Efficient Web Browsing with a Single-Switch

Laurianne SitbonQueensland University of

TechnologyBrisbane, Australia

l.sitbon@qut.edu.au

Oscar WongQueensland University of

TechnologyBrisbane, Australia

oscarwong91@gmail.com

Margot BreretonQueensland University of

TechnologyBrisbane, Australia

m.brereton@qut.edu.au

ABSTRACTThis paper presents a new approach to web browsing in situ-ations where the user can only provide the device with a sin-gle input command device (switch). Switches have been de-veloped for example for people with locked-in syndrome andare used in combination with scanning to navigate virtualkeyboards and desktop interfaces. Our proposed approachleverages the hierarchical structure of webpages to operate amulti-level scan of actionable elements of webpages (links orform elements). As there are a few methods already exist-ing to facilitate browsing under these conditions, we presenta theoretical usability evaluation of our approach in com-parison to the existing ones, which takes into account theaverage time taken to reach any part of a web page (suchas a link or a form) but also the number of clicks necessaryto reach the goal. We argue that these factors contributetogether to usability. In addition, we propose that our ap-proach presents additional usability benefits.

Keywordsdisability, web browsing, single switch, scanning

Categories and Subject DescriptorsH.5.2. [Information Interfaces and Presentation (e.g.HCI)]: User Interfaces

1. INTRODUCTIONInternet is central in many people’s lives, as much as a tool

for accessing services, as a source of knowledge, entertain-ment and communication. Modern websites are generallynavigated through by a pointing device (e.g. mouse) anda keyboard. Although there are some efforts put on cre-ating new browsing experience (e.g. Opera face gestures),a mouse and a keyboard are still the devices that websitesare designed for. While keyboards are generally involved toinform text fields in forms, pointing devices are used to ac-

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tivate contents such as hyperlinks, form elements, but alsodisplay of dynamic contents.

While people are trying to improve the browsing speed byintroducing different gestures, one should not ignore peoplewith motor impairments. Some people with physical dis-ability cannot manipulate classical pointing devices or key-boards, which is why single switch inputs have been devel-oped and are often used to control virtual keyboards anddesktop based software with a minimal physical require-ments. In these instances desktop software (including virtualkeyboards) is designed or augmented to integrate a scan-ning mechanism, which sequentially highlights different ac-tionable elements of the software for selection by the user.Other technologies specially designed as a replacement for amouse as pointing device include eye tracking devices, how-ever despite their high efficiency ([3] suggested that it canbe 60% faster than using mouse control), they remain veryexpensive and are therefore not accessible to all.

In order to reduce the barrier to access, we propose anovel light-weight web browser plugin which enables usersto web-surf using a single switch, by dynamically generatinga scanning layer on webpages using a browser plugin tech-nology. In this paper, we first present our methodology thatleverages the hierarchical structure of web pages to facilitateaccess to specific parts of the page, in particular links. Wethen present a theoretical evaluation of usability to compareour approach to existing ones, using simulation. Namely, wemeasure the average wait time and the average number ofclicks necessary to attain any link in any page.

2. RELATED WORKAlthough there are some single-switch browsing techniques

being developed, only a few of them are designed for webbrowsing. They generally follow one of two navigation algo-rithms as follows.

2.1 TabbingTabbing is the most common approach for single-switch

navigation. In webpages, most of the elements can be navi-gated through pressing the tab key on the keyboard. Someof the applications, for example AVANTI browser [5], Mul-tiWeb Browser [2] and the Hawking toolbar extension forMozilla Firefox, simulate the “tabbing” action on keyboardand scans through elements at a fixed time interval. Thereare other variations which extract all the links and displaythem on a separated list [1]. In both cases, the user accessesthe active zones of the page (links and form elements) insequential order. For example, with a time interval of 1 sec-

ond, it would take 31 seconds to reach the link to the secondpage of results for a Google search for OzChi2014. Tabbingimplicitly allows scrolling control of a page, as the displaywill start adjusting to new contents to ensure a currentlyselected tab is always visible. It is an advantage (providedthe user can control the activation of scanning) as actionablezones are the ones of current interest. However it also meansthat the user is limited to the pace of the scan to read con-tents, which in turns depends on the number of actionablezones presented on the screen.

