Mexhid Ferati
email: mexhid.ferati@hioa.no

Bahtijar Vogel
email: bahtijar.vogel@mah.se

Arianit Kurti
email: arianit.kurti@lnu.se

Bujar Raufi
email: b.raufi@seeu.edu.mk

David Salvador Astals

Web Accessibility for Visually Impaired People: Requirements and Design Issues

Access to web content continues to be a challenge for the visually impaired, as the needs of such community are very diverse. The access is further hindered by the fact that designers continue to build websites noncompliant with Web Content Accessibility Guidelines (WCAG). To better understand the needs of the visually impaired community, three workshops were organized with various stakeholders coming from three different countries. The results from the workshops suggest that one-solution-fits-all model is inadequate without considering the levels of visual impairment when providing customized web experience. A set of requirements devised from the workshops guided the process of building a middleware prototype. Using eight adaptation techniques, the prototype provides the required user experience based on users level of visual impairment. Preliminary evaluation of the middleware suggests that several adaptation techniques perform better with non-WCAG compliant websites compared to those being compliant.

Introduction

The increased portability and wide adoption of diverse web content and mobile technologies have resulted in the fact that computers are not anymore perceived as distinct technological objects, but more as integrated tools to support our everyday activities [START_REF] Sheth | Computing for Human Experience: Semantics-Empowered Sensors, Services, and Social Computing on the Ubiquitous Web[END_REF]. The ubiquity of these environments creates the possibilities for people to communicate across multiple computational devices at the same time. These trends provided the opportunities for the evolvement of the web toward a fully-fledged software platform [START_REF] Smith | How Digital Outcasts Can Pilot the Future of Health Care[END_REF]. The main idea behind this view is the fact that people are actively engaged by contributing with digital content on the web through the use of different web and mobile applications and platforms across diverse devices [START_REF] Berners-Lee | Long live the Web: a call for continued open standards and neutrality[END_REF].

All these developments result in new ways for people to create, share, manage everyday life, as well as communicate with their friends and family. The different levels of accessibility of these solutions directly affect their use by diverse user groups. Primarily this creates challenges for user groups with special needs. One such user group is the community of visually impaired people, which is usually marginalized. Some of their challenges include lack of proper access to the different web content that could facilitate their everyday activities.

Considering that this community is highly diverse, such as, in terms of levels of impairment, poses an additional challenge when addressing their needs. One way to better understand their needs was to consider different societies and levels of impairment when identifying the requirements. Moreover, considering various user interaction modalities and adaptation techniques, we believe helps in mitigating the problems when visually impaired users access web content.

Motivated by these challenges and research trends, in this paper we report our efforts on the web accessibility issues for the visually impaired community. The main effort is to understand the key requirements and provide initial solutions that could be utilized for providing access to web content for this marginalized group. To this end, we provide exploratory insights on the accessibility requirements identified through three workshops held in Macedonia and Sweden [START_REF] Ferati | Accessibility Requirements for Blind and Visually Impaired in a Regional Context: An Exploratory Study[END_REF]. This was followed with the design activities and development of a middleware using contemporary web technologies in order to adapt a given website based on user needs. A preliminary user evaluation of the middleware prototype was conducted in Spain, which is reported in details in section 6.

In the following sections of this paper we present our research approach followed with an overview of the accessibility requirements identified via realized workshops. Afterwards, we give details of initial design issues discovered and addressed in a prototype. At the end, we discuss initial findings from the prototype user evaluation and provide some challenges for future efforts.

Background

The idea of web accessibility is to make the web open to disabled people [START_REF]Web Accessibility: A Foundation for Research[END_REF]. Contemporary web technologies also play a crucial role in this area [START_REF] Johari | Measuring web accessibility for persons with disabilities[END_REF][START_REF] Zhou | Design and Research for Mobile Web Learning Platform Accessibility[END_REF]. However, web access suffers from interoperability and usability problems that make interaction of disabled users difficult [START_REF]Web Accessibility: A Foundation for Research[END_REF][START_REF] Zhou | Design and Research for Mobile Web Learning Platform Accessibility[END_REF]. Moreover, the need to improve the web browsing experience by adapting and personalizing the software to user preferences and device characteristics has become evident [START_REF]Web Accessibility: A Foundation for Research[END_REF].

To ensure universal design and equal access to web content by all users, the World Wide Web Consortium (W3C) developed the Web Content Accessibility Guidelines (WCAG). These guidelines in many cases help mitigate problems that visually impaired users face when accessing web content. The current version of WCAG 2.0 was published on December 2008 as a W3C Recommendation and includes 12 guidelines organized in four principles [START_REF]Web Accessibility: A Foundation for Research[END_REF]. However, WCAG 2.0 seems to not completely address the accessibility issues, where the low level guidelines (e.g., level A) are not fulfilling the needs of visually impaired users [START_REF] Power | Guidelines are Only Half of the Story: Accessibility Problems Encountered by Blind Users on the Web[END_REF]. This research shows that the application of WCAG is often insufficient for visually impaired users, because of the overlooked factors, particularly in terms of efficiency and satisfaction.

An interesting issue is that the implementation of WCAG 2.0 is still poor in most of governmental and news agencies websites [START_REF] Hanson | Progress on website accessibility?[END_REF]. Therefore the most used assistive technologies today are the screen readers which most of them are proprietary software in nature [START_REF] Brown | The uptake of web 2.0 technologies, and its impact on visually disabled users[END_REF]. In this manner, most of the screen readers fail to notify in an efficient way that new content has appeared on the web site. This does not allow visually impaired users to fully experience and benefit from dynamic websites. A change in the overview of website design and a stronger inclusion of accessibility is needed given that visually impaired users still cannot fully benefit from the advantages of contemporary web technologies. Thus, there is a need for a new approach on "assisting" the assistive technologies that are open and that allow customizations in terms of personalized accessibility features.

With respect to these developments and as suggested by [START_REF] Kelly | From Web Accessibility to Web Adaptability[END_REF] there is a need for adaptation in enhancing web accessibility for visually impaired users. The advances of web technologies (such as HTML5 and web frameworks) offer a wide variety of adaptation possibilities that can be utilized to increase web accessibility. New web technologies offer a wide range of approaches and techniques for adaptation that were not possible when the WCAG 2.0 was developed. These developments bring new possibilities for increased accessibility of the web content. In this context, web adaptability encourages the development of web-based services that can be resilient to the diversity of uses of such services as well as target audiences [START_REF] Kelly | From Web Accessibility to Web Adaptability[END_REF][START_REF] Knutov | AH 12 years later: a comprehensive survey of adaptive hypermedia methods and techniques[END_REF]. These recent advances in the web technologies increase the possibilities for the adaptive approaches to better follow user preferences and get the most of the visual and navigation aspects by facilitating the interaction with the web content. Nevertheless, the web content adaptation becomes challenging especially when it needs to be applied to the specificities of the visually impaired users. In this manner we have identified two primary lines of adaptation when it comes to visually impaired users: content and modality adaptation approaches:

 Content adaptation approach involves displaying and transforming the web content in a more accessible way suitable to user preferences in a specific context [START_REF] Brusilovsky | Adaptive Hypermedia. User Modeling and User-Adapted Interaction[END_REF][START_REF] Knutov | AH 12 years later: a comprehensive survey of adaptive hypermedia methods and techniques[END_REF][START_REF] Watanabe | Adapting Web content for low-literacy readers by using lexical elaboration and named entities labeling New Review of Hypermedia and Multimedia[END_REF].  Modality adaptation approach involves alternative content representation (often non-visual) that facilitate the content accessibility using voice narrators and other non-speech sounds [START_REF] Brusilovsky | Adaptive Hypermedia. User Modeling and User-Adapted Interaction[END_REF][START_REF] Ferati | Audemes at work: Investigating features of non-speech sounds to maximize content recognition[END_REF][START_REF] Knutov | AH 12 years later: a comprehensive survey of adaptive hypermedia methods and techniques[END_REF]. These adaptation approaches can be instantiated with a number of techniques especially by utilizing advances in the web technologies in order to increase accessibility of web content.

