applied sciences

Article Haptic Hybrid Prototyping (HHP): An AR Application for Texture Evaluation with Semantic Content in Product Design

Miguel-Ángel Pardo-Vicente 1,* , Lucía Rodríguez-Parada 1 , Pedro F. Mayuet-Ares 1 and Francisco Aguayo-González 2 1 Department of Mechanical Engineering & Industrial Design, Faculty of Engineering, University of Cádiz, Av. Universidad de Cádiz 10, Puerto Real, E-11519 Cádiz, Spain; [email protected] (L.R.-P.); [email protected] (P.F.M.-A.) 2 Department of Design Engineering, University of Seville, Virgen de África 7, 41011 Seville, Spain; [email protected] * Correspondence: [email protected]



Received: 28 October 2019; Accepted: 21 November 2019; Published: 25 November 2019


Abstract: The manufacture of prototypes is costly in economic and temporal terms and in order to carry this out it is necessary to accept certain deviations with respect to the final finishes. This article proposes haptic hybrid prototyping, a haptic-visual product prototyping method created to help product design teams evaluate and select semantic information conveyed between product and user through texturing and ribs of a product in early stages of conceptualization. For the evaluation of this tool, an experiment was realized in which the haptic experience was compared during the interaction with final products and through the HHP. As a result, it was observed that the answers of the interviewees coincided in both situations in 81% of the cases. It was concluded that the HHP enables us to know the semantic information transmitted through haptic-visual means between product and user as well as being able to quantify the clarity with which this information is transmitted. Therefore, this new tool makes it possible to reduce the manufacturing lead time of prototypes as well as the conceptualization phase of the product, providing information on the future success of the product in the market and its economic return.

Keywords: augmented reality; product design; texture; semantic; emotion; sensory perception; prototyping

1. Introduction Consumers’ lifestyles are continually changing and demand that new products come onto the market more frequently [1]. These products are increasingly personalized so that they can, on the one hand, adapt to the functional needs of today’s market and, on the other, use the product as a means of communicating a changing lifestyle [2]. This, together with the challenge posed by the paradigm of Industry 4.0 (I 4.0) at present, makes tools such as augmented reality (AR) have the purpose of promoting autonomous interoperability, agility, flexibility, rapid decision-making, efficiency, and cost reduction [3–5]. Within this framework, one of the main purposes of design engineering teams is to focus on the user to meet their needs and expectations [6,7]. Thus, in the conceptual phase, the correct formal, functional and aesthetic adaptation of the product by industrial designers is crucial to avoid problems in the following phases of the design process or even market products with erroneous attributes [8]. For this reason, during the product conceptualization process, it is crucial to predict at an early stage during the design phase the future reactions of users to the product [9]. Thus, it must be possible

Appl. Sci. 2019, 9, 5081; doi:10.3390/app9235081 www.mdpi.com/journal/applsci Appl. Sci. 2019, 9, 5081 2 of 20 to demonstrate that the requirements of the product specification are aligned with what users think and feel in real conditions of use. Historically, the most studied requirements in the field of product design have been those that allow the product to accomplish its function. However, in the last few decades, product semantics (PS) [10] and then emotional design (ED) [11,12] have shown that not only is function important, but that products serve as a channel for communicating concepts [13–15]. Many of these concepts are related to the way of living and feeling of people and with them emotions are produced [16,17]. The beginning of this communication process starts with what concepts want to be communicated and by what means they are going to be transmitted [18,19]. Hence the importance of establishing design and manufacturing requirements related to PS and of being able to reliably demonstrate what message is delivered through the design properties (shape, colour, material, and texture) [20,21]. To approach the resolution of this problem, one of the most commonly used methods by design teams to get the user’s opinion before the manufacturing phase has been the creation of prototypes [22]. This is an economical and quick way to reproduce the shape of the product and be able to validate certain basic requirements [23]. Thus, the techniques developed in prototyping vary depending on the historical framework where increasing complexity in design processes and efforts to improve decision making leads to the creation of new approaches and techniques to support designers in order to improve product quality. This scenario has given rise to the appearance of hybrid prototypes (HP), defined as the simultaneous presence of a virtual representation, either through virtual reality (VR) or AR and physical support [24,25]. Thus, the application of these processes results in a reduction of time in the manufacture of prototypes and, therefore, of the conceptualization phase [26]. In addition, it allows the process to use fewer materials, produce less waste and consume less energy, achieving the same result [27,28]. These techniques make it possible to combine virtual interaction with physical interaction, studying specific aspects of the product [29]. However, there is no methodology that is oriented towards the evaluation and selection of textures and reliefs, being this an important facet in the detailed design of a product. There is currently a multitude of methods and techniques to help designers to graphically represent a product. Among the most commonly used are rendering and animation techniques, although it should be noted that advanced techniques have recently appeared such as VR and AR [30,31]. In addition, other methods are being developed that focus on the choice of sounds, such as the door of a car when it closes [32] or the sound of an office chair as it slides [33]. Similarly, there is a long tradition of perfumers who create essences capable of evoking emotions through past memories [34]. However, when it comes to the choice of textures, the industry employs traditional methods based on catalogs of commercial samples [35], so there is no satisfactory framework for exploiting the haptic sensitivity of the user as a means of conveying concrete emotions that enhance the user experience and help communicate concepts related to the product or the brand image of the manufacturer. In addition, these methods do not allow the haptic property to be connected to other properties, such as the visual property [36]. Although touch is capable of evoking memories of our subconscious and helps to communicate the concepts we wish to transmit, other products also require integrating the haptic experience with the rest of the senses and aligning them with the objectives of the project, as in the case of packaging or other products that may come into contact with the user [37]. An outstanding example is the interior of a car, where the texture of the steering wheel, the upholstery or the plastics of the dashboard must be aimed at achieving the same objective. Thus, in order to transmit emotions, it is important to determine what message is to be transmitted through the product and by what sensory means this information reaches the user. Studies have shown that the most diverse sensory system is touch, as it is not limited to perceiving textures, but also thermal, chemical or mechanical characteristics and allow the person to collect more data about their weight, pressure, temperature, humidity, or determine if the surface is slippery [38]. In this way, it has been stated that touch is more accurate than vision when evaluating changes in the surface of Appl. Sci. 2019, 9, 5081 3 of 20 anAppl. object Sci. 2019 [36, 9]., x This FOR PEER ability REVIEW makes touch an important means of emotional communication between3 of 20 product and user. It is for this reason that this article aims to provide a method to assess and predict hapticpredict communication haptic communication early and early effi cientlyand efficiently by creating by creating the haptic the hybrid haptic prototyping hybrid prototyping (HHP) concept. (HHP) Inconcept. order toIn validateorder to thevalidate method, the thismethod, article this carries articl oute carries an experiment out an experiment with 56 participants with 56 participants in which the in perceptionwhich the perception of users is evaluatedof users is byevaluated substituting by substituting the final products the final with products HHP. with HHP.

2. Haptic Hybrid Prototyping (HHP): Method Overview This article studies the developmentdevelopment of a methodmethod thatthat combinescombines haptichaptic andand visualvisual experienceexperience withwith thethe aimaim ofof transmittingtransmitting aa certaincertain message.message. Fo Forr this purpose the concept of HHP is created, a method that aims to shorten the product design phasephase in the early stages, reducing costs and making the processprocess moremore eefficient.fficient. The developmentdevelopment of this method, based on the AR technique,technique, provides a methodology thatthat serves as a means of validating texturestextures or reliefs and ribs fr fromom simulation by finitefinite elements. This isis aa methodologymethodology thatthat serves serves to to test test the the solutions, solutions, to to meet meet the the communication communication needs needs of users,of users, that that reduces reduces costs andcosts prototyping and prototyping times, eventually times, eventually using additive using manufacturing additive manufacturing techniques. Figuretechniques.1 outlines Figure these 1 outlines five ways thes leadinge five ways to the leading justification to the andjustification creation ofand HHPs. creation of HHPs.