2.2 Keyboard NavigationA more efficient alternative keyboard navigation. Vir-

tual keyboards are widely available and generally offer singleswitch on-screen scanning capabilities. A number of optimi-sations of the layout, including hierarchical layouts, accel-erate access to a given key (rather than offering sequentialaccess).

The web browser Conkeror (http://conkeror.org), devel-oped based on Mozilla Firefox, assigns a navigation key (ID)to each elements on a web page. Another example is theKeysurf plugin on Mozilla Firefox, which is a search basednavigation system with a ranking system for the result ele-ments in the page [4]. Keysurf also offers access via a uniquenaming of each element, which can be a combination of let-ters and numbers where the letters are generally the firstletters of the element (for links) and numbers follow in caseseveral element have the same starting letter. Non lexicalelements (text boxes or images) are represented with num-bers only. For example, for a document with 3 link namedapple, april and amazon, all the links started with a canbe selected by typing a , a0 and a1, instead of ap1, ap2and am. Keysurf is the most well-developed plugin and hasdemonstrated state of the art performance in terms of theaccuracy and key-stroke efforts.

Keyboard navigation requires the user to fully controlscrolling of the page displayed, which requests additionalinput from the user and can considerably increase the timespent by a user in controlling the view in addition to access-ing actionable zones.

3. THE 1CLICK BROWSING APPROACHOur single input web browsing plugin is a Google Chrome

plugin which uses a “divide and conquer” approach, leverag-ing hierarchical information on the display of contents pre-sented in web pages.

When a page is loaded, each high level zone in the page ishighlighted in a scanning sequence with a fixed time inter-val.A highlighted zone is the current active zone which canencompass content as well as actionable zones. When theuser clicks on an active zone, if this zone contains severallower level content zones, then these are sequentially high-lighted in turn. If the active zone contains only one elementthat is an actionable zone, then the click equates to that ofa regular pointing device click. An example of sequence ofscanning and clicks is presented in figure 1.

When a zone is highlighted, the position of the page isautomatically updated. That is, there is no need for theuser to scroll down. 1

1Additional single input controls have been integrated in theplugin to allow the scrolling to pause and to reverse actions.However these are not the focus of the present paper.

a)# b)#

c)# d)#

e)# f)#

Figure 1: Example of successive views to attain aspecific link on the OzChi 2013 webpages. Clicksoccur after steps b), d) and f). The active zone isrepresented in black and the future active zone ingrey.

A green border is added to indicate the next element in thescanning sequence (represented in grey on figure 1) in orderto support anticipation, which is a typical issue of scanningapproaches ([4]).

From a technical perspective, the algorithm first builds ahierarchy of all the elements on the page and stores it in adata structure. The hierarchy uses HTML tags in the samefashion that they are reconciled with CSS. The representa-tion is then compressed to remove the empty layers. Emptylayers are common for websites that use CSS for display,and if not compressed and can result in additional delaysto reach an element. This is why the entire mapping hasto be done completely when the page is loaded rather thandynamically as the user selects subsections. Figure 2 showsan example of a final representation.

4. SIMULATION AND EVALUATIONWe propose that the two measurable factors affecting us-

ability of such a system are waiting time (WT) and numberof user actions (NUA). Waiting time is proportional to the

Figure 2: Example of compressed structure obtainedwith the mapping algorithm

number of zones (single elements or groups) the scanner tra-verses to arrive at the desired element in a page, whether itis scanning directly on the page, through a list of actionablezones, or on a virtual keyboard. The number of user actionsis the number of times the user actions the switch to reacha given actionable zone. While wait time may lead to frus-tration and lack of patience, excessive number of necessaryclicks may lead to fatigue.The best balance between thesetwo factors may also depend on the scanning speed that auser may be able to work with. If the scan is fast, then a highnumber of clicks would be more tiring and and differencesin wait time may not be very significant. On the contrary,if the scan is slow, then more clicks would be preferred tovery long wait times.