Research Approach

The rich technological landscape, in which we live in, enables us to use different devices to deploy, invoke, and represent web content that are related to our everyday context. These developments bring a palette of new opportunities to support an increased accessibility of the web content for the visually impaired users [START_REF] Terven | New Opportunities for Computer Vision-Based Assistive Technology Systems for the Visually Impaired[END_REF]. But in order to utilize and gain full benefit from these advances, a proper domain analysis of the visually impaired users' requirements is essential [START_REF] Ludi | Requirements gathering for assistive technology that includes low vision and sighted users[END_REF]. This type of analysis is defined as a process that acquires, classifies and analyzes all requirements of domain stakeholders [START_REF] Qiu | Research on Domain Requirement Analysis Method Used Ontology[END_REF].

Having in mind that visually impaired community is rather a diverse group, we have utilized a need-driven approach based on active user participation in order to identify the needs in this domain. Another motivation for choosing a need-driven and user-oriented approach was the need to reduce the risk of over engineering as well as avoiding defective requirements [START_REF] Braude | Software Engineering: Modern Approaches, 2nd Edition[END_REF]. Motivated from this and trying to get the best grasp of the domain analysis, we organized three workshops with different stakeholders from various ethnic, cultural, professional and socio-demographic backgrounds. Workshops have been organized in Macedonia (one) and Sweden (two).

The aim of the first workshop held in Macedonia was to enable an in depth understanding of the needs and requirements of the visually impaired community. Whereas, the aim of the second and third workshop held in Sweden was to validate the identified requirements in the first workshop and bring the diverse research expertise on the domain. These three workshops have been followed with a discussion activity with Optic and Optometry specialists in Spain. The purpose of this activity was to understand how different optical deficiencies could be compensated by utilizing the advances of the web technologies. The overall flow of the research activities conducted in this study is depicted in Fig. 1.

Workshop Settings and Stakeholders

The first workshop was held at South East European University in Tetovo, Macedonia and gathered various participants starting from research community, visually impaired people, and non-governmental organizations (NGO's) working especially with visually impaired people. The workshop hosted a total of 21 participants (12researchers and students from the web and mobile technologies and Human-Computer Interaction (HCI) fields; 4-representatives of educational establishments; 2-NGO representatives; and 3-visually impaired students).

The second workshop was held in Kalmar at Linnaeus University, Sweden. The added value of this workshop was the inclusion of additional stakeholders from the fields such as eHealth and Optometry. In total it gathered 11 participants (3-eHealth; 1-optometrist researcher; 1-visually impaired; and 6-researchers from various fields of web and mobile technologies and HCI). The third workshop took place at Blekinge Institute of Technology in Karlskrona, Sweden. This workshop included additional stakeholders coming from the fields of Applied Health Technologies, Interaction Design and Caring Sciences. In total it gathered eight participants (3-health technologies; 1-Informatics; and 4-from various fields of Computer Science).

These three workshops helped us identify various accessibility challenges and adaptation techniques, which were later implemented in a middleware prototype that utilized a number of adaptation techniques to increase the web content accessibility. Furthermore, in a direct discussion with a specialist from Terrassa School of Optics and Optometry of the Universitat Politècnica de Catalunya we have further specified the exact adaptation techniques that would be used to determine key functional requirements of the middleware. A follow up user evaluation of the middleware was then conducted with visually impaired users from the same institution.

In order to gain a better insight of different stakeholders involved in the research activities, an ecosystem scheme of the stakeholders is depicted in Fig. 2. The ecosystem view became a confluence between educators, researchers, community support agents and most importantly, the end users, i.e., the visually impaired. This research approach enabled us to build up knowledge about different accessibility challenges, adaptation approaches and techniques when dealing with visually impaired user needs.

Web Accessibility Challenges

The discussion with stakeholders during the three workshops provided a good empirical base to understand the main challenges that keeps the visually impaired as a marginalized community (especially in Macedonia and the surrounding region). List of all challenges identified in the workshops are detailed in [START_REF] Ferati | Accessibility Requirements for Blind and Visually Impaired in a Regional Context: An Exploratory Study[END_REF], while in this paper we mainly emphasize on the web content accessibility challenges for visually impaired people. [START_REF] Ferati | Accessibility Requirements for Blind and Visually Impaired in a Regional Context: An Exploratory Study[END_REF].

Fig. 2. Ecosystem view of the stakeholders

The analysis of the data gathered during the workshops, helped us identify two important aspects that inform the process of interface requirements for the visually impaired community. The first factor is related to contextual factors and pertains to the fact that web applications have increased in importance due to the relevance of the user context (i.e., profile, activities, and location). Table 2 highlights different contextual factors motivated particularly for (a) the importance due to the user context that plays nowadays, (b) the end-user satisfaction, (c) and the significant impact on the quality of the overall user experience, particularly visually impaired people. For instance, a particular website could be accessible on Windows, but not on OS X or diverse mobile platforms, because of a lack of sophisticated screen reader. Or following the WCAG guidelines does not guarantee that all visually impaired people will gain the satisfactory level access to digital information. A website could pass all WCAG validations, but still be unusable due to a lack of screen readers available for a particular language.

To overcome situations when contextual factors play negative role in achieving satisfactory user experience, in our previous studies we have used non-speech sounds to deliver content to visually impaired users. In the process of auralizing content and deliver it in a non-visual form, we have successfully developed and evaluated audemes as a novel non-speech sounds to deliver educational content in experiments conducted with K12 students in a visually impaired school in U.S. [START_REF] Ferati | Audemes at work: Investigating features of non-speech sounds to maximize content recognition[END_REF]. Audemes are brief non-speech sounds created of music and sound effect sound snippets referring to natural, artificial or abstract sounds, even popular music.