Figure 1. Pathways leading to the creation of haptic hybrid prototyping (HHP). Figure 1. Pathways leading to the creation of haptic hybrid prototyping (HHP). This integration of solutions in a single method has been the product of the study and observation This integration of solutions in a single method has been the product of the study and of multiple investigations. Accordingly, there are some projects of special relevance that served as observation of multiple investigations. Accordingly, there are some projects of special relevance that precursors of HHP. In 2005, Lee and Park created prototypes of products with foamed material that is served as precursors of HHP. In 2005, Lee and Park created prototypes of products with foamed easy to work with. They included a QR code to add different aesthetic aspects to evaluate in AR. To test material that is easy to work with. They included a QR code to add different aesthetic aspects to their proposal they superimposed the virtual and physical models of a cup and a vacuum robot [39]. evaluate in AR. To test their proposal they superimposed the virtual and physical models of a cup In this experiment, the authors evaluated the physical appearance of a product without the need to and a vacuum robot [39]. In this experiment, the authors evaluated the physical appearance of a create a detailed the prototype. This experiment can be considered as a visual validation prototype. product without the need to create a detailed the prototype. This experiment can be considered as a Another important milestone came in 2009, at the 8th Berlin Workshop Human-Machine-Systems visual validation prototype. BWMMS’09, whereby a hybrid is created between a mechatronic prototype and a VR image for the Another important milestone came in 2009, at the 8th Berlin Workshop Human-Machine- purpose of evaluating functional characteristics of a product. The combination of physical and virtual Systems BWMMS’09, whereby a hybrid is created between a mechatronic prototype and a VR image parts was called smart hybrid prototyping (SHP) [25,28,40]. In this experiment, it was possible to for the purpose of evaluating functional characteristics of a product. The combination of physical and interact with a physical product in a virtual environment. virtual parts was called smart hybrid prototyping (SHP) [25,28,40]. In this experiment, it was possible to interact with a physical product in a virtual environment. Recently, a novel methodology called VPModel has also been published, which uses mixed reality (MR) through Microsoft MR HoloLens glasses, a leap motion controller and 3D printing Appl. Sci. 2019, 9, 5081 4 of 20

Appl.Recently, Sci. 2019, 9 a, x novel FOR PEER methodology REVIEW called VPModel has also been published, which uses mixed reality4 of 20 (MR) through Microsoft MR HoloLens glasses, a leap motion controller and 3D printing technology totechnology make a physical-virtual to make a physical-virtual hybrid prototype hybrid capable prototype of detecting capable handof detecting gestures hand and recognizinggestures and actionsrecognizing [41]. Thisactions methodology [41]. This methodology was put into was practice put in into the practice creation in the of acreation digital of camera, a digital in camera, which thein userwhich could the user handle could the handle product the in product a situation in a ofsitu useation similar of use to similar the real to one.the real The one. objective The objective of the VPModelof the VPModel is to provide is to informationprovide information on the general on th geometrye general ofgeometry the product of the and product in turn implementand in turn graphicimplement information. graphic information. However,However, through through the the creation creation of theof the HHPs, HHPs, there there has beenhas been a response a response to the to need the to need use theto use sense the ofsense touch of as touch a means as a of means transmitting of transmitting semantic semantic content related content to related the product to the or product the marketing or the company.marketing Incompany. this way, itIn helps this theway, product it helps design the product teams to desi choosegn teams the textures to choose and reliefsthe textures that communicate and reliefs thethat keycommunicate information the detailed key information in the design detailed requirements, in the desi thusgn reaching requirements, the end thus user reaching in a more the effi endcient user and in effaective more way.efficient and effective way. TheThe HHP HHP method method is is based based on on the the integration integration of of haptic haptic and and visual visual sense. sense. Commercial Commercial texture texture and and reliefrelief samples samples and and a devicea device capable capable of of working working with with AR AR applications applications are are used used (Figure (Figure2). The 2). The aim isaim to is useto use partial partial samples samples of texture of texture and and relief relief and and to completeto complete the the geometry geometry of of the the product product by by means means of of virtualvirtual modeling. modeling. This This allows allows the userthe user to receive to receive the haptic the haptic and visual and information visual information he needs tohe perceiveneeds to aperceive situation a of situation use similar of use to thesimilar real one.to the real one.

Figure 2. HHP method overview. Figure 2. HHP method overview. In order for HHPs to be useful, easily reproducible and inexpensive to implement in design In order for HHPs to be useful, easily reproducible and inexpensive to implement in design teams around the world, a simple methodological design has been sought. Thus, it is not necessary to teams around the world, a simple methodological design has been sought. Thus, it is not necessary manufacture physical prototypes or expensive pre-series by means of final manufacturing technologies. to manufacture physical prototypes or expensive pre-series by means of final manufacturing By means of AR technology and commercial samples it is possible to approach experiences of use of technologies. By means of AR technology and commercial samples it is possible to approach finished products. It is convenient to point out that although in this application the samples used are experiences of use of finished products. It is convenient to point out that although in this application flat, it is possible to use any geometry, two-dimensional or three-dimensional, with any relief or texture. the samples used are flat, it is possible to use any geometry, two-dimensional or three-dimensional, In summary, this study is based on the hypothesis that the haptic-visual experience of a user with any relief or texture. before a real product can be extrapolated to the interaction with an HHP through samples of textures In summary, this study is based on the hypothesis that the haptic-visual experience of a user and three-dimensional images using AR. before a real product can be extrapolated to the interaction with an HHP through samples of textures and three-dimensional images using AR.

Appl. Sci. 2019, 9, 5081 5 of 20

3. Materials and Methods

3.1. Ethical Implications Participants have been provided with understandable information about the experimental procedure. There are no known dangers for participants. All subjects have participated voluntarily and could have decided to leave the study at any time without explanation. The data collected in this research are anonymous and their use will be regulated by the current legislation on the protection of personal data.

3.2. Participants The study involved 56 members from the community of the Faculty of Engineering of the University of Cádiz, of whom 42 were men and 14 women. 75% of those surveyed were between 18 and 30 years old; 16% were between 31 and 40; and 9% were between 41 and 50. It should be noted that 82.1% of participants studied engineering degrees that are offered at the educational center where the study was carried out. All of the participants carried out the same experiment.