We first establish the estimated average performance onthese two factors for our 1Click plugin, Keysurf, and thelinear scanning navigation. This theoretical measure usesone or all of structure of the documents (for 1Click), thenumber of elements in the documents (for scanning) or thelexical organisation of the elements (for KeySurf).

We next simulate the behaviour of these 3 methods tomeasure their average NUA and WT on actual websites.Our evaluation is based on the 121 most popular websitesas listed on Alexa in January 2013. It is a combination ofthe top 100 viewed websites worldwide and in Australia withduplicates under various domain names removed. Searchengines are evaluated at the first search results page. Whileseveral of these websites are in non alphabetical languagesnot suitable keyboard-based approaches, we include themin the evaluation as they do represent a majority of usersworldwide but also in multicultural Australia.

4.1 TabbingTabbing navigation is a linear scanning operation, which

only involves one user action when the target is reached.The theoretical average wait time to access any element canbe expressed by the following function:

AWT =

∑elementwaittime

Total number of elements(1)

4.2 KeySurfWe estimate and simulate KeySurf efficiency in a single-

switch context with the code-based access and a dynamicvirtual keyboard, which groups characters into tiers accord-ing to their appearing frequency in the document, as illus-trated on Figure 3 where 1st tier would be the 2 most fre-quent letters in the document (eg. e and w). Hierarchicalscanning scrolls over lines first and then individual charac-ters (including letters, numbers and commands). In this de-sign, every key can be attained in a maximum of 6 wait time

Figure 3: Virtual keyboard to simulate KeySurf

periods while reducing this time for the most needed keys.KeySurf requires a code composed of one letter or number,and/or a number with a number of digits depending on thenumber of actionable elements likely to start with the sameletter. As an estimate, we can consider that any componentof the code can be reached in 3.5 wait time period on thevirtual keyboard.

In addition, this approach requires a scroll up and scrolldown button to ensure that the user can visualise all theeligible elements if a single browser frame cannot display allthe elements. By a rough estimation, the maximum numberof elements in a single browser frame is around 200. It meansthat if the document has around 200 -400 elements, the userhas to scroll once to select all the elements in the document.This value is just for reference however it does affect theusability of the extension.

The theoretical average wait time for KeySurf cannot beexactly determined as it depends on the distribution of theletters of the actionable zones and their nature, however wepropose to estimate it as follows:

AWT = 7∗EWT∗|TNE

200|+3.5∗(1+LOG10(1+

TNE

26)) (2)

where EWT is the individual element wait time and TNE isthe total number of elements. The first part of the equationis for the estimated number of scrolls, and the second partis for the estimated number of letters/numbers of the code.

4.3 1Click browser pluginWith our plugin, WT and NUA depend on the shape of

the tree that maps the structure of the document. The depthof an element in the tree is the NUA needed for that element(user input is required to go from a higher to a lower levelin the structure). The wait time depends on the width ofthe lower subtree containing the element, and on that of allhis parents.

An estimate can therefore be drawn from the averagewidth and depth of the compressed document structure:

AWT =Avg. Width of Layers

2 ∗Avg. depth of structure(3)

ANUA = Avg. depth of structure (4)

3  

8  

13  

18  

23  

28  

0   200   400   600   800   1000  

Average  Wai*n

g  Time  

Number  of  Ac*onable  Zones  

Avg  Wait  

KeySurf  Wait  

tab  wait  

keysurf  /w  scroll  

1Click  EsAmated  Wait  Keysurf  EsAmated  Wait  Log.  (Avg  Wait)  

Log.  (KeySurf  Wait)  

Linear  (tab  wait)  

Linear  (keysurf  /w  scroll)  Log.  (1Click  EsAmated  Wait)  Linear  (Keysurf  EsAmated  Wait)  

Figure 4: Average wait to reach any link for eachapproach (estimated, simulated and interpolated).

