previously formed groups in order to reach a better representation oftheir tactile sensation. At the end of the second session, after the free sortingtask, the participants evaluated the verbal attributes.3 ResultsThe participants formed between 2 and 6 groups of fabric samples (M= 3.62;SD= 1.05; Mode= 4). Sixty percent of the participants maintained the numberof groups in both sessions, and the consistency in the sorting task (percentage oftimes each pair of fabrics was grouped together on both sessions) ranged between55.1% and 78.2% (M= 67.6%, SD= 5.97%).The MDS revealed that the adjustment measures 1-R2 and Stress had accept-able levels in the one-dimensional solution [10]. The 1-R2 values explain 96% ofthe variability and the Stress value is 0.12. These measures do not improve inthe two-dimensional representation, indicating that the one-dimensional solutionis reliable. Figure 1 represents the one-dimensional solution. Two close pointsreveal tactile similarities between the represented fabric samples. Some samplesare overlaid - A1, A2 and A10; A9, A11 and A12; A15 and A19; A4, A16 andA20 - indicating that they were perceived as identical by the evaluators.The verbal attributes were measured in centimeters from the “zero point”on the scale, associated with the “nothing” pole. The participants were able toFig. 1. Representation of the one-dimensional solution from MDS340 A. Fernandes and P.B. AlbuquerqueTable 1. Verbal atributtes’ correlation matrix (*p < 0.01)Delicate Thick Light Smooth Soft Flexible Warm ResistantDelicateThick -.973*Light .973* -.968*Smooth .979* -.955* .998*Soft .979* -.945* .942* .986*Flexible .955* -.965* .959* .935* .926*Warm -.934* .967* -.965* -.916* -.907* -.939*Resistant -.944* .975* -.959* -.913* -.906* -.954* -.952*diﬀerentiate all the attributes, as shown by the ANOVA analysis of the individualevaluations: delicate (F (20,504)= 13.10, p< 0.01); thick (F (20,504)= 18.43, p<0.01); light (F (20,503)= 14.02, p< 0.01); smooth (F (20,504)= 16.29, p< 0.01);soft (F (20,504)= 15.99, p< 0.01); ﬂexible (F (20,504)= 11.53, p< 0.01); warm(F (20,504)= 8.90, p< 0.01); and resistant (F (20,504)= 5.64, p< 0.01). Thediﬀerence between the fabric with the highest and the fabric with the lowestscale value for each attribute varies from 4.5 (resistant) to 7.4 (smooth), with amean variation of 6.2 (SD = 0.95).The correlation matrix for the verbal attribute scales is shown in table 1.Results show as strong association between the evaluations of the attributes,originating two groups (based on the type of correlations − negative and posi-tive): one composed by the attributes thick, warm, and resistant and other bythe remaining attributes.To interpret the MDS solution, the mean evaluations of the attributes foreach fabric were regressed into the coordinates of each stimulus on the MDSsolution (table 2). The β values are very high for all the attributes, revealinga strong association of the attributes with the one-dimensional space. The at-tribute soft presents the higher β value (0.978), followed by the attributes delicateand smooth, all surface attributes. The attributes thick, warm and resistant arenegatively associated with the perceptual dimension, while the others presentpositive relations. Although the attributes had well distinguishable meanings[9], all revealed to be related to the one-dimensional perceptual solution.The physical properties present a tight relationship in this set of stimuli, withsigniﬁcant correlations (as shown in table 3), contributing to the one-dimensionalpattern in the MDS solution.Table 4 shows the β coeﬃcients for the physical properties, resultant from itsregression in the MDS coordinates. The ligament coeﬃcient (fabric tightness),thickness, weft density, weight, and warp and weft yarn title (thickness of theTable 2. Standardized β values for the verbal attributes (*p < 0.01)Delicate Thick Light Smooth Soft Flexible Warm Resistantβ Values .976* -.948* .955* .973* .978* .934* -.898* -.908*Tactile Perceptual Dimensions: A Study with Light-Weight Wool Fabrics 341Table 3. Physical properties’ correlation matrix (*p < 0.01; **p < 0.05)LigamentCoeﬃcientThicknessWarpDensityWeftDensityWeightWarpYarnTitleWeftYarnTitleLigament CoeﬃcientThickness -.498*Warp Density -.622** .058Weft Density -.196 -.425 .547*Weight -.477 .788** -.130 -.470*Warp Yarn Title -.151 .614** -.494* -.684** -.816**Weft Yarn Title -.182* .649** -.430 -.726** .841* .797**Table 4. Standardized β values for the physical properties (*p < 0.01;**p < 0.05)LigamentCoeﬃcientThicknessWarpDensityWeftDensityWeightWarpYarnTitleWeftYarnTitleβ Values .478* -.808* .060 .532** -.675* -.697* -.626*yarn) are signiﬁcantly associated with the perceptual dimension - the propertiesligament coeﬃcient and weft density are positively related to the perceptualdimension, while the other present negative associations. The overall β valuesof the physical properties are lower than the verbal attributes values. This maybe interpreted as an indication that each physical property by itself cannotexplain the MDS solution. The verbal attributes could, therefore, describe amore complex perception of the stimuli.4 ConclusionsWith this study we were able to deﬁne an one-dimensional solution in the tac-tile perception of light-weight wool fabrics. This solution appears to be a goodtranslation of the participants’ sensations and represents a robust dimension.Both physical properties and verbal attributes are projected in the dimensionalspace, conﬁrming the one-dimensional solution, since interpretability is a rele-vant criterion for the dimensional decision in MDS [10].In this set of fabrics, it is possible to preview the consumers’ evaluations,based on two attribute groups (positive and negative), which are conceptuallylinked to the same perceptual dimension.Through a procedure which did not involve experts, we were able to deﬁne aglobal and stable sensory proﬁle in a short period of time. The deﬁned dimensionof light-weight wool fabrics is positively associated with the attributes delicate,342 A. Fernandes and P.B. Albuquerquelight, smooth, soft, and ﬂexible and with the physical properties ligament coeﬃ-cient and weft density; and negatively related to the attributes thick, warm, andresistant, and the properties thickness, weight, and weft/warp yarn title.Although the participants were able to diﬀerentiate the fabrics, they com-pose a tactually similar set, discriminated essentially by global sensations. TheMDS dimension may be interpreted as an identifying characteristic of the light-weight wool fabrics, implying all the verbal attributes. However, in a qualitativeanalysis, this dimension is verbalized exclusively as surface properties by theparticipants, particularly the attribute soft.References1. Katz, D.: The World of Touch (L. E. Krueger, Trans.). Lawrence Erlbaum, Hillsdale(1989) (Original work published in 1925)2. Garner, W.R.: The Processing of Information and Structure. Wiley, New York(1974)3. Klatzky, R.L., Lederman, S.J., Reed, C.: Haptic Integration of Object Properties:Texture, Hardness, and Planar Contour. Journal of Experimental Psychology: Hu-man Perception and Performance 15, 45–57 (1989)4. Hollins, M., Faldowski, R., Rao, S., Young, F.: Perceptual Dimensions of Tac-tile Surface Texture: A Multidimensional Scaling Analysis. Perception and Psy-chophysics 56, 697–705 (1993)5. Hollins, M., Bensma¨ıa, S., Karlof, K., Young, F.: Individual Diﬀerences in Percep-tual Space for Tactile Textures: Evidence from Multidimensional Scaling. Percep-tion and Psychophysics 62, 1534–1544 (2000)6. Hollins, M., Lorenz, F., Seeger, A., Taylor, R.: Factors Contributing to the Integra-tion of Textural Qualities: Evidences from Virtual Surfaces. Somatossensory andMotor Research 22, 193–206 (2005)7. Picard, D., Dacremont, C., Valentin, D., Giboreau, A.: Perceptual Dimensions ofTactile Textures. Acta Psychologica. 114, 165–184 (2003)8. Tiest, W.M., Kappers, A.M.: Analysis of Haptic Perception of Materials by Multi-dimensional Scaling and Physical Measurements of Roughness and Compressibility.Acta psychologica. 121, 1–20 (2006)9. Fernandes, A.: Identiﬁcation of the perceptual dimensions in tactile diﬀerentiationof light-weight wool fabrics. Universidade do Minho: Departamento de Psicologia(2007) [unpublished thesis]10. Kruskal, J.B., Wish, M.: Multidimensional Scaling. Sage, Beverley Hills (1978)

Tactile perceptual dimensions: a study with light-weight wool fabrics

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