3.3. Materials The virtual models of the products evaluated were generated with the computer-aided design program Solidworks® (2019 version, Dassault Systèmes SE, Velizy-Villacoublay, France), commonly used by industrial designers, and the virtual models were generated using the AR program Unity® (12 October 2017, 2.0f3 version, Unity Technologies, San Francisco, CA, USA). This software was selected because it represents the virtual perspective of a high-quality object, provides fluid movement and rendering allows for a clear appreciation of changes in the plane of the containers studied. The engine of the AR software used was Vuforia® Engine 8.3, which uses deep learning to generate the graphic models instantly. In order to associate the CAD models in AR with the samples, each of the products was associated with a QR code with the minimum size to be read by the application: 47 47 mm. × It should be added that the combination of the CAD model, the sample and the QR code result in the HHP. Physical finishing samples have been developed in this experiment using additive manufacturing and thermoforming techniques. Afterwards they were attached to a support, which includes the QR code, to allow manipulation of the samples while evaluating the virtual image. Also, although the AR program allows use of any digital device, we have worked with a 10.1 inch Samsung® Tab A 2016 Tablet with an IPS display with a maximum resolution of 1920 1200 was used to improve the × functionality of the procedure. In addition, four types of packaging have been created for the purpose of carrying out the experiment, which, in turn, includes four different reliefs. Figure3 shows the geometries used, where the model type A presents relief in the form of sawtooth, type B a dot pattern, type C ribs and type D undulations. Figure4 shows a comparative example of visualization of the physical and virtual product. The physical prototype, Figure4a, has a transparent finish and the virtual prototype has a white finish, Figure4b, showing in the image the superposition of the prototype in AR over the physical prototype. Appl. Sci. 2019, 9, x FOR PEER REVIEW 6 of 20

Appl. Sci. 2019, 9, 5081 6 of 20 Appl. Sci. 2019, 9, x FOR PEER REVIEW 6 of 20

(a) (b) (c) (d)

Figure 3. Design of moulds for thermoforming. (a) Model A mould with sawtooth relief; (b) Model B mould with(a) relief formed by a dot pattern;(b) (c) Model C mould(c) with ribs; (d) Model D (mouldd) with undulating relief. Figure 3. Design of moulds for thermoforming. (a) Model A mould with sawtooth relief; (b) Model Figure 3. Design of moulds for thermoforming. (a) Model A mould with sawtooth relief; (b) Model B FigureB mould 4 shows with relief a comparative formed by aexample dot pattern; of visualization (c) Model C mould of the with physical ribs; ( dand) Model virtual D mould product. with The mould with relief formed by a dot pattern; (c) Model C mould with ribs; (d) Model D mould with physicalundulating prototype, relief. Figure 4a, has a transparent finish and the virtual prototype has a white finish, undulating relief. Figure 4b, showing in the image the superposition of the prototype in AR over the physical prototype. Figure 4 shows a comparative example of visualization of the physical and virtual product. The physical prototype, Figure 4a, has a transparent finish and the virtual prototype has a white finish, Figure 4b, showing in the image the superposition of the prototype in AR over the physical prototype.

(a) (b)

FigureFigure 4. 4.ImagesImages of ofthe the experiment: experiment: (a) ( aImage) Image of ofthe the real real packaging packaging and and (b ()b packaging) packaging in inaugmented augmented realityreality (AR) (AR) superimposed superimposed with with the the real real one. one. (a) (b) ForFor the the physical physical samples, samples, the the moulds moulds of of the the containers containers were were constructed constructed by by means means of of additive additive Figure 4. Images of the experiment: (a) Image of the real packaging and (b) packaging in augmented manufacturingmanufacturing (FFF) (FFF) on on a aZortrax Zortrax M200 M200 printer. printer. They They were were printed printed using using a layer a layer height height of of0.2 0.2 mm, mm, reality (AR) superimposed with the real one. fillingfilling density density of of 15% 15% and and wall wall of of 1.4 1.4 mm mm to to pr preventevent the the surface surface roughness roughness caused caused by by the the layer layer manufacturingmanufacturing of of the the FFF FFF from from being being transmitted transmitted to tothe the thermoformed thermoformed sheet, sheet, in inaccordance accordance with with [42]. [42 ]. For the physical samples, the moulds of the containers were constructed by means of additive Hence,Hence, users users were were only only able able to to perceive perceive the the designed designed reliefs. reliefs. manufacturingThe containers (FFF) were on a thenZortrax manufactured M200 printer. using They a Formech were printed 450DT using thermoforming a layer height machine of 0.2 withmm, afilling 500 µ densitym thick of transparent 15% and PETwall sheet.of 1.4 Thismm materialto prevent allows the thesurface containers roughness to be caused transparent by the and layer the colourmanufacturing does not of distract the FFF the from interviewees. being transmitted to the thermoformed sheet, in accordance with [42]. Hence, users were only able to perceive the designed reliefs. Appl. Sci. 2019, 9, x FOR PEER REVIEW 7 of 20

The containers were then manufactured using a Formech 450DT thermoforming machine with a 500 µm thick transparent PET sheet. This material allows the containers to be transparent and the colour does not distract the interviewees. Figure 5 shows the three physical products evaluated and the three QR-coded flat relief samples used to generate HHP by using AR. Thus, the coding of the relief samples, with associated QR code, is the same as the container to which the sample corresponds and the termination AR has been added. In order to carry out the experiment, 6 samples were manufactured, Figure 5: two samples of the Appl.type Sci. A2019 and, 9 B, 5081 container models and one sample for types C and D (Figure 3). This is due to the7 of fact 20 that the prototypes type A and B were evaluated by means of the conventional experimental physical prototypeFigure 5and shows by means the three of the physical HHP method products proposed evaluated in and this thework. three These QR-coded parts tested flat relief with samples AR were usedcalled to A-AR generate and HHP B-AR by in using Figure AR. 5. Thus,On the the other coding hand, of thethe reliefthermoformed samples, with prototype associated type QR C, Figure code, is 5, thehas same been as evaluated the container only tophysically, which the and sample the sample corresponds type D and has the been termination evaluated AR virtually has been with added. HHP, Figure 5, called D-AR in the experiment.

(a) (b) (c)

(d) (e) (f)

Figure 5. Nomenclature of containers and samples used in the experiment: (a) Sample A-AR, with sawtoothFigure 5. relief; Nomenclature (b) Sample of B-AR, containers with dotand patternsamples texture; used in (c the) Sample experiment: D-AR, ( witha) Sample undulated A-AR, relief; with (dsawtooth) Packaging relief; A, ( withb) Sample reliefs B-AR, in the with form dot of pattern saw teeth; texture; (e) Packaging(c) Sample B,D-AR, with with dot patternundulated texture; relief; (f()d Packaging) Packaging C, A, with with relief reliefs in the in formthe form of ribs. of saw teeth; (e) Packaging B, with dot pattern texture; (f) Packaging C, with relief in the form of ribs. In order to carry out the experiment, 6 samples were manufactured, Figure5: two samples of the type A and B container models and one sample for types C and D (Figure3). This is due to the fact that the prototypes type A and B were evaluated by means of the conventional experimental physical prototype and by means of the HHP method proposed in this work. These parts tested with AR were called A-AR and B-AR in Figure5. On the other hand, the thermoformed prototype type C, Figure5, has been evaluated only physically, and the sample type D has been evaluated virtually with HHP, Figure5, called D-AR in the experiment. Accordingly, in order to make the samples that make up part of the proposed HHP, a wall of the thermoformed container was cut to remove only the reliefs designed on type A, B and D containers in Figure3. As shown in Figure6, a support with three legs was placed on the cut samples, which was used as a separator, at a distance of 35 mm, with the generated QR code, which was designed to touch the finishing sample without hiding the QR code from the camera. An effect of the superimposition of the virtual product on the hand was achieved on the screen. Appl. Sci. 2019, 9, x FOR PEER REVIEW 8 of 20

Accordingly, in order to make the samples that make up part of the proposed HHP, a wall of the thermoformed container was cut to remove only the reliefs designed on type A, B and D containers in Figure 3. As shown in Figure 6, a support with three legs was placed on the cut samples, which was used as a separator, at a distance of 35 mm, with the generated QR code, which was

Appl.designed Sci. 2019 to, 9touch, 5081 the finishing sample without hiding the QR code from the camera. An effect of8 of the 20 superimposition of the virtual product on the hand was achieved on the screen.