5. RESULTSThe average WT have been estimated and simulated for

each approach and reported based on the number of ele-ments for each of the 121 most popular web pages in Fig-ure 4. In combination with the proposed dynamic virtualkeyboard and not accounting for scrolling, KeySurf has aconsistent performance between 6 and 8 units of time, in-cluding for small documents, making 1Click a better choicefor documents under 100 elements. If we estimate a need toscroll every 200 elements, then the AWT increases rapidly.If scrolling controls were placed at the beginning of the key-board, then they would incur an additional wait time forsmall pages as well. In this context, the 1Click Browser plu-gin show better performances in terms of average wait timealso for larger documents.

The estimated (theoretical) AWT and simulated AWT forthe 121 most popular web pages, as well as their interpola-tions presented on Figure 4 shows a reasonable alignmentalthough the estimates could be further refined to accountfor complexity and unbalance of document structures andlexicon of actionable zones.

The estimated and simulated average number of user ac-tions are presented on Figure 5. It shows that, as expected,the number of clicks (user actions) required to access an ac-tionable zone is on average smaller for small documents withKeySurf, but much better and stable with 1Click for largerdocuments.

6. FUTURE WORKSo far we have made the simplifying assumption that a

user is equally likely to reach for any element in the page,when in reality web designer strategically place the most at-tractive elements either at the beginning of the document toensure usability, or at the end to encourage users to reads ev-erything. In terms of usability, we argue that scanning based

0"

10"

20"

0" 200" 400" 600" 800" 1000"

Average'Num

ber'o

f'User'A

c1on

s'(clicks)'

Number'of'Ac1onable'zones'

1Click"est."avg."NUA"

Keysurf"avg."NUA"

Log."(1Click"est."avg."NUA)"

Poly."(Keysurf"avg."NUA)"

Figure 5: Average number of user action (NUA) for1Click and KeySurf (tab is always 1).

navigation is more intuitive than a search based navigation.The user does not need to switch his/her focus between thepage and the on screen keyboard. Instead, the user onlyneed to concentrate on where the focus of the scanner is andselect the desired group of elements. Future work will focuson user studies with users needing such assistance, whetheror not they currently use such assistive technologies.

The plugin is freely available on request to the authors.An immediate extension will be to further break up a longlist of elements into smaller groups (ie. the language selec-tion part in a Wikipedia page with 20+ links).

The technology we propose here could be combined withlow resolution eye tracking to speed up access to large zones,and use the scan for parts of the page too small for highprecision detection (such as a list of links for example).

7. ACKNOWLEDGEMENTSLars Gullestrup has contributed to the implementation.

8. REFERENCES[1] J. Mankoff, A. Dey, U. Batra, and M. Moore. Web

accessibility for low bandwidth input. In In Proc. of theFifth ACM SIGCAPH Conference on AssistiveTechnologies, pages 17–24. ACM Press, 2002.

[2] J. Owens, S. Keller, and D. University. MultiWeb[electronic resource] : Australian contribution to webaccessibility / Janet Owens, Susan Keller. Institute ofDisability Studies, School of Management InformationSystems Burwood, Vic, 2000.

[3] L. E. Sibert and R. J. K. Jacob. Evaluation of eye gazeinteraction. In Proceedings of the SIGCHI conferenceon Human Factors in Computing Systems (CHI00),pages 281–288, 2000.

[4] L. Spalteholz. Keysurf-a keyboard web navigationsystem for persons with disabilities. Master’s thesis,University of Victoria, 2012.

[5] C. Stephanidis, A. Paramythis, C. Karagiannidis, andA. Savidis. Supporting interface adaptation: the avantiweb-browser. In Proc. of 3rd ERCIM workshop on userinterfaces for all, pages 3–4, 1997.