An interesting insight from one of the workshops revealed the second factor that highlights the necessity to "teach" visually impaired how to make the best use of their remained sight. An optometrist present at the workshop argued that many visually impaired people could pass the legally blind threshold by learning techniques of using peripheral vision [START_REF] Lewis | Resolution of static and dynamic stimuli in the peripheral visual field[END_REF]. Designing interfaces for visually impaired users familiar with such techniques would require understanding their specific needs, rather than treating them as homogenous group. While various web adaptation techniques could be used to deliver usable content to visually impaired users, the one-size-fits-all model, however, does not provide satisfactory solution. Hence, a specific user requirement should be gathered to apply the specific adaptation technique suitable for the user. Based on user's level of impairment, a particular solution should be suggested. To achieve such goal, as a result of the workshops we have identified specific challenges different users face when accessing web content. Fig. 3 lists these challenges along with the actions and approaches anticipated to address them.

All these challenges identified from the workshops had as a common denominator, the need to access diverse web content in a more accessible way, and beyond the WCAG guidelines. This inspired the idea of a middleware that would enable applying adaptation techniques of existing web content primarily possible due to the advances in the web technologies.

In order to identify the best adaptation techniques to be implemented into the middleware, we have discussed our ideas with an optician specialist. The result of this discussion indicated that some visually impaired users feel more comfortable with a different contrast rather than the usual black over white. This inspired the idea of color transformation as part of our middleware solution. Furthermore, it is desirable to offer the flexibility of increased text and other content on the web site, but this should not be on the expenses of losing the navigational context of the page. For that reason this inspired us to implement an amplifying text lens that enables the visually impaired user to read the text with an increased size, but without losing the context of the entire web page. All this served as a solid background to initiate our prototyping efforts for the design and implementation of the middleware solution.

Design Issues and Implementation Details

The design activities and implementation of the prototype solution was highly motivated by contemporary web technologies. Both, the design and the requirements 3) of our prototype design, were motivated from: the adaptation approaches identified in section two, three workshops, and individual meetings with an Optics and Optometry specialist. Considering these requirements, we have developed a prototype solution that adapts a given website based on user's preferences and their disability.

In order to provide a fully accessible web content, our solution transforms any available web site by making it WCAG 2.0 compliant. Moreover, one of our goals with our solution was to reach the following:

1. To offer different types of visual for various levels of impairment. 2. To provide the best personalized user experience for the existing web content (such as governmental portals, news agencies and other). Table 3 lists the requirements identified, which essentially address challenges listed in Fig. 3. In addition, this table lists the technique and rationale for each requirement. Given these requirements and the related technique needed to be implemented into our prototype, the architectural choice was motivated following the software architectural pattern, the Model-View-Controller (MVC) that lately is being highly used in modern web technologies. This architectural pattern is composed of three parts: the Model -corresponds to the data, the View -is the representation of the data, and the Controller -manages the data.

The reason of utilizing this pattern is that it allows decoupling the visual representation of the data and its management. As such, it provides solutions to flexibly address the requirements identified in Table 3, and in the future extend our solution with new features in a more flexible manner. The solution prototype is implemented by utilizing contemporary web technologies in terms of HTML5, CSS, JavaScript and PHP as well as external libraries including: HTML DOM, Modernizr, jQuery, Web Speech API, Lens effect, TextScrolling, and contextJS (source code: https://github.com/davidsalvador/degree-project). All adaptation techniques identified in Table 3 are carefully implemented into our solution. Fig. 4, presents the architectural overview of our prototype solution. The "Controller" and the "View" play a central role in our solution. The "Controller" usually manipulates the "Model" elements and updates the "View". The "Model" of the solution is formed by all HTML elements. The "Content extractor" component in the "Controller" uses a third-party library (HTML DOM), which belongs to the "Model" part. The HTML DOM parser makes it possible to manipulate the HTML elements of a certain web page and its content. The "Data controller" component manages the data extracted from "Content extractor" and afterwards applies different adaptations (see details in Fig. 4). The "View" is responsible for representations. It gets the adaptations and presents them to the user. Usually the "Controller" applies the static changes, whereas the "View" allows the user to change the options and automatically reload the page to display the new content by using the "contextMenuLoader" component. In general, the "View" allows to dynamically change and adapt the web content to different styles and features without reloading the page.

To better understand our solution prototype, a usage scenario is presented in Fig. 5. The typical steps depicted in the use case diagram are:

1. The user enters the URL of the page to browse into the prototype along with the types of adaptations selected (preferences). 2. The solution requests the original website (gets web content and data) and applies the adaptations requested. 3. Finally the adapted page is presented based on the chosen user preferences. In order to conserve the adaptations chosen by the user, persistent adaptation is applied, enabling that in every subsequent browsing instance, the requested page will be adapted based on the same chosen preferences as the last browsing experience. Before the user searches the web, session cookie is initiated where the features chosen by the user will be stored. The "href" attribute of every anchor HTML element is modified by appending "adapt?web" string to the URL. Using this, all links will refer the "adapt" page where the adapted web content is received as a GET parameter. In this way, every petition that the "adapt" page receives, the session features (variables) are read from the cookie and the adaptations are made available based on the preferences chosen by the user (see Fig. 6). In other words, for each URL submission the adapt.php is called. We must clarify that at this stage, the two-way communication of form handling (e.g., searching) has not been implemented.

In order to rationalize the design and implementation, Fig. 7 presents the screen shot of the protoype solution. The simple and user-friendly interface shows a textbox for typing the requested site and two buttons. The button "Take me there!" takes the user to the desired website with default adaptations. The button "Change options" offers the user the ability to alter the default settings in a wizard-like fashion by guiding them through each adaptation. If users right-click anywhere on the page, a context menu is shown giving them the option to directly apply a desired adaptation, e.g., change the text size.

To better illustrate the effects of adaptation of a given website, in Fig. 8 and9 we show the original and adapted version of the University of Barcelona website with default adaptation settings. The prototype solution removes irrelevant images, such as logos, and leaves only images that refer to content. Fig. 9 shows that the menu links are transformed into a form that more clearly indicates them being clickable links.

When users hover with a mouse over a given paragraph, such as the one highlighted in yellow in Fig. 9, the content will show and slide left-to-right with a bigger font on a small window below the paragraph. As the content slides, it is also read at loud using a text-to-speech voice narration. The middleware prototype can be accessed at: http://salvadorastals.com/middleware/ The user evaluation of the middleware was conducted involving four visually impaired users from the Terrassa School of Optics and Optometry of Universitat Politecnica de Catalunya. The evaluation process consisted of three phases. Initially, the participants were given time to familiarize with the middleware and discover its features. Afterwards, participants were asked to find a particular information from a given website. To accomplish this task, each participant chose the middleware settings of their choice. Finally, after participants completed the tasks, they were interviewed to record their feedback about their experience with the middleware.

Participants

Individual characteristics of each participant is given in Table 4 below. Participants were between 28 and 70 with various types of disability, years of low vision and internet usage per day. One common factor among all participants was that they used the Window Eyes screen reader.

Procedure

Each participant was sent an email with test instructions and two links. The first link corresponded to the middleware interface, while the second link contained the evaluation survey. Two participants tested the website of the Universitat Autonoma de Barcelona (http://uab.cat), which was WCAG 2.0 non-compliant at the time of testing. Two other participants tested the ONCE website (the Spanish National Blind Association, http://once.es), which was WCAG 2.0 level AA compliant at the time of testing. The WCAG compliance was checked using the achecker online tool (http://achecker.ca).