Figure 6.6. A-AR relief sample with QR code and support. 3.4. Evaluation of Haptic-Visual Properties 3.4. Evaluation of Haptic-Visual Properties The survey created was divided into seven blocks, the first relating to user data: sex, age, and The survey created was divided into seven blocks, the first relating to user data: sex, age, and level of education. The remaining six were related to the pieces studied. In each of these blocks the level of education. The remaining six were related to the pieces studied. In each of these blocks the concepts were ordered randomly, maintaining 10 concepts related to texture: silky, dirty, abrasive, concepts were ordered randomly, maintaining 10 concepts related to texture: silky, dirty, abrasive, rough, soft, sharp-edge, clean, slippery, adherent and smooth, but adding other concepts related to rough, soft, sharp-edge, clean, slippery, adherent and smooth, but adding other concepts related to other properties of temperature, hardness, shape, and weight. The aim of adding these adjectives other properties of temperature, hardness, shape, and weight. The aim of adding these adjectives was was to prevent the respondent from relating the experiment only with the haptic characteristics of the to prevent the respondent from relating the experiment only with the haptic characteristics of the packaging. In this way, it was intended that the interviewee did not know the objective of the study packaging. In this way, it was intended that the interviewee did not know the objective of the study and, therefore, did not unintentionally alter the result of the work. and, therefore, did not unintentionally alter the result of the work. Each of the concepts evaluated could be graded, on a Likert scale, between 1 (not at all adequate) Each of the concepts evaluated could be graded, on a Likert scale, between 1 (not at all adequate) and 5 (very adequate). During the bibliographic review it was detected that this five-point scale has and 5 (very adequate). During the bibliographic review it was detected that this five-point scale has been used in other research on applied haptic experience in product design [43] or in emotion research been used in other research on applied haptic experience in product design [43] or in emotion by means of Kansei Engineering [44]. Thus, the aim of the questionnaire was to ask users about research by means of Kansei Engineering [44]. Thus, the aim of the questionnaire was to ask users concepts related to the haptic experience of the samples while they are watching and manipulating about concepts related to the haptic experience of the samples while they are watching and the physical prototype and to contrast their answers with those reported after performing the same manipulating the physical prototype and to contrast their answers with those reported after process with the hybrid prototype. It is important to point out that the value they gave to each concept performing the same process with the hybrid prototype. It is important to point out that the value is not relevant for the study, but to know if its answer does not depend on the visual medium used. they gave to each concept is not relevant for the study, but to know if its answer does not depend on 3.5.the visual Procedure medium used.

3.5. ProcedureThe participants were moved one by one to an empty, quiet and well-illuminated room. Participants were not informed about the purpose of the study. There were no distractions. They were made to sit at a tableThe withparticipants a computer were monitor moved and one mouse by one and to asked an empty, to complete quiet the and first well-illuminated survey data relating room. to theirParticipants gender, were age, andnot educationalinformed ab level.out the The purpose rest of the of experimentthe study. Th wasere divided were no into distractions. two phases: They werePhase made 1:to sit Packaging at a table Awith was a computer delivered monito to ther subjects and mouse (Figure and7 asked). The to subjectscomplete were the first informed survey thatdata thererelating was to no their time gender, limit and age, they and wereeducational asked to level. manipulate The rest theof the packaging experiment and was then divided answer into the questionnairetwo phases: questions on the computer. At the end of the process, the container was removed and B was handedPhase 1: over Packaging with the A same was instructions.delivered to Thenthe subjects it wasrepeated (Figure 7). with The packaging subjects C.were The informed interviewees that couldthere notwassee no whichtime limit samples and would they were be given asked to themto manipulate or the number the packaging of them. and then answer the questionnairePhase 2: Aquestions Tablet was on placedthe computer. in front At of the en intervieweesd of the process, on a support the container that maintained was removed it in and an upright position. The A-AR sample was given to them and they were asked to place it in front of the camera so that they had to see it through the screen (Figure8). They were asked to manipulate it, but always seeing it through the device. As they did this, they answered the questions on the questionnaire using the mouse. Next, they were given the D-AR sample and given the same instructions. The procedure was repeated with the B-AR sample. The HHP images obtained for these three products are shown in Table A1. Appl. Sci. 2019, 9, x FOR PEER REVIEW 9 of 20

B was handed over with the same instructions. Then it was repeated with packaging C. The interviewees could not see which samples would be given to them or the number of them.

Appl. Sci. 2019, 9, x FOR PEER REVIEW 9 of 20

Appl.B was Sci. 2019handed, 9, 5081 over with the same instructions. Then it was repeated with packaging C.9 ofThe 20 interviewees could not see which samples would be given to them or the number of them.

Figure 7. Manipulation of sample A.

Phase 2: A Tablet was placed in front of the interviewees on a support that maintained it in an upright position. The A-AR sample was given to them and they were asked to place it in front of the camera so that they had to see it through the screen (Figure 8). They were asked to manipulate it, but always seeing it through the device. As they did this, they answered the questions on the questionnaire using the mouse. Next, they were given the D-AR sample and given the same Figure 7. Manipulation of sample A. instructions. The procedure was repeatedFigure 7. withManipulation the B-AR of sample. sample A.The HHP images obtained for these three Phaseproducts 2: A are Tablet shown was in placed Table A1.in front of the interviewees on a support that maintained it in an upright position. The A-AR sample was given to them and they were asked to place it in front of the camera so that they had to see it through the screen (Figure 8). They were asked to manipulate it, but always seeing it through the device. As they did this, they answered the questions on the questionnaire using the mouse. Next, they were given the D-AR sample and given the same instructions. The procedure was repeated with the B-AR sample. The HHP images obtained for these three products are shown in Table A1.

FigureFigure 8. 8. ManipulationManipulation of of the the sample sample A A and and vi visionsion of of the the AR AR through through a tablet.

WithWith regard to the evaluation order of the samples from both phases, an attempt was made to to hinderhinder the the relationship relationship of of the the physical physical flat flat sample samples,s, phase phase 2, 2, with with the the physical physical products products evaluated, evaluated, phase 1, varying the order of evaluation, thus ensuring the reliability of the results.

4.4. Results Results and and Discussion Discussion Figure 8. Manipulation of the sample A and vision of the AR through a tablet. AsAs mentioned above, ofof thethe fourfour models models used used in in the the experiment, experiment, only only models models A andA and Bare B are used used for forthe the assessmentWith assessment regard of theto of the reliabilitythe evaluation reliability of the oforder methodologythe ofmethod the samplesology applicable applicable from toboth product to phases, product design. an design. attempt These These modelswas mademodels could to couldbehinder evaluated be the evaluated relationship in parallel in parallelof during the physical theduring physical flatthe samplephys handlingicals, phasehandling of the 2, packaging with of thethe paphysical andckaging through products and AR through technology evaluated, AR technologyusingphase the1, varying HHP using method. thethe orderHHP The method.of studied evaluation, The attributes studied thuswere ensuring attrib evaluatedutes the were reliability with evaluated respect of the to with theresults. degreerespect ofto coincidence the degree ofof coincidence both results. of both results. 4. Results and Discussion 4.1. Analysis of Coincidence between Physical Prototypes and HHP As mentioned above, of the four models used in the experiment, only models A and B are used Table1 shows the sum of the answers given to each attribute indicating the level of coincidence for the assessment of the reliability of the methodology applicable to product design. These models for product type A between both experiments: physical prototype and HHP method. From the sum of could be evaluated in parallel during the physical handling of the packaging and through AR the results obtained in all adjectives by the level of coincidence, it can be deduced that in 216 responses technology using the HHP method. The studied attributes were evaluated with respect to the degree the deviation of the results was 1 on a weighting of 5 points. Secondly, and no less representatively, of coincidence of both results. ± 201 answers were obtained with total coincidence in the answers, the numerical value of the rest of the answers were much lower. Therefore, in a first approximation of the results, it was detected that the Appl. Sci. 2019, 9, x FOR PEER REVIEW 10 of 20

