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564 lines
33 KiB
564 lines
33 KiB
% MORE INFO
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% WRUED: https://www.ccohs.ca/oshanswers/diseases/rmirsi.html
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\section{Literature Review}
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In this section, we gathered information about conventional methods, tools and
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metrics that are used in the domain of keyboard related research. We were
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particularly interested in how keyboard usage is related to health risks, the
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status quo of keyboard design, which metrics to use when conducting a typing
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related experiment and previous studies that evaluated the impact of key
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actuation force on those metrics. The information collected during the
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literature review ensured a profound understanding of those topics, which helped
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us during the design phase of our two preliminary studies and the main
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study. Additionally, we partially established our hypotheses based on the
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results of previous research.
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\subsection{Work Related Upper Extremity Disorders}
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\label{sec:wrued}
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\Gls{WRUED} is a term to describe a group of medical conditions related to
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muscles, tendons and nerves in shoulder, arm, elbow, forearm or hand, such as
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e.g., \gls{CTS}, \gls{RSI}, tendonitis, tension neck syndrome, etc. Symptoms of
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\gls{WRUED} are aching, tiredness and fatigue of affected regions that either
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occur while working or even extend to phases of relaxation. A common way to
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treat \gls{WRUED} is to avoid the potentially harmful activities that cause
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discomfort in affected areas \cite{ccfohas_wrued}. Pascarelli and Hsu reported,
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that out of 485 patients with \gls{WRUED} 17\% were computer users
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\cite{pascarelli_wrued}. Since computers have become an essential part of many
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jobs in almost any sector of employment, restrictions of computer related
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activities would result in either reduced productivity or the complete inability
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to fulfill required tasks, which in the worst case could require a change of
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profession \cite{ccfohas_wrued}. Potential problems with current keyboard
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designs and possible solutions are discussed in the following sections.
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\begin{phga_sum*}
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\gls{WRUED} are a serious problem of modern society and since there is evidence
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pointing towards computer related work to be a possible factor for these
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diseases, it is likely that especially keyboards, as the main input device, are
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responsible for a portion of people affected by \gls{WRUED}.
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\end{phga_sum*}
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\subsection{Keyboards and Keyswitches}
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\label{sec:kb_ks}
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\subsubsection{Keyboard Models and Layouts}
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\label{sec:kb_layout}
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\begin{figure}[ht]
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\centering
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\includegraphics[width=1.0\textwidth]{images/keyboard_models.jpg}
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\caption{Different keyboards, including alternative split models, smaller form
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factors and traditional layouts such as ISO/IEC 9995 \cite{iso9995-2} and
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ANSI-INCITS 154-1988 \cite{ansi-incits-154-1988}}
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\label{fig:keyboard_models}
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\end{figure}
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Keyboards are well known input devices used to operate a computer. There are a
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variety of keyboard types and models available on the market, some of which can
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be seen in Figure \ref{fig:keyboard_models}. The obvious difference between
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those keyboards in Figure \ref{fig:keyboard_models} is their general
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appearance. The keyboards feature different enclosures and keycaps, which are
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the rectangular pieces of plastic on top of the actual keyswitches that
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sometimes indicate what letter, number or symbol, also known as characters, a
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keypress should send to the computer. These keycaps are mainly made out of the
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two plastics \gls{ABS} and \gls{PBT} which primarily differ in feel, durability,
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cost and sound \parencite[8]{bassett_keycap}.
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\begin{figure}[ht]
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\centering
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\includegraphics[width=1.0\textwidth]{images/keyboard_layouts.png}
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\caption{The three major physical keyboard layouts all labeled with the
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alphanumeric characters of the most popular layout―\gls{QWERTY}
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\cite{wiki_kb_layouts}}
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\label{fig:keyboard_layouts}
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\end{figure}
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Nowadays, there are three main standards that define the physical layout of a
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keyboard―ISO/IEC 9995 \cite{iso9995-2}, ANSI-INCITS 154-1988
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\cite{ansi-incits-154-1988} and JIS X 6002-1980 \cite{jis-x-6002-1980}. These
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layouts propose slightly different arrangements of the keys and some even alter
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the shape of a few keys entirely. Figure \ref{fig:keyboard_layouts} shows the
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layouts defined by the three standards mentioned and shows the main
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differences. In addition to the physical layout, there are also various layouts
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concerning the mapping of the physical key to a character that is displayed by
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the computer. Most of the time, the mapping happens on the computer via software
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and therefore the choice of layout is not necessarily restricted by the physical
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layout of the keyboard but rather a personal preference. As seen in Figure
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\ref{fig:keyboard_models}, there are also non standard physical layouts
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available which are often designed to improve the posture of the upper extremity
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while typing to reduce the risk of injury or even assist in recovering from
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previous \gls{WRUED} \cite{ripat_ergo, tittiranonda_ergo}. Those designs often
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split the keyboard in two halves to reduce ulnar deviation and some designs also
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allow tenting of the halves or provide a fixed tent which also reduces forearm
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pronation \cite{baker_ergo, rempel_ergo}.