The following steps were involved:  Step 1: The participant familiarizes with using the middleware interface, and playing with the features to find the best fit for their needs. (At this point, participants are not yet exposed to the two testing websites.)  Step 2: The participant is randomly assigned to either the WCAG compliant or non-compliant website in which he is instructed to find a given information.


Step 3: After the participant accomplishes the task, he is instructed to answer the survey, which consisted of three parts: (i) questions gathering information about participant's demographics including their experience with technology and the type and level of visual impairment; (ii) questions highlighting whether the participant was able to find the information required from the given website, indicating Yes, No or Partially Found; and (iii) using a combination of Likert scale and openended questions participants were required to evaluate the usability of the middleware interface.

Results and Discussion

Participants were successful in finding the required information from the randomly assigned website. Only one out of four participants was not able to find the information required, to whom a WCAG 2.0 non-compliant website was assigned. Two adaptation techniques, text transformation and amplifying lens, were rated with maximum score (6.0) by all participants whether using a WCAG 2.0 compliant or non-compliant website. This result proves that these two techniques were well accepted by participants regardless of the level of WCAG compliance the website had.

A technique that the WCAG compliance of the website had the most effect was Image filtering, which was rated very differently depending on whether participants used a non-or compliant website. Participants using non-compliant website rated this technique with maximum score (6.0), while participants using a compliant website rated it with a minimal score (2.0). We believe this result indicates that the website does not need to be WCAG 2.0 compliant for an adaptation technique to be useful. The content filter technique received high rating from three participants, while one participant using a WCAG compliant website gave a poor rating. The image resizing and contrast transformation techniques received below the average rating. Further studies need to be conducted in order to identify reasons that make these techniques less successful. The only technique addressing a non-visual (auditory) requirement was the voice narrator. This technique was rated average by all but one user, who gave it a maximum score using a WCAG compliant website. Summarized quantitative values of the results are given in Table 5.

Few participants gave negative comments concerning aspects of the middleware homepage. One participant requested that the font size of the contextual menu be higher, while another participant stated that it would be easier to use the middleware as a search engine, rather than requiring to input the entire URL into the box.

Conclusion and Future Work

In this paper we presented requirements gathered from three workshops held with different stakeholders to identify the needs of visually impaired users. The novelty of this study was the identification of two important factors relevant when addressing the needs of visually impaired people. The first factor identified was the context of use, which influences the accessibility of digital content for the visually impaired users. The second factor was the need to evaluate user's level of visual impairment before applying any adaptation technique on the existing web content.

The outcome of the realized workshops was the generation of requirements that guided the development of a middleware prototype that made websites usable by adapting them based on user's visual impairment level. The user evaluation of the middleware indicated that several adaptation techniques perform better with non WCAG compliant websites than with those being compliant. Overall, adaptation techniques were useful to our participants.

Although this study used just four participants, it is still important because of two reasons. First, it gives an indication that requirements gathered and the middleware built are an approach in the right direction. The user testing provides some initial insights both regarding the middleware prototype as well as validating the approach in gathering requirements using workshops. Second, it is typical that studies involving people with disabilities are conducted only with several participants. Limitations in terms of mobility and skill qualification of these people are usually the underlying reasons [START_REF] Stevens | Principles for the design of auditory interfaces to present complex information to blind people[END_REF]. To an extent, this study is an effort in addressing this issue by giving greater access to information to visually impaired users.

In line with such efforts, we are currently investigating Massive Open Online Course (MOOC) as a means to provide quality education to visually impaired people [START_REF] Rizzardini | An Open Online Course with Accessibility Features[END_REF]. Future efforts need to gather requirements for building accessible MOOCs and the skills required for the users to have in order to be able to access web content.

Moreover, building and evaluating how different adaptation techniques contribute toward achieving greater web content accessibility will present a step in the direction to increase the number of visually impaired community participating in online education.

In the future, in order to increase content accessibility, new adaptation approaches could be investigated by leveraging open data and standards together with emerging web technologies. In addition, this would enable architectural solutions that are capable to deal with dynamic requirements and heterogonous environments in web and mobile technologies [START_REF] Vogel | Towards an Open Architecture Model for Web and Mobile Software: Characteristics and Validity Properties[END_REF]. These two lines of action represent important future research challenges, as we believe that they are key aspects to influence accessibility needs and emerging technologies in general, and in particular of the visually impaired community.

Fig. 1 .

 1 Fig. 1. Depiction of this study flow.

Fig 3 .

 3 Fig 3. Accessibility challenges, actions and adaptation approaches for BVI users.

Fig. 4 .

 4 Fig. 4. Architectural overview of the solution based on MVC.

Fig. 5 .

 5 Fig. 5. Use case diagram.

Fig. 6 .

 6 Fig. 6. Persistent adaptations.

Fig. 7 .

 7 Fig. 7. Prototype homepage and contextual menu.

Fig. 8 .

 8 Fig. 8. The University of Barcelona website without adaptation.

Fig. 9 .

 9 Fig. 9. The University of Barcelona website with default adaptations applied.

Table 2 .

 2 Contextual factors[START_REF] Ferati | Accessibility Requirements for Blind and Visually Impaired in a Regional Context: An Exploratory Study[END_REF].

	Factors	Description	Testing activities
	Day/time of use	The impact of natural light and time of day in user's activities	Functionality testing
	Location	User activity influenced by his location (indoor, outdoor, in a car, train, etc.)	Mobility testing
	Device/Platform	The impact of device type, size and platform in user's activities	Interoperability and/or compatibility
	User profile	The level of user disability	Optometric testing/ Survey testing
	Accessibility	An overarching factor that ensures achievement of all previous factors	Heuristics/ Usability/field testing

Table 3 .

 3 Requirements and related techniques to address identified challenges.

	Approach Action	Technique	Requirement	Rationale

Table 4 .

 4 Participant demographics.

	PID Age	Hours of Internet	Assistive	Years of	Pathology
			per day	software	low vision
	A	45	4	Window Eyes	12	Magna myopia
	B	65	2	Window Eyes	2	Glaucoma
	C	70	1	Window Eyes	5	Age Related Macular
						Degeneration
						(ARMD)
	D	28	5	Window Eyes	28	Retinitis pigmentosa

Table 5 .

 5 Prototype evaluation results.

	Participants			Middleware feature / Adaptation technique			WCAG 2.0	compliance
		Image filtering	Image resizing	Text transformation	Contrast	Content filter	Voice narrator	Amplifying lens
	A	2	2	6	3	2	2	6	Yes
	B	2	2	6	1	5	6	6	Yes
	C	6	3	6	3	6	3	6	No
	D	6	3	6	2	6	2	6	No
	Mean	4	2.5	6	2.25	4.75	3.25	6	-

Acknowledgments. We thank all participants from Kosova, Macedonia and Sweden that attended our workshops. We thank the eHealth Institute in Kalmar and Blekinge Institute of Technology in Karlskrona, for hosting our workshops. Furthermore, we thank the professor of UPC -FOOT, Eulalia Sánchez, for her scientific, optical and optometry approach and counseling during the assessment study. Finally, we thank the Swedish Foundation for International Cooperation in Research and Higher Education for supporting this research.