4.1. Analysis of Coincidence between Physical Prototypes and HHP Table 1 shows the sum of the answers given to each attribute indicating the level of coincidence for product type A between both experiments: physical prototype and HHP method. From the sum of the results obtained in all adjectives by the level of coincidence, it can be deduced that in 216 responses the deviation of the results was ±1 on a weighting of 5 points. Secondly, and no less representatively, 201 answers were obtained with total coincidence in the answers, the numerical valueAppl. Sci. of 2019the, rest9, 5081 of the answers were much lower. Therefore, in a first approximation of the results,10 of 20 it was detected that the HHP method allows the analysis of haptic-visual properties in the field of industrial design, generating an evaluable sensory experience [45]. HHP method allows the analysis of haptic-visual properties in the field of industrial design, generating an evaluableTable 1. sensory Number experienceof accumulated [45]. responses according to the degree of coincidence of product A.

Sharp TableSilky 1. NumberDirty Abrasive of accumulated Rough responses Soft according toClean the degreeSlippery of coincidence Adherent of Smoothproduct A.Σ -Edge C Silky24 Dirty22 Abrasive 32 Rough 24 Soft 14 Sharp-Edge 12 25 Clean 18 Slippery Adherent 11 Smooth 19 201 Σ CC±1 2419 2219 32 18 24 26 14 24 24 12 18 25 24 18 30 11 14 19216 201 C 1 19 19 18 26 24 24 18 24 30 14 216 ± CC±22 99 88 4 4 2 2 1515 16 16 9 9 11 11 11 11 16 16101 101 ± C 3 4 6 1 4 3 4 3 3 4 4 36 C±3± 4 6 1 4 3 4 3 3 4 4 36 C 4 01100010036 C±4± 0 1 1 0 0 0 1 0 0 3 6

On the other hand, Figure9 shows the results obtained in Table1 as a percentage of responses. On the other hand, Figure 9 shows the results obtained in Table 1 as a percentage of responses. An overall analysis of the results shows that the deviation of 3 and 4 is reduced in comparison An overall analysis of the results shows that the deviation of ±3± and ±4± is reduced in comparison to to the responses that present a greater similarity. Thus, of the 10 attributes studied, the answers in the responses that present a greater similarity. Thus, of the 10 attributes studied, the answers in 5 of 5 of them present a total coincidence: silky, dirty, abrasive, clean and smooth. Among them, the them present a total coincidence: silky, dirty, abrasive, clean and smooth. Among them, the adjective adjective “abrasive” stands out, for which 57.1% of the participants coincided in their answers in both “abrasive” stands out, for which 57.1% of the participants coincided in their answers in both experiments. The minimum value of these terms is reached by the “smooth” attribute with 33.9%, experiments. The minimum value of these terms is reached by the “smooth” attribute with 33.9%, which means a difference of 23.2% between these terms. This adjective is also the one that presents which means a difference of 23.2% between these terms. This adjective is also the one that presents similar values between total coincidence, 1, 2 and 3. This may be due to the fact that product type similar values between total coincidence, ±±1, ±2± and ±3.± This may be due to the fact that product type A presents angulated plane changes where the surface finish of the plastic material is intentionally A presents angulated plane changes where the surface finish of the plastic material is intentionally non-abrasive, due to the lack of discontinuities that the product presents, to evaluate the degree of non-abrasive, due to the lack of discontinuities that the product presents, to evaluate the degree of flatness of a piece is complex, with which the degree of dispersion of responses is higher. flatness of a piece is complex, with which the degree of dispersion of responses is higher.

60%

50%

40%

Coincidence 30% Coincidence ±1 20% Coincidence ±2 Total answers answers Total (%) 10% Coincidence ±3

Coincidence ±4 0%

Adjectives

Figure 9. Cumulative coincidence of responses for product type A. Figure 9. Cumulative coincidence of responses for product type A. As to the degree of coincidence 1, the adjectives that stand out are “rough”, “soft”, “sharp-edge”, ± “slippery”As to the and degree “adherent”. of coincidence Where the ±1, highest the adjectives value is that for stand “adherent” out are with “rough”, 53.6% “soft”, and the “sharp- lowest edge”,for “soft” “slippery” and “sharp-edge” and “adherent”. with 42.9%. Where These the highes data indicatet value thatis for there “adherent” is a difference with 53.6% between and these the lowestterms offor 10.7%. “soft” Itand is also “sharp-edge” important with to point 42.9%. out Thes thate the data adjectives indicate “soft”, that ther “sharp-edge”e is a difference and “smooth”between thesepresent terms a percentage of 10.7%. ofIt answersis also important with a 2 to coincidence point out that between the adjectives 20% and 30%.“soft”, It is“sharp-edge” possible that and the ± adjective “soft” has the same difficulty for users as the term “smooth” since both are related to the lack of discontinuities in the surface of the pieces. On the other hand, the term “sharp-edge” can direct the attention of respondents from the proposed reliefs to the edges of the pieces and cause a distortion in the statistics. As an overall result of the study of product type A it was obtained that 74.5% of the answers are concentrated between the total coincidence and 1. This result indicates that respondents tend to ± repeat their answers between the first and second phases exactly or with the minimum deviation. Appl. Sci. 2019, 9, x FOR PEER REVIEW 11 of 20

“smooth” present a percentage of answers with a ±2 coincidence between 20% and 30%. It is possible that the adjective “soft” has the same difficulty for users as the term “smooth” since both are related to the lack of discontinuities in the surface of the pieces. On the other hand, the term “sharp-edge” can direct the attention of respondents from the proposed reliefs to the edges of the pieces and cause a distortion in the statistics. As an overall result of the study of product type A it was obtained that 74.5% of the answers are concentrated between the total coincidence and ±1. This result indicates that respondents tend to repeatAppl. Sci. their2019 answers, 9, 5081 between the first and second phases exactly or with the minimum deviation.11 of 20 Table 2, analogous to Table 1, shows the sum of the answers given to each attribute, indicating the level of coincidence for the type B product between both experiments. In the summation, it is observedTable that2, analogous228 responses to Table correspond1, shows to the a deviatio sum ofn the of answers±1 on a weighting given to each of 5 attribute,points, followed indicating by totalthe levelcoincidence of coincidence with 224 for responses. the type BAs product in Table between 1, the rest both of experiments. the answers Inare the much summation, smaller itin is observed that 228 responses correspond to a deviation of 1 on a weighting of 5 points, followed magnitude than the rest of the data. In this way it is observed that± in product B there is also a tendency toby respond total coincidence with a total with coincidence 224 responses. or ±1 so As this in second Table1 ,product the rest also of the suggests answers that are the much HHP smaller method in makesmagnitude it possible than theto analyze rest of the haptic-visual data. In this properties way it is observed in the field that of in industrial product B design, there is generating also a tendency an to respond with a total coincidence or 1 so this second product also suggests that the HHP method assessable sensory experience. ± makes it possible to analyze haptic-visual properties in the field of industrial design, generating an assessableTable 2. sensoryNumber experience.of cumulative responses according to the degree of coincidence for product type B.