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\subsubsection{Membrane Keyswitch}
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\label{sec:mem_switch}
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Besides the exterior design of the keyboard, there is another part of
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interest—the keyswitch. This component of a keyboard actually sends the signal
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that a key is pressed. There are different types of keyswitches available to
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date. The most commonly used ones are scissor switches and rubber dome switches
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which are both subsets of the membrane switch family. Scissor switches are often
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found in keyboards that are integrated into notebooks while rubber dome switches
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are mostly used in workplace keyboards. Both variants use a rubber membrane with
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small domes underneath each key. When a key is pressed, the corresponding dome
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collapses and because the dome's inner wall is coated with a conductive
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material, closes an electrical circuit \cite{ergopedia_keyswitch,
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peery_3d_keyswitch}.
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\subsubsection{Mechanical Keyswitch}
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\label{sec:mech_switch}
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Another type of switches are mechanical keyswitches. These switches are
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frequently used in gaming and high quality workplace keyboards as well as by
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enthusiast along with prosumers which build and then sell custom made keyboards
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to the latter audience \cite{bassett_keycap, ergopedia_keyswitch}. These
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keyswitches are composed of several mechanical parts which can be examined in
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Figure \ref{fig:mech_keyswitches_dissas}. The housing is made up of two parts,
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the bottom and top shell. The actual mechanism consists of two conductive
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plates, which when connected trigger a keypress, a stainless steel spring which
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defines how much force has to be applied to the switch to activate it and a stem
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which sits on top of the spring and separates the two plates. The shape of the
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stem, represented by the enlarged red lines in Figure
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\ref{fig:mech_keyswitches_dissas}, defines the haptic feedback produced by the
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keyswitch. When pressure is applied to the keycap, which is connected to the
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stem, the spring gets contracted and the stem moves downwards and thereby stops
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separating the two plates which closes the electrical circuit and sends a
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keypress to the computer. After the key is released, the spring pushes the stem
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back to its original position \cite{bassett_keycap, peery_3d_keyswitch,
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ergopedia_keyswitch, chen_mech_switch}. Usually, mechanical keyswitches are
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directly soldered onto the \gls{PCB} of the keyboard but there are also
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keyboards where the \gls{PCB} features special sockets where the keyswitches can
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be hot-swapped without soldering at all \cite{gmmk_hot_swap}. It is also
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possible to equip an already existing \gls{PCB} with sockets to make it
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hot-swappable \cite{te_connect}.
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\begin{figure}[ht]
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\centering
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\includegraphics[width=1.0\textwidth]{images/mech_keyswitches_dissas.jpg}
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\caption{Disassembled tactile, clicky and linear mechanical keyswitchs. The
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red lines resemble the shape of the stem which is responsible for the haptic
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feedback and thus, in combination with the strength of the spring, the
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required actuation force}
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\label{fig:mech_keyswitches_dissas}
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\end{figure}
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Mechanical keyswitches also have three main subcategories. Those categories
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primarily define if and how feedback for a keypress is realised:
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\begin{enumerate}
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\item \textbf{Tactile Switches} utilize a small bump on the stem to slightly
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increase and then instantly collapse the force required immediately before the
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actual actuation happens \cite{cherry_mx_brown}. This provides the typist with
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a short noticeable haptic feedback and which should encourage a premature
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release of the key. An early study by Brunner and Richardson suggested, that
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this feedback leads to faster typing speeds and a lower error rate in both
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experienced and casual typists (n=24) \cite{brunner_keyswitch}. Contrary, a
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study by Akagi yielded no significant differences in terms of speed and error
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rate between tactile and linear keyswitches and links the variation found in
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error rates to differences in actuation force (n=24)
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\cite{akagi_keyswitch}. Tactile feedback could still assist the typist to
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prevent \gls{bottoming}.