Shogo Matsuno

Minoru Ohyama
email: ohyama@mail.dendai.ac.jp

Kiyohiko Abe
email: abe@kanto-gakuin.ac.jp

Shoichi Ohi
email: ohi@mail.dendai.ac.jp

Naoaki Itakura

Differentiating Conscious and Unconscious Eyeblinks for Development of Eyeblink Computer Input System

Keywords: eyeblink, eye gaze input, voluntary eyeblink, eyeblink waveform, input interface

In this paper, we propose and evaluate a new conscious eyeblink differentiation method, comprising an algorithm that takes into account differences in individuals, for use in a prospective eyeblink user interface. The proposed method uses a frame-splitting technique that improves the time resolution by splitting a single interlaced image into two fields-even and odd. Measuring eyeblinks with sufficient accuracy using a conventional NTSC video camera (30 fps) is difficult. However, the proposed method uses eyeblink amplitude as well as eyeblink duration as distinction thresholds. Further, the algorithm automatically differentiates eyeblinks by considering individual differences and selecting a large parameter of significance in each user. The results of evaluation experiments conducted using 30 subjects indicate that the proposed method automatically differentiates conscious eyeblinks with an accuracy rate of 83.6% on average. These results indicate that automatic differentiation of conscious eyeblinks using a conventional video camera incorporated with our proposed method is feasible.

Introduction

In general, eyeblinks can be classified as voluntary, reflex, or spontaneous. A voluntary eyeblink occurs consciously, a reflex eyeblink occurs as a result of external factors such as sound and/or light stimuli, and a spontaneous eyeblink is one that occurs unconsciously [START_REF] Matteo | Voluntary, spontaneous and reflex blinking in patients with clinically probable progressive supranuclear palsy[END_REF]. If a system was able to distinguish when a user has blinked with a conscious desire to enter information, then we would be able to control a computer device. In other words, computer control using eyeblinks could be realized if a method that automatically distinguishes conscious eyeblinks from unconscious eyeblinks was available.

The results of psychology experiments have shown that the occurrence of eyeblinks is associated with cognitive status. Using this knowledge, a system that measures the state of exhaustion of drivers has been developed [START_REF] Majaranta | Twenty years of eye typing: Systems and design issues[END_REF]. Further, studies have been conducted in an effort to determine whether it can be used as a communication support and assistance system for severely crippled persons such as amyotrophic lateral sclerosis (ALS) patients [START_REF] Richard | Adaptive one-switch row-column scanning[END_REF][START_REF] Melanie | Indirect Text entry using one or two keys[END_REF][START_REF] Kiyohiko | An eye-gaze input system using information on eye movement history[END_REF]. Systems using eyeblink as an input switch and otherwise combining it with eye gaze in an input interface to operate equipment have also been proposed [START_REF] Diogo | Filteryedping: Design challenges and user performance of dwell-free eye typing[END_REF][START_REF] Naoaki | Investigation for calculation method of eye-gaze shift from electro-oculograph amplified by AC coupling with using eye-gaze input interface[END_REF][START_REF] Dekun | Improvement of eye gesture interface system[END_REF][START_REF] Tanabe | Eyeblink activity during identification of Katakana characters viewed through a restricted visual field[END_REF][START_REF] Abe | Automatic method for measuring eye blinks using splitinterlaced images[END_REF][START_REF] Abe | Automatic classification of eye blink types using a frame-splitting method[END_REF]. However, in most systems, because eyeblinks occur at high speeds, accurate and dedicated equipment is required to measure them. In addition, these systems usually employ a fixed threshold or special operations.

Our aim is to develop an eyeblink input system that can be installed on conventional information devices, such as smartphones and smart glasses [START_REF] Miluzzo | EyePhone: Activating mobile phones with your eyes[END_REF][START_REF] Mayberry | iShadow: Design of a wearable, real-time mobile gaze tracker[END_REF][START_REF] Shogo | Computer input system using eye glances[END_REF]. Using image analysis [START_REF] Abe | Automatic method for measuring eye blinks using splitinterlaced images[END_REF][START_REF] Abe | Automatic classification of eye blink types using a frame-splitting method[END_REF], we previously obtained and examined shape feature parameters in an eyeblink waveform (i.e., the waveform representing the time evolution of the eyeblink process) and observed differences between conscious and unconscious eyeblinks among subjects [START_REF] Matsuno | Automatic discrimination of voluntary and spontaneous eyeblinks. Use of the blink as a switch interface[END_REF]. In this paper, we propose a new automatic conscious eyeblinks differentiation method, and report on the results of evaluation experiments conducted using the proposed method and algorithm with 30 subjects.

Related Work

Conventional eyeblink input systems are classified into two basic types. The first type uses input based on pre-established time values (for example, when a user closes his/her eyes for more than 200 ms) [START_REF] Grauman | Communication via eye blinks-Detection and duration analysis in real time[END_REF][START_REF] Mackenzie | BlinkWrite: Efficient text entry using eye blinks[END_REF]. In this case, a dynamic threshold value is used for each type of eyeblink because eyeblinks show wide individual differences. A false input may occur if the threshold is fixed because the input time is user-dependent; a user might unconsciously produce considerably short or long eye movements. The second type of input system examines special eye movements, such as double eyeblinks and winks [START_REF] Missimer | Blink and wink detection for mouse pointer control[END_REF][START_REF] Gorodnichy | Second-order change detection, and its application to blink-controlled perceptual interfaces[END_REF]. However, these systems require the user to perform conscious, and occasionally complex, actions; therefore, users have to practice in order to be proficient at using these systems. In addition, the unusual eyeblinks required can cause user stress, especially when the systems are used over a long period [START_REF] Matteo | Voluntary, spontaneous and reflex blinking in patients with clinically probable progressive supranuclear palsy[END_REF], [START_REF] Tanabe | Eyeblink activity during identification of Katakana characters viewed through a restricted visual field[END_REF].

In an effort to overcome these problems, eyeblink input interfaces that incorporate more natural eyeblinks are being studied. However, a user who does not display a noticeable difference in shape feature parameters between voluntary and spontaneous eyeblinks must be conditioned and encouraged by such a system for it to accurately measure voluntary eyeblinks [START_REF] Naoaki | Investigation for calculation method of eye-gaze shift from electro-oculograph amplified by AC coupling with using eye-gaze input interface[END_REF][START_REF] Dekun | Improvement of eye gesture interface system[END_REF][START_REF] Tanabe | Eyeblink activity during identification of Katakana characters viewed through a restricted visual field[END_REF][START_REF] Abe | Automatic method for measuring eye blinks using splitinterlaced images[END_REF]. Conversely, the system proposed in this paper uses a messaging system-for example, it announces to a user, "you blinked correctly at the perceived signal"-to decrease user stress and to amplify the difference in the shape feature parameters. This system most closely approximates an actual eyeblink interface because it is expected that the user is conscious of the input when blinking, even if no user training has been conducted.