Sharp TableSilky 2. NumberDirty ofAbrasive cumulative Rough responses Soft according to theClean degree Slippery of coincidence Adherent for product Smooth type Σ B. -Edge C Silky31 Dirty31 Abrasive 32 Rough 23 Soft 16 Sharp-Edge 8 33 Clean 18 Slippery Adherent 15 Smooth17 224 Σ C±1C 1831 18 31 32 15 23 23 16 33 25 8 12 33 29 18 27 15 28 17228 224 C 1 18 18 15 23 33 25 12 29 27 28 228 ± C±2C 2 77 5 9 9 7 7 5 5 15 15 9 9 7 7 9 9 7 780 80 ± C 3 0 1 0 3 2 7 2 2 4 4 25 C±3± 0 1 0 3 2 7 2 2 4 4 25 C 4 01000100103 C±4± 0 1 0 0 0 1 0 0 1 0 3

OnOn the the other other hand, hand, Figure Figure 10 10 shows shows the the results results obta obtainedined in in Table Table 22 as as a apercentage percentage of of responses. responses. InIn a adeeper deeper analysis analysis of of the the results, results, it it is is observed observed that that the the deviation deviation of of ±3 3and and ±4 4is is comparatively comparatively ± ± reducedreduced and and can can be be considered considered irrelevant, irrelevant, which which reinforces reinforces the the validation validation of of the the method method in in the the same same wayway as as for for the the A A packaging. packaging. In In additi addition,on, from from the the results results it itis isextracted extracted that that there there are are 4 4adjectives adjectives that that presentpresent a a majority ofof totaltotal coincidence coincidence for for product produc B,t theseB, these are: are: “silky”, “silky”, “dirty”, “dirty”, “abrasive” “abrasive” and “clean”. and “clean”.Specifically, Specifically, this last this term last represents term represents the highest the percentagehighest percentage of coincidence of coincidence with 58.9% with and 58.9% the termsand the“silky” terms and “silky” “dirty” and have “dirty” had thehave lowest had the percentage lowest percentage of coincidence of coincidence with 54.4% each.with 54.4% This indicates each. This that indicatesthere is onlythat there a 3.5% is di onlyfference a 3.5% between difference the highestbetween hit the values. highest hit values.

60%

50%

40%

Coincidence 30% Coincidence +/-1 20% Coincidence +/-2 Total answers answers Total (%) 10% Coincidence +/-3

Coincidence +/-4 0%

Adjectives

Figure 10. Cumulative match of responses for product type B. Considering theFigure values 10. of Cumulative coincidence match2, itof isrespon observedses for that product the adjectivestype B. that present greater ± reliability between answers are “soft”, “sharp-edge”, “slippery”, “adherent” and “smooth”. The highest value is produced for “soft” with 58.9% and the lowest for “sharp-edge” with 44.6%, there is a difference of 14.3% between them. Regarding the values for the 3 coincidence, only the term “Sharp-edge” is between 20% and ± 30%, with the rest of the data being much lower. As a global result of the study of product type B it is obtained that 80.7% of the answers are concentrated between the total coincidence and 1. As in product A, this result indicates that the ± Appl. Sci. 2019, 9, 5081 12 of 20 respondents tend to repeat their answers between the first phase and the second in an exact way or with the minimum deviation. In a comparative evaluation between Figures9 and 10, it is observed that the total coincidences and the coincidences 1 have increased in product B with respect to A for all the adjectives evaluated ± except for the term “rough”. Based on this, it should be noted that the maximum deviation between the maximum value reached in product A and the lowest in product B for the concept “rough” occurs for the coincidence 1 and is 5.3%. This value in comparison with the increments that have experienced ± the rest of adjectives can be considered unrepresentative. This general increase in the coincidence between one product and another indicates that the dot pattern texture generates less response dispersion than the sawtooth texture and the results obtained are clearer. It can, therefore, be deduced that with the HHP method it is possible to distinguish between textures that communicate concepts clearly (categorical responses) or confusingly (dispersion of responses), being able to choose not only what information is to be transmitted, but also the clarity of this. In the same way and regulating the level of texture, it would be possible to regulate the intensity of the concept transmitted, having an influence on the emotion produced and associated with that concept [46]. It is important to point out that this experience is not only linked to the haptic sense, but to the union of this sense with the sense of view. Accordingly, in the mind of the user this sensory information is linked to the product in an inseparable way [47,48] so that it was this texture associated with that image that led him or her to transmit a semantic content and with it, evoke an emotion [49] and not the perception of both pieces of information separately. Thus, the design team of the trading company can use this sensory and cognitive experience to communicate through its products a concrete brand image [50,51] detecting this synergetic effect of two sensory channels together with a concrete memory and an associated emotion. All this becomes more valuable when detected at a very early stage of the design phase, enabling the working methodology proposed in this article to be made more efficient and effective. On the other hand, there is also a strong parallelism in the level of overlap between product A and product B. So all adjectives where total matches predominate in one product also do in the other. In the case of total coincidence, these adjectives are “silky“, “dirty“, “abrasive“ and “clean”. And in the same way, all the adjectives in which the 1 match is predominant in product A also coincide in ± product B. These are “soft“, “sharp-edge”, “slippery“ and “adherent“. This occurs with eight of the adjectives, except in the terms “smooth” where the predominance is opposite and the term “rough” where both coincidences, total and 1 are equal. This may be due, as explained above, to the fact that ± the adjective “smooth” in the plastic samples causes confusion in the users since the test samples do not deliberately show surface irregularities in both products, making it difficult to evaluate a change in flatness. Similarly, for the term “rough” the response deviation between products A and B is minimal so it is not considered relevant data. All of the above suggests that there are some terms that are more complex to evaluate and make the user tend to a slight dispersion in their responses. Therefore, it can be deduced that the level of success that the interviewees have in their answers depends on the evaluated adjectives and not on the textures or reliefs of the proposed pieces. Thus, on the one hand, the easiest adjectives to evaluate for the proposed products are “silky”, “dirty”, “abrasive” and “clean” and, on the other hand, the more complicated “soft”, “sharp-edge” “slippery” and “adherent”. It is also deduced that the adjective “smooth”, depending on the type of texture and relief evaluated, can generate greater uncertainty than the rest of the adjectives, producing the described tendency to move away from total coincidence. In order to analyses in a more detailed way the differences between the responses of products A and B, Figure 11 is carried out. It shows the sum of the percentages of total coincidence and 1 ± coincidence for each product and compares these values reached in both products. In this way, it is observed that in both products the adjective “sharp-edge” reports the lowest values, below 65%. As commented, it is possible that the term leads users to evaluate the cut made to produce the sample Appl. Sci. 2019, 9, x FOR PEER REVIEW 13 of 20 Appl. Sci. 2019, 9, x FOR PEER REVIEW 13 of 20 uncertainty than the rest of the adjectives, producing the described tendency to move away from total uncertaintycoincidence. than the rest of the adjectives, producing the described tendency to move away from total coincidence.In order to analyses in a more detailed way the differences between the responses of products A andIn B, order Figure to analyses11 is carried in a moreout. Itdetailed shows waythe thesum differences of the percentages between theof responsestotal coincidence of products and A±1 andcoincidence B, Figure for 11 each is carried product out. and It comparesshows the these sum values of the reachedpercentages in both of products.total coincidence In this way, and it±1 is coincidence for each product and compares these values reached in both products. In this way, it is Appl.observed Sci. 2019 that, 9, 5081 in both products the adjective “sharp-edge” reports the lowest values, below 65%.13 of As 20 observedcommented, that itin is both possible products that thethe adjectiveterm leads “sha usersrp-edge” to evaluate reports the the cut lowest made values, to produce below the 65%. sample As commented,shown and itthey is possible do not evaluatethat the termthe texture, leads users so a tocl arificationevaluate the in cutthe madeevaluation to produce of this the term sample or its shown and they do not evaluate the texture, so a clarification in the evaluation of this term or its shownsubstitution and they could do produce not evaluate higher the values texture, of success. so a clarification in the evaluation of this term or its substitutionsubstitution could could produce produce hi highergher values values of success.