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\item \textbf{Tactile and audible Switches (Clicky)} separate the stem into
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two parts, the lower part also features a small bump to provide tactile
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feedback and is also responsible for a distinct click sound when the actuation
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happens \cite{cherry_mx_blue}. Gerard et al. noted, that in their study
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(n=24), keyboards with audible feedback increased typing speed and decreased
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typing force. This improvement could have been due to the previous experience
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of participants with keyboards of similar model and keyswitch characteristic
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\cite{gerard_keyswitch}.
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\item \textbf{Linear Switches} do not offer a distinct feedback for the
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typist. The activation of the keyswitch just happens after approximately half
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the total travel distance \cite{cherry_mx_red}. The only tactile feedback that
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could happen is the impact of \gls{bottoming}, but with enough practice,
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typist can develop a lighter touch which reduces overall typing force and
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therefore reduces the risk of \gls{WRUED} \cite{gerard_keyswitch,
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peery_3d_keyswitch, fagarasanu_force_training}.
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\end{enumerate}
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The corresponding force-displacement curves for one exemplary keyswitch of each
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category by the manufacturer Cherry are shown in Figure
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\ref{fig:ks_fd_curves}. The Operational position indicates the activation of the
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keyswitch.
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\begin{figure}[ht]
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\centering
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\includegraphics[width=1.0\textwidth]{images/ks_fd_curves.jpg}
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\caption{Actuation graphs for Cherry MX BROWN \cite{cherry_mx_brown} | BLUE
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\cite{cherry_mx_blue} | RED \cite{cherry_mx_red} switches. Tactile position marks the point where a haptic feedback happens, operational position marks the activation of the keyswitch and reset position is the point where the keyswitch deactivates again}
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\label{fig:ks_fd_curves}
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\end{figure}
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All types of keyswitches mentioned so far are available in a myriad of actuation
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forces. Actuation force, also sometimes referred to as make force, is the force
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required to activate the keyswitch \cite{radwin_keyswitch,
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ergopedia_keyswitch}. That means depending on the mechanism used, activation
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describes the closing of an electrical circuit which forwards a signal, that is
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then processed by a controller inside of the keyboard and finally send to the
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computer. The computer then selects the corresponding character depending on the
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layout used by the user. Previous studies have shown, that actuation force has
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an impact on error rate, subjective discomfort, muscle activity and force
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applied by the typist \cite{akagi_keyswitch, gerard_keyswitch,
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hoffmann_typeright} and as suggested by Loricchio, has a moderate impact on
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typing speed, which could be more significant with greater variation of
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actuation force across tested keyboards \cite{loricchio_force_speed}.
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\begin{phga_sum*}
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Since this thesis is focused around keyboards and especially the relation
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between the actuation force of the keyswitch and efficiency (speed, error rate)
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and also the differences in satisfaction while using keyswitches with varying
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actuation forces, it was important to evaluate different options of keyswitches
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that could be used to equip the keyboards used in the experiment. The literature
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suggested, that the most common switch types used in the broader population are
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rubber dome and scissor switches \cite{ergopedia_keyswitch,
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peery_3d_keyswitch}. Naturally, those keyswitches should also be used in the
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study, but one major problem due to the design of those keyswitches arises. It
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is not easily possible to alter the actuation force of individual keyswitches
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\cite{peery_3d_keyswitch}. This will be necessary to create a keyboard where
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each key should have an adjusted actuation force depending on the finger that
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normally operates it. It should be mentioned, that it is theoretically possible
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to exchange individual rubber dome switches on some keyboards, e.g. keyboards
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with \gls{Topre} switches, but the lacking availability of compatible keyboards
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and especially the limited selection of actuation forces (30g to 55g for
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\gls{Topre} \cite{realforce_topre}) makes this not a viable option for this
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thesis \cite{keychatter_topre}. Therefore, we decided to use mechanical
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keyswitches for our experiment, because these keyswitches are broadly available
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in a variety of actuation forces and because the spring which mainly defines the
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actuation force can be easily replaced with any other compatible spring on the
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market, the selection of actuation forces is much more appropriate for our use
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case (30g to 150g) \cite{peery_3d_keyswitch}. We also decided to use linear
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switches because they closest resemble the feedback of the more wide spread
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rubber dome switches. Further, linear switches do not introduce additional
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factors beside the actuation force to the experiment. In addition, based on the
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previous research we settled on using a keyboard model with hot-swapping
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capabilities for our experiment to reduce the effort required to equip each
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keyboard with the required keyswitches and in case a keyswitch fails during
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the experiment, decrease the time required to replace the faulty switch.