3

Characteristics of Eyeblinks Waveforms

We distinguish between conscious and unconscious eyeblinks by considering the fact that the duration of a conscious eyeblink is longer than that of an unconscious eyeblink [START_REF] Abe | Automatic classification of eye blink types using a frame-splitting method[END_REF], [START_REF] Grauman | Communication via eye blinks-Detection and duration analysis in real time[END_REF]. However, an eyeblink is a rapid motion that completes a series of operations on the order of a few hundred milliseconds; over and above that, individual differences are substantial. Consequently, because the time resolution of conventional video cameras is low, when measured with these cameras, significant differences in the eyeblink duration are not observed. Eyeblinks vary widely by individual, but in most cases, during a consious eyeblink, the eyelids close completely. In addition, variation in terms of the eyeblink waveform is relatively small in each individual. Therefore, we focused on the following parameters: closing-phase amplitude, opening-phase amplitude, and eyeblink duration, as discussed in a previous study [START_REF] Tanabe | Eyeblink activity during identification of Katakana characters viewed through a restricted visual field[END_REF]. Figure 1 shows a model of an eyeblink waveform in which the closing-phase amplitude Acl is defined as the height of the closing-phase starting point Ps to the minimum point Pmin. Pmin is defined as the point where the eye-opening area is smallest; that is, from the closingphase end point Psb to the opening-phase starting point Peb. Similarly, the openingphase amplitude Aop is defined as the height of the minimum point Pmin to the openingphase end point Pe. Finally, the eyeblink duration Dur is defined as the field count from Ps to Pe.

Automatic Measurement of an Eyeblink Waveform

If the time evolution of the eyeblink process could be accurately measured, it would be possible to express an eyeblink as a waveform. Individual eyeblinks must be measured and then analyzed for automatic differentiation of eyeblink types. The typical techniques used to sample eyeblink waveforms are electrooculogram (EOG) and image analysis.

The EOG method involves placing an electrode on the skin near the eyeball. Eyeblink waveforms are then collected by recording changes in the cornea-retina potential. This technique was proposed for automatic detection of conscious eyeblinks until recently [START_REF] Tetuya | Development of an input operation of the communication tool using voluntary eye blink[END_REF]. However, the EOG method requires a unique apparatus to process ocular potential, and the user must have an electrode attached to his/her skin. Therefore, the EOG method is unsuitable for a simple interface. Moreover, extraneous noise from a living body can cause interference. By contrast, image analysis examines pictures of eyeblinks captured by a video recorder. It has become popular because it requires no bodily contact and is manageable and adaptable. However, eye movements are difficult to capture with a video camera that has a standard aspect ratio (NTSC) because an eyeblink is a highspeed operation. Therefore, in this paper, we incorporate an algorithm used in previous research [START_REF] Abe | Automatic method for measuring eye blinks using splitinterlaced images[END_REF] that detects changes in eye aperture. The algorithm samples at 1/60 s using interlaced NTSC video images further divided into field images. Figure 2 shows the processing flow for detecting changes in the eye-aperture area.

Fig. 2. Overview of frame-splitting method and binarization.

When image analysis is used, the first step is to analyze video images of the area surrounding the eye in order to assess changes in eye aperture using binarization based on flesh color. Figure 3 shows an example of changes that occur in the eye-aperture area. The data shown in Fig. 3 include changes in the eyeblink waveform. The next step applies smoothing differentiation between the split field area and the next split field. Coordinates that reveal the maximum area difference value and the minimum area difference value are then determined using a second differentiation.

Interlaced image (near-eye area)

Split image (Fields 1 + 2) Binarized (eye-aperture area) Fig. 3. Changes in eye-opening area.

However, this step in the analysis involves excessive noise resulting from small movements in the vicinity of the eye, such as from an eyelid. Therefore, we remove three coordinate classes of extreme value (maximum, minimum, and few-moving) using the k-means method. We determine the start and end of an eyeblink waveform using its maximum and minimum values because one eyeblink waveform contains only one maximum and one minimum value. Minimum values exist in the opening phase and maximum values exist in the closing phase. Data are obtained from one eyeblink waveform according to these factors. If the obtained maximum and minimum values are observed in succession as two points, the point closer to the field of temporal axes is used. An eyeblink start field is calculated by differentiating between field areas in the direction opposite to that of the temporal axes from the maximum value's field. In this field, the threshold Th1 becomes positive for the first time. By contrast, the eyeblink end field is calculated by the difference between the field areas in the forward direction of the temporal axes from the minimum value's field. In this field, the threshold Th1 becomes negative for the first time. The threshold Th1 is then determined by the following equation:

ℎ = -+
where n is the attention field and f(n) is the eye-opening area in the n field. Figure 4 shows an example of the detected eyeblink waveform. An eyeblink waveform measured by means of image analysis can be applied to the model in Fig. 4. The eyeblink duration is represented as field numbers from the eyeblink starting point to the eyeblink end point. The eyeblink amplitude is represented as changes in the eye-aperture area. The point Pmin, at which an area is minimized, is determined based on the model (Fig. 1) in theory. However, it might not be determined by an actual measurement (Figure 5). Therefore, Pmin is defined as the average of the eye-aperture field areas that are less than threshold Th2 in one eyeblink waveform. Threshold Th2 is determined from the following equation:

ℎ = -+
where Amax and Amin are the maximum and minimum, respectively, of the eye-opening area of the eyeblink waveform. In addition, the closing-phase amplitude is calculated based on the difference between the area of the eyeblink starting field and point Pmin.

Similarly, the opening-phase amplitude is calculated based on the difference between the area of the eyeblink end field and point Pmin.

Automatically Differentiating Conscious and Unconscious Eyeblinks

In this section, we examine the differentiation of eyeblinks on the basis of the parameters of the extracted eyeblink waveform using the method outlined in Section 4. It has been reported that the duration of a conscious eyeblink is longer than that of an unconscious eyeblink [START_REF] Matsuno | Analysis of trends in the occurrence of eyeblinks for an eyeblink input interface[END_REF]. However, in many cases, distinguishing between the two types of eyeblinks using this information is difficult because the difference in the duration of eyeblinks cannot be measured if the time resolution of the moving image is low. Therefore, the proposed method improves the distinction accuracy by combining the duration and amplitude. There are many cases in which differences between eyeblinks are not found because amplitude values are more sensitive to individual differences than duration values. However, we have already confirmed the following in preliminary experiments. Specifically, approximately one-half of all subjects in our experiment had a significant difference in both the duration and amplitude, and the other half had significant differences in either one of duration or amplitude. We also administered a t-test to the subjects using a 1% standard deviation between conscious and unconscious parameters. And Table 2 shows the details of the results obtained. A significant difference of 24% (12 subjects) is evident in eyeblink duration. For eyeblink amplitude, the difference is 22% (11 subjects). For both parameters, the significant difference is 46% (23 subjects). Finally, no significant difference is apparent in 8% of the subjects (4 subjects). In other words, a significant difference in shape feature parameters between voluntary and spontaneous eyeblinks is seen in a minimum of 92% of the subjects. Moreover, the results of examination of individual parameters reveal the following. The total percentage of subjects who show a significant difference in eyeblink duration is 70%. The total percentage of subjects who display significant differences in eyeblink amplitude is 68%. Finally, the total percentage of subjects who show significant differences in both parameters is 46%.