100% 100%90% 90%80% 80%70% 70%60% 60% Product A 50% Product A 50%40% Product B Product B 40%30% Total answers answers Total (%) 30% Total answers answers Total (%) 20% 20%10% 10%0% 0%

Adjectives Adjectives

Figure 11. Percentage of responses that show total coincidence or 1 between products A and B. Figure 11. Percentage of responses that show total coincidence or± ±1 between products A and B. Figure 11. Percentage of responses that show total coincidence or ±1 between products A and B. If we analyze the differences between the percentages of success between pieces A and B (Figure 12), If we analyze the differences between the percentages of success between pieces A and B (Figure we observe that the adjective “smooth” has the highest value with 21.5%. This term is followed by 12), Ifwe we observe analyze that the thedifferences adjective between “smooth” the has percen the tageshighest of successvalue with between 21.5%. pieces This Aterm and is B followed (Figure “soft” with 19.6%. The rest of adjectives present increases of a lower magnitude. Once again it is 12),by “soft”we observe with 19.6%.that the The adjective rest of “smooth”adjectives haspresent the highest increases value of a with lower 21.5%. magnitude. This term Once is followedagain it is proven that users have problems when evaluating these concepts. Additionally, the evaluation of byproven “soft” that with users 19.6%. have The problems rest of adjectives when evaluating present increases these concepts. of a lower Additionally, magnitude. the Once evaluation again it isof these terms is sensitive to the texture evaluated. This may be due to the fact that users evaluate the proventhese terms that usersis sensitive have problemsto the texture when evaluated. evaluating Th theseis may concepts. be due to Additionally, the fact that theusers evaluation evaluate theof surface finish and not the reliefs of the containers. Therefore, if we want to evaluate these adjectives it thesesurface terms finish is sensitive and not theto the reliefs texture of the evaluated. containers. Th Thereforis may bee, dueif we to want the fact to evaluate that users these evaluate adjectives the is convenient to focus the user’s attention on the surface finish, eliminating the reliefs and at the same surfaceit is convenient finish and to not focus the thereliefs user’s of the attention containers. on the Therefor surfacee, finish,if we want eliminating to evaluate the reliefsthese adjectivesand at the time that these present very different roughness. Accordingly, greater percentages of response and itsame is convenient time that tothese focus present the user’s very differentattention roughneon the surfacess. Accordingly, finish, eliminating greater percentages the reliefs ofand response at the smaller increases between pieces could be obtained. sameand smallertime that increases these present between very pieces different could roughne be obtained.ss. Accordingly, greater percentages of response and smaller increases between pieces could be obtained.

SMOOTH SMOOTH ADHERENT ADHERENT SLIPPERY SLIPPERY CLEAN CLEAN SHARP-EDGE SHARP-EDGE SOFT

Adjectives SOFT ROUGH Adjectives ROUGH ABRASIVE ABRASIVE DIRTY DIRTY SILKY SILKY 0% 5% 10% 15% 20% 25% 0% 5% 10% 15% 20% 25% Difference of accuracy between product A and B (%) Difference of accuracy between product A and B (%) Figure 12. Increase in accuracy between products A and B considering the total coincidence and 1. Figure 12. Increase in accuracy between products A and B considering the total coincidence and± ±1. Figure 12. Increase in accuracy between products A and B considering the total coincidence and ±1. However, it should also be pointed out that the success rate could be increased by carrying out an experimental design more focused on certain haptic-visual experiences. Thus, examples such as the adjective “dirty” could be interpreted differently in the real prototype as synonymous with cleanliness or as image clarity in the virtual prototype. Therefore, by being careful in the preparation of the sample Appl. Sci. 2019, 9, x FOR PEER REVIEW 14 of 20

However, it should also be pointed out that the success rate could be increased by carrying out an experimental design more focused on certain haptic-visual experiences. Thus, examples such as the adjective “dirty” could be interpreted differently in the real prototype as synonymous with cleanliness or as image clarity in the virtual prototype. Therefore, by being careful in the preparation of the sample and clearly delimiting the limits of the essay and informing the subject of the objective sought the percentage of success between pieces could increase. Taking into account this information and in order to make the results of the experiment conform to reality, it is observed that the adjectives “smooth” and “soft” are causing an alteration in the Appl. Sci. 2019, 9, 5081 14 of 20 analysis of data, just as the term “sharp-edge” is also producing a bias in the results due to the problem of understanding the concept to be evaluated described above. For these reasons, a new analysisand clearly is carried delimiting out by eliminating the limits of these the essay three andadjectives. informing the subject of the objective sought the percentageTable 3 shows of success the sum between of answers pieces couldgiven increase. to products A and B together. It can be seen that by eliminatingTaking the into three account concepts this mentioned information above, and in us orderers reach to make thethe highest results value of the of experimentanswers for conform total coincidence,to reality, it with is observed a difference that the of adjectives5.4 points “smooth”above the and next “soft” coincidence, are causing the anrest alteration being a indownward the analysis progression.of data, just This as theinformation term “sharp-edge” reveals the issignificant also producing fact that a 81% bias of in the the answers results due are toconcentrated the problem in of theunderstanding first two rows theof the concept table. to be evaluated described above. For these reasons, a new analysis is carried out by eliminating these three adjectives. TableTable 3. Number3 shows of the cumulative sum of responses answers according given to to products the degree A of and coincidence B together. for products It can A be and seen B. that by eliminating the three concepts mentioned above, users reach the highest value of answers for total Silky Dirty Abrasive Rough Clean Slippery Adherent Σ % coincidence, with a difference of 5.4 points above the next coincidence, the rest being a downward progression.C 55 This information53 64 reveals the47 significant58 fact that36 81% of the 26 answers339 are concentrated43,2% in theC±1 first two37 rows of37 the table.33 49 30 53 57 296 37.8% C±2 16 13 13 9 18 18 20 107 13,6% C±3Table 3.4 Number7 of cumulative1 responses7 according5 to the degree5 of coincidence 8 for products37 4,7% A and B. C±4 0 Silky2 Dirty1 Abrasive 0 Rough1 Clean0 Slippery 1 Adherent 5 Σ 0,6% % C 55 53 64 47 58 36 26 339 43.2% TheseC 1 values37 are plotted 37 in Figure 33 13. 49This shows 30 the percentages 53 of 57 answers 296 and a 37.8% linear ± interpolationC 2 of the16 points 13 that show 13 a clear tendency 9 of 18 the users 18to correct. 20 107 13.6% ± C 3 4 7 1 7 5 5 8 37 4.7% It therefore± follows that HHPs can simulate a real experience of using a product in haptic visual C 4 0 2 1 0 1 0 1 5 0.6% terms, with± a probability of 81% and a dispersion of the set of measured values of ±1 over 5 points, implying an accuracy of ±20%. These values can guide design teams to know the tendency of users to understandThese values the semantic are plotted information in Figure of 13the. product This shows perceived the percentages in a multimodal of answers way and and with a linear it theinterpolation emotion associated of the points with that that cognitive show a clear processing. tendency of the users to correct.