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\end{phga_sum*}
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\subsection{Measurement of Typing Related Metrics}
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\label{sec:metrics}
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Nowadays, a common way to compare different methods concerning alphanumeric
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input in terms of efficiency is to use one of many typing test or word
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processing applications which are commercially available. Depending on the
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software used and the experimental setup, users have to input different kinds of
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text, either for a predefined time or the time is measured till the whole text
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is transcribed \cite{chen_typing_test, hoffmann_typeright,
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fagarasanu_force_training, akagi_keyswitch, kim_typingforces,
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pereira_typing_test, baker_ergo}.
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\subsubsection{Readability of Text}
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\label{sec:meas_fre}
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Text used should be easy to read for typists
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participating in studies that evaluate their performance and are therefore is
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chosen based on a metric called the \gls{FRE} which indicates the
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understandability of text \cite{fagarasanu_force_training,
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kim_typingforces, flesch_fre}. The score ranges from 0 which implies very poor reading
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ease to 100 suggesting that the style of writing used causes the text to be very
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easy to comprehend \cite{flesch_fre}. Immel proposed an adjusted formula of the
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\gls{FRE} that is suitable for German text \cite{immel_fre} and can be seen in
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(\ref{eq:fre_german}).
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\begin{equation}\label{eq:fre_german}
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FRE_{deutsch} = 180 - \underbrace{ASL}_{\mathclap{\text{Average Sentence Length}}} - (58,5 * \overbrace{ASW}^{\mathclap{\text{Average Syllables per Word}}})
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\end{equation}
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According to Flesch, the values retrieved by applying the formula to text can be
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classified according to the ranges given in Table \ref{tbl:fre_ranges} \cite{flesch_fre}.
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\begin{table}
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\centering
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\small
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\ra{1.3}
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\begin{tabular}{?l^c}
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\toprule
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\multicolumn{1}{c}{\emph{FRE}}& \emph{Understandability} \\
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\midrule
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\multicolumn{1}{c}{0 - 30} & Very difficult \\
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30 - 50 & Difficult \\
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50 - 60 & Fairly difficult \\
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60 - 70 & Standard \\
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70 - 80 & Fairly easy \\
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80 - 90 & Easy \\
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\multicolumn{1}{r}{90 - 100} & Very easy \\
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\bottomrule
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\end{tabular}
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\caption{Categories for different FRE scores to classify the understandability
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of text \cite{flesch_fre}}
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\label{tbl:fre_ranges}
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\end{table}
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\subsubsection{Performance Metrics}
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\label{sec:meas_perf}
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There are several metrics to measure the performance of typists. Typical methods
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to measure speed are
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\begin{enumerate}
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\item \textbf{\Gls{WPM}}
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\begin{equation}\label{eq:wpm}
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WPM = \frac{|T| - 1}{S} * 60 * \frac{1}{5}
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\end{equation}
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In Eq. (\ref{eq:wpm}), $|T|$ is the length of the transcribed text, $S$ the
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time in seconds taken to transcribe $T$, $\frac{1}{5}$ the average word length
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and $60$ the conversion to minutes. $|T| - 1$ counteracts the first input
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which starts the timer in many typing tests \cite{mackenzie_metrics}.
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\item \textbf{\Gls{AdjWPM}} is especially useful if participants are allowed to
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make mistakes and at the same time not forced to correct them. This method adds
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an adjustable factor to lower the \gls{WPM} proportionally to the uncorrected
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error rate $UER := [0;1]$ defined in Eq. (\ref{eq:uer}). The exponent $a$ in
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Eq. (\ref{eq:cwpm}) can be chosen depending on the desired degree of correction
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\cite{mackenzie_metrics}.
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\begin{equation}\label{eq:cwpm}
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AdjWPM = WPM * (1 - UER)^{a}
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\end{equation}
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\item \textbf{\Gls{KSPS}} measures the raw input rate of a typist by capturing
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the whole input stream including backspaces and deleted characters ($IS$)
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\cite{mackenzie_metrics}.