Figure 6 shows a histogram that summarizes the distribution of the average value of the eyeblink duration of the 50 subjects by eyeblink type. Conversely, the histogram in Fig. 7 summarizes the distribution of the average value of the eyeblink amplitudes of the 50 subjects by eyeblink type. Fig. 6. Duration difference in each group [START_REF] Matsuno | Analysis of trends in the occurrence of eyeblinks for an eyeblink input interface[END_REF]. Fig. 7. Amplitude difference in each group [START_REF] Matsuno | Analysis of trends in the occurrence of eyeblinks for an eyeblink input interface[END_REF].

We perform automatic differentiation using a threshold to distinguish the larger differences among the measured feature parameters between conscious and unconscious eyeblinks in every subject. In the proposed method, a normalization process is first applied to each feature parameter based on the average value of conscious eyeblinks to decide the differentiation threshold of each subject. As shown in Table 1, the trends in the parameters of subjects can be classified into three groups: Groups A, B, and C. Group A comprises subjects who exhibit significant differences in eyeblink duration only. Group B comprises subjects who exhibit significant differences in eyeblink amplitude only. Group C comprises subjects who exhibit significant differences in both parameters. The method then selects the parameter difference of the larger side among the duration and amplitude after normalization. For instance, in a scenario where there is a particular difference in duration, the threshold, Th3, used to distinguish conscious eyeblinks, is determined from the following equation:

ℎ = -+
where Tdv is the average duration of conscious eyeblinks and Tds is the average duration of unconscious eyeblinks. In this instance, an eyeblink is distinguished as a conscious eyeblink if the duration exceeds Th3. Further, an eyeblink is distinguished as unconscious if it falls below Th3.

On the other hand, in the case where there is a particular difference in amplitude, the threshold, Th4, used to distinguish conscious eyeblinks is determined from the following equation:

ℎ = -+
where Adv is the average amplitude of conscious eyeblinks and Ads is the average amplitude of unconscious eyeblinks. In this case, an eyeblink is distinguished as a conscious eyeblink if the duration exceeds Th4. Conversely, it is distinguished as unconscious if it falls below Th4. The proposed method determines thresholds Th3 and Th4 via the above method during calibration, before actual measurements are conducted. Subsequently, it automatically distinguishes eyeblinks as conscious or unconscious based on the feature parameter.

Evaluation Experiments

In this section, we discuss the results obtained on employing the eyeblink waveform measurement and distinction algorithm outlined above and measuring the eyeblink waveform of 30 subjects (22 men and 8 women with ages in the range of 20-29 years; all without disabilities) to analyze the periodicity of the shape feature parameters of eyeblinks.

System Outline

The hardware comprising our experimental system included a Sony HDR-HC9 digital camcorder for obtaining eye images, and a personal computer for image and eyeblink waveform analysis. Although the camera could capture high-definition (HD) pictures, standard-definition (SD) pictures were used in the experiments. The system is intended to be mounted on wearable and smart devices. Furthermore, an experimental system was developed as a prototype. Ordinary indoor lighting (incandescent lighting) was used when capturing moving images. A pair of light-emitting diodes (LEDs) was placed symmetrically on both sides of the camera and at a distance of approximately 60 cm directly in front of the face of the subject. The back of the subject's head was lightly supported with a stabilizing device to prevent it from shaking. The video camera was placed in front of and below the subject's head at a distance of approximately 20 cm. The camera was then used to magnify and obtain pictures of the area surrounding the subject's left eye. Because the image format was set for SD video, the resolution was 720 × 480 pixels with a 16:9 aspect ratio and refresh rate of 30 fps (NTSC). These experiments were performed on the naked eye; therefore, eyeglasses were not allowed during filming.

Experimental Method

The subjects were given the following instructions during filming:

 Pay attention to the silver dot mark located on the upper part of the camcorder.

(The mark was placed at this location by us.)  When you hear the signal, "blink well" always.



You do not have to resist any unconscious urge to blink.

The "blink well" instruction was meant to increase the difference in the shape of the feature parameters between conscious and unconscious eyeblinks. In other words, the signal was a means of encouraging subjects to be strongly conscious of their voluntary blinks. The signal was sounded randomly at intervals of 4 to 10 s using a digital timer.

Images were captured for an overall total of 90 s during the course of the experiment. The first 20 s was used for calibration. This experiment does not use a control group because it was a conscious property the eyeblink immediately after sounding. After measuring the eyeblink video image, we measured and analyzed the individual eyeblink waveform using moving images. The calibration determined the distinction threshold by using 20 s at the beginning of the moving image based on the method described in Section 4 to decide the feature parameter to use as the distinction threshold by normalization and comparison in each subject. Differentiation of conscious and the unconscious eyeblinks was then performed in the subsequent 70 s of moving images, using the obtained Th3 and Th4 thresholds. At this point, the system distinguished only eyeblink waveforms that had been successfully detected automatically.

At the conclusion of the experiment, the subjects were asked to complete questionnaires and/or comment about their experiences during the experiment. The items in question were age, gender, sleep time during the previous night, health condition (five levels: one (bad) through five (good)), task difficulty (five levels: one (easy) through five (difficult)), confidence in achieving the task (five levels: one (low) through five (high)), and personal interpretation of "blink well."

6.3

Real-time Measurement Experiment

Table 3 provides data on the subjects that show a significant difference in the measurements between conscious and unconscious blinks. Representative results of the experiment in relation to measured conscious and unconscious blinks, including the average values of the durations of blinks, the closing-phase amplitude, and the openingphase amplitude, are shown. The right side of the table shows the results after normalization and the selected feature parameter.

Using the amplitude ratio of the closing phase to the opening phase for parameters is complicated because the ratio of the closing-phase to the opening-phase amplitude was, in all cases, found to contain a minimum of one large parameter. Therefore, we redefined the average value of two amplitudes as the eyeblink amplitude. In Table 3, the tendency for variation in individual differences between conscious and unconscious eyeblinks is as follows.

Let us now analyze those subjects who either did not show significant differences or exhibited only some differences in shape feature parameters. The number of unconscious eyeblinks was found to be limited. Two reasons explain this. The first is the fact that few eyeblinks actually occurred, which may be because the subjects were under stress during the experiment. The second is that eyeblinks registered movements that were too small to be accurately detected. Therefore, this study might promote future research in eyeblink detection accuracy.

= - × = - × = + -+ + ×
These equations for accuracy rate are adopted from [START_REF] Abe | Automatic classification of eye blink types using a frame-splitting method[END_REF].

Using our proposed method, the average rate of successful differentiating of conscious eyeblink is approximately 72.7% for the experimental sample of 30 subjects. While, the average rate of successful differentiating of unconscious eyeblink is approximately 90.3%. Thus, the average accuracy rate of total is 83.6%. In unconscious eyeblinks are high identification rate, however in conscious eyeblinks are lower as compared to the unconscious rate. At this point, we believe that this passed differentiating of conscious blink is not a major problem. If these passed differentiating occur, the input can be attempted again through an intentional repetition of the conscious eyeblink. Therefore, we think the accuracy rate of unconscious is more important than conscious rate. In addition, there are often subjects of only a low accuracy rate of either conscious or unconscious. Because we used a simple algorithm in this experiment (e.g. subject 1, 3, 5, and more…) intend to improve the accuracy of differentiating by using a combination of two parameters.