50% 45% 40% 35% 30% 25% 20% 15% Total answers (%) 10% 5% 0% C C±1 C±2 C±3 C±4 Degree of coincidence

Figure 13. Percentage of responses and match levels for products A and B and their trendline. Figure 13. Percentage of responses and match levels for products A and B and their trendline. It therefore follows that HHPs can simulate a real experience of using a product in haptic visual terms, with a probability of 81% and a dispersion of the set of measured values of 1 over 5 points, ± implying an accuracy of 20%. These values can guide design teams to know the tendency of users to ± understand the semantic information of the product perceived in a multimodal way and with it the emotion associated with that cognitive processing.

4.2. Analysis of the Application of Augmented Reality (AR) Technology as Part of the HHP Method The experience of using AR technology as part of the design process was also analyzed during the HHP evaluation experiment. The majority of participants perceived that the technology is useful, being qualified as positive and realistic. However, they considered that the synchronization system Appl. Sci. 2019, 9, 5081 15 of 20 of the virtual image and the texture sample could be improved with the elimination of the QR code. The study of the application of the AR without code is considered of interest to improve the interaction of the prototype with the user. To this end, it has been observed the existence of AR software tools in which a photograph is used as a reference image for the virtual object [52]. This can be applied using the physical sample, although it is necessary to study the dynamic relationship between the user and the hybrid prototype since the virtual image could be lost with the movement of the physical pattern. In addition, it should be noted that the application of AR has been validated as a technique used in the perception of a product, so it can be improved through the application of rendering motors with photorealistic materials. On the other hand, in previous investigations prototypes and methodologies can be found that measure the functionality of a product and that use the new technologies of VR, AR, and MR to reproduce experiences close to those lived by the users in the real circumstances of their use. This is the case of the Smart Hybrid Prototyping (SHP), which was created for the rapid and efficient evaluation of mechatronic products early in the product design phase [53]. All these experiences use VR to generate an environment and, for this, facilities and technical preparation that require a relatively high investment are necessary [54]. In this context, the study carried out shows that HHPs improve these technical aspects through the use of AR, allowing an integration of the element created in a real environment, and not the other way around. This facilitates user immersion, creating more realistic experiences. In this way, the realization of these hybrid prototypes is less expensive, besides being faster to implement, with simple software preparation.

4.3. Sensory Experience and HHP In the study conducted with the HHP method created, it was observed that this method provides, in addition to a realistic haptic-visual multimodal integration, a way of being able to choose the sensations that users need to feel when faced with a specific product. This makes it possible for the product to be more competitive in the market. This way of detecting the information that is communicated to the client through the product makes is possible to carry it out in the early stages of the conceptualization of the product with the rapidity of implementation and effectiveness that the I4.0 demands. Accordingly, this simple evaluation method, thanks to HHP, provides the creation of a new method that offers the evaluation of a sensory experience related to the finishes of a product. In this way other techniques related to haptic experience have been investigated, however, few works of literature have been found about devices that recreate the sense of touch. An example of this is the creation of a glove prototype that allows hand movements to be monitored and acted on [55]. Work is also being done on the use of general-purpose devices such as the Phantom Omni, a device that is also applied in the simulation of a tool in an operating room or controlling a robot arm during a virtual mechanical assembly [43]. However, with this device when evaluating a texture a bias is generated in the transmitted information. In this device, it is not the user who can directly touch the texture sample and, therefore, this complex sensory chain of electrical currents of the body is replaced by one based on vibrations. This is not the case with HHP, where the haptic experience is real and it must also be added that the visual experience in the case of AR allows an integration of the object in the real environment, which creates an integrated multimodal experience and not a disaggregated experience. The simplicity of the use of HHPs also allows for a simpler and less costly implementation in monetary terms than in the case of the Phantom Omni. With regard to Product Semantics, it should be noted that there are some outstanding authors who have made important contributions in this field, such as Krippendorff [10,20,56], Gibson [57,58] or Karjalainen [51,59]. However, no contributions have been found on the evaluation of semantic content transmitted via haptics technology. However, as explained in previous research, an attempt is made to integrate haptic sense with visual sense but they do not provide an effective methodology for the selection of textures in the creation of new products. On the contrary, the HPP semantic Appl. Sci. 2019, 9, 5081 16 of 20 evaluation method has managed to integrate both perceptions and, therefore, it is possible to verify the transmission and correct reception of the information in a multimodal way.

5. Conclusions In the experiment, a new prototyping tool was evaluated, for the evaluation of products, based on AR technology. The haptic-visual experience of the participants during the interaction with a real product and an HHP was studied. Analyzing the data, the results show that during the use of HHPs users tend to perceive the same semantic information as during the experience of use with a real product. Therefore, it is concluded that the HHP method is capable of distinguishing between the meaning transmitted by the textures and reliefs of a product, and consequently, it is possible to transmit concrete information to users. It has also been found that it is possible to distinguish not only the information communicated but also the clarity with which this information reaches the user. The HHP can be used in this way by design teams to detect and transmit product-related values, being a reliable method for initially evaluating the emotions evoked by products, together with their finish, in users through haptic-visual means. On the other hand, it has been detected that in order to achieve results closer to a real situation of use, it is considered necessary to focus the evaluation of products on certain surface finishes, provided that all of them are relevant for the study, and at the same time, if a clear differentiation is incorporated between texturized surfaces, the analysis of the experience would improve. Similarly, the increased graphical integration of the physical sample finish with the prototype in AR can provide an improved haptic experience in evaluating products with the HHP tool. In addition, the reliability of the method can be increased by generating samples with a clear delimitation of the textured zone, as this favours concentration on the elements of interest in the evaluation of finishes and shapes. In this way, the user experience with HHP could be improved. Finally, it was concluded that the application of the HHP method in early stages of the conceptualization of a product can lead to the reduction of design times and the lowering of the prototyping phase, in addition to leading to more reliable results in user-product communication and, therefore, to have some certainty in the success of the product and economic return.

Author Contributions: Conceptualization, M.-Á.P.-V.; methodology, M.-Á.P.-V., L.R.-P. and P.F.M.-A.; software, M.-Á.P.-V.; validation, M.-Á.P.-V., L.R.-P., P.F.M.-A. and F.A.-G.; formal analysis, M.-Á.P.-V., L.R.-P., P.F.M.-A. and F.A.-G.; investigation, M.-Á.P.-V. and L.R.-P.; resources, P.F.M.-A.; data curation, M.-Á.P.-V., L.R.-P. and P.F.M.-A.; writing—original draft preparation, M.-Á.P.-V.; writing—review and editing, L.R.-P. and P.F.M.-A.; supervision, P.F.M.-A. and F.A.-G. All authors read and approved the final manuscript. Funding: The APC was funded by the University of Cádiz (Programme for the promotion and encouragement of research and transfer). Acknowledgments: The authors thank the collaboration of Guillermo Naya García for his contribution in the realization of the experiment, as well as all the participants in it. Conflicts of Interest: The authors declare no conflict of interest. Appl. Sci. 2019, 9, 5081 17 of 20

Appl. Sci. 2019, 9, x FOR PEER REVIEW 17 of 20 Appl.Appl. Sci.Sci. 20192019,, 99,, xx FORFOR PEERPEER REVIEWREVIEW 1717 ofof 2020 Appendix A AppendixAppendix AA

Table A1. HHP image for A-AR, B-AR and D-AR samples. TableTable A1.A1. HHPHHP imageimage forfor A-AR,A-AR, B-ARB-AR andand D-ARD-AR samples.samples.

SampleSampleSample AR AR Prototype PrototypePrototype

A-AR A-ARA-AR

B-AR B-ARB-AR

D-AR D-ARD-AR

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