Following the experiments, we interviewed the subjects and discovered that some subjects did not perform eyeblinks consciously when signals were given because their unconsious eyeblinks occurred at the same rate. On the basis of the results of these interviews, we plan to revise future instructions to promote more clarity. In addition, the classification of eyeblink types can be improved based on those subjects who did not show significant differences.

Conclusion

In this paper, we proposed a method for automatic differentiation of conscious eyeblinks. A method that can automatically differentiate between conscious and unconscious eyeblinks is an important prerequisite for developing an input interface for eyeblinks. The results of the evaluation experiment conducted using the proposed method show that it is possible to automatically distinguish eyeblinks with higher accuracy than in previous studies if there is a small difference in the eyeblink duration. The proposed method shows that it is possible using a frame-splitting method even in environments that use a low time resolution video camera. The results of our evaluation experiment conducted with 30 different subjects indicate that the average accuracy is 83.6%. We required to fix head lightly and to detach glasses from subjects. This is a problem at actual use. We believe that this problem can be solve by image processing using motion vector. Consequently, typical information devices will able to control using eyeblinks, only installing software based on proposed method.

In the future, we plan to develop a real-time computer input system based on proposed measuring system. We also plan to improve this method to increase the detection accuracy and investigate methods by which this system can be incorporated into mobile devices. And we want to validate racial and cultural difference influence to eyeblinks.

Fig. 1 .

 1 Fig. 1. Model of eyeblink waveform.

Fig. 4 .

 4 Fig. 4. Example of an eyeblink waveform.

Fig. 5 .

 5 Fig. 5. Example of a difficult-to-decide minimum point.

Table 1 .

 1 Strengths and weaknesses of previous works.

	Fixed-length	Concepts	Special eye
	threshold [16, 17]		movements [18, 19]
	Easy	Inputting	Have to practice
	Necessary	Calibration	May be necessary
	A bit too much	Get exhausted	Much
	High	Requisite measuring accuracy	Low
	Difficult	Estimate of intention	Easy

Table 2 .

 2 Results of preliminary experiment[START_REF] Matsuno | Analysis of trends in the occurrence of eyeblinks for an eyeblink input interface[END_REF].

	Parameter type Subject number Rate
	Both parameters	23	46%
	Duration only	12	24%
	Amplitude only	11	22%
	No difference	4	8%
	Total	50	100%

Table 3 .

 3 Results of the extracted parameters.

	Subjects		Conscious Eyeblinks	Unconscious Eyeblinks	Normalization
		Counts Duration	Amplitude	Counts Duration	Amplitude	Selected
			(ms)	(pixel)		(ms)	(pixel)
	1	4	841	6799	7	650	6789	Duration
	2	5	590	7906	6	335	4875	Duration
	3	5	580	7054	16	338	5725	Duration
	4	3	755	14111	5	393	12195	Duration
	5	5	706	13009	4	511	10558	Duration
	6	2	325	18785	3	288	11858	Amplitude
	7	5	1053	19852	4	450	17100	Duration
	8	5	660	16718	3	553	14435	Duration
	9	5	560	15216	5	256	10850	Duration
	10	5	553	15552	4	316	11326	Duration
	11	5	400	9370	4	278	6620	Duration
	12	5	463	7829	4	341	6918	Duration
	13	5	686	5883	9	445	3763	Amplitude
	14	5	733	10139	2	308	6817	Duration
	15	5	576	9919	3	288	7077	Duration
	16	5	390	11880	6	350	10942	Duration
	17	5	623	11268	1	366	11213	Duration
	18	4	400	14121	3	376	8291	Amplitude
	19	4	625	9160	14	331	7166	Duration
	20	4	595	12904	19	263	7481	Duration
	21	5	530	13494	17	336	10860	Duration
	22	5	376	11559	18	345	10951	Duration
	23	5	553	5644	5	486	5631	Duration
	24	5	386	7059	21	256	6553	Duration
	25	5	606	5564	20	400	5095	Duration
	26	5	686	9257	13	385	7822	Duration
	27	5	856	8673	15	436	7948	Duration
	28	5	530	7122	8	279	5119	Duration
	29	5	500	8699	6	435	6885	Amplitude
	30	4	436	6418	3	216	3385	Duration

Table 4

 4 provides the results of automatic distinction rate. Representative results of the experiment are displayed in relation to measured conscious and unconscious blinks. The table shows counts of detected conscious eyeblinks Vi and unconscious eyeblinks Si, distinction error of conscious eyeblinks Ev, and unconscious eyeblinks Es, distinction accuracy rate of conscious eyeblinks Cv and unconscious eyeblinks Cs, and total accuracy rate Ct. The accuracy rate values Cv, Cs, and Ct are determined from the following equations:

Table 4 .

 4 Results of automatic distinction rate of conscious eyeblinks.

	Subjects Counts of eyeblink	Distinction error	Distinction rate (%)
	Conscious Unconscious Conscious Unconscious Conscious Unconscious	All
	1	11	12	4	1	63.6	91.7	78.3
	2	10	11	0	0	100.0	100.0	100.0
	3	10	39	8	4	20.0	89.7	75.5
	4	10	12	0	0	100.0	100.0	100.0
	5	10	10	7	0	30.0	100.0	65.0
	6	10	15	0	5	100.0	66.7	80.0
	7	10	12	0	3	100.0	75.0	86.4
	8	10	7	5	0	50.0	100.0	70.6
	9	9	11	1	0	88.8	100.0	95.0
	10	10	10	0	0	100.0	100.0	100.0
	11	9	15	2	3	77.7	80.0	79.2
	12	10	13	2	3	80.0	76.9	78.3
	13	10	17	1	0	90.0	100.0	96.3
	14	10	12	0	0	100.0	100.0	100.0
	15	9	6	5	0	44.4	100.0	66.7
	16	10	12	7	0	30.0	100.0	68.2
	17	10	7	4	0	60.0	100.0	76.5
	18	10	3	1	0	90.0	100.0	92.3
	19	7	29	3	0	57.1	100.0	91.7
	20	10	43	1	12	90.0	72.1	75.5
	21	10	49	3	4	70.0	91.8	88.1
	22	10	23	1	8	90.0	65.2	72.7
	23	10	17	5	0	50.0	100.0	81.5
	24	7	58	3	5	57.1	91.4	87.7
	25	9	47	7	5	22.2	89.4	78.6
	26	10	35	2	7	80.0	80.0	80.0
	27	10	21	4	3	60.0	85.7	77.4
	28	10	16	2	1	80.0	93.8	88.5
	29	10	15	0	3	100.0	80.0	88.0
	30	11	10	0	2	100.0	80.0	90.5
	Average					72.7	90.3	83.6

Acknowledgment

We thank Mr. Hironobu Sato of the Kanto Gakuin University College of Science and Engineering for his advice, comments and help in this study. This work was supported by JSPS KAKENHI Grant Number 24700598.