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\begin{equation}\label{eq:ksps}
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KSPS = \frac{|IS| - 1}{S}
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\end{equation}
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\end{enumerate}
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In addition to speed, the error rate of typists can be measured with the
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following two methods
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\begin{enumerate}
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\item \textbf{\gls{CER}} is the ratio of erroneous input that got fixed
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($IF$) to any character typed during transcription, including $IF$
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\cite{soukoreff_metrics}.
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\begin{equation}\label{eq:cer}
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CER = \frac{|IF|}{|T| + |IF|}
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\end{equation}
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\item \textbf{\gls{UER}} is the ratio of erroneous input that was \textbf{not}
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fixed ($INF$) to any character typed during transcription, including $IF$
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\cite{soukoreff_metrics}.
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\begin{equation}\label{eq:uer}
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UER = \frac{|INF|}{|T| + |IF|}
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\end{equation}
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\end{enumerate}
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\subsubsection{Electromyography}
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\label{sec:meas_emg}
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In several other studies, in addition to the metrics mentioned so far, \gls{EMG}
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data was captured to evaluate the muscle activity or applied force while typing
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on completely different or modified hardware \cite{kim_typingforces,
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fagarasanu_force_training, gerard_audio_force, gerard_keyswitch, martin_force,
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rose_force, rempel_ergo, pereira_typing_test}. \gls{EMG} signals, are captured
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with the help of specialized equipment that utilize electrodes which are either
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placed onto the skin above the muscles of interest (non-invasive) or inserted
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directly into the muscle (invasive). The disadvantage of non-invasive surface
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level electrodes is the lacking capability to capture the distinct signal of one
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isolated muscle \cite{reaz_emg}. Nevertheless, because this type of electrode is
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more likely to find acceptance among participants and is also easier to apply by
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non-medically trained researchers, it finds wide adoption among studies
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\cite{takala_emg}. To make \gls{EMG} data comparable across subjects, it is
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necessary to conduct initial measurements where each individual participant is
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instructed to first completely relax and then fully contract (\gls{MVC}) the
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muscles of interest. These values are used to normalize further data obtained in
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an experimental setting. The mean signal yielded by complete relaxation is
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subtracted to reduce noise and the \gls{MVC} is used to obtain the individuals
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percentage of muscle activity (\%MVC or EMG\%) during tests \cite{halaki_emg,
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takala_emg, rempel_ergo}. Muscles typically measured during typing exercises
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are the \gls{FDS}, \gls{FDP} and \gls{ED}. The main function of the \gls{FDS}
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and \gls{FDP} is the flexion of the medial four digits, while the \gls{ED}
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mainly extends the medial four digits. Therefore, these muscles are primarily
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involved in the finger movements required for typing on a keyboard
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\cite{netter_anatomy, kim_typingforces, gerard_keyswitch, gerard_audio_force}.
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A method frequently used to measure applied force is to place one or multiple
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load cells under the keyboard \cite{gerard_keyswitch, rempel_ergo,
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bufton_typingforces}. Load cells are electronic components that are able to
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convert applied force to an electrical signal. This signal usually gets
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amplified by specialized circuits and then further processed by a micro
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controller, computer or other hardware \cite{johnson_loadcell}.
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\subsubsection{Subjective Metrics}
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\label{sec:meas_sub}
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Lastly, subjective metrics e.g., comfort, usability, user experience, fatigue
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and satisfaction, are evaluated based on survey data collected after
|
|
participants used different input methods \cite{kim_typingforces,
|
|
bell_pauseboard, bufton_typingforces, pereira_typing_test, iso9241-411}. In
|
|
their study, Kim et al. used a modified version of the \gls{KCQ} provided by the
|
|
\gls{ISO} which is specifically designed to evaluate different keyboards in
|
|
terms of user satisfaction, comfort and usability \cite{kim_typingforces,
|
|
iso9241-411}. This survey poses a total of twelve questions concerning e.g.,
|
|
fatigue of specific regions of the upper extremity, general satisfaction with
|
|
the keyboard, perceived precision and uniformity while typing, etc., which are
|
|
presented on a seven-point Likert-scale \cite{iso9241-411}. Further, studies
|
|
concerning the usability and user experience of different text entry methods
|
|
used the \gls{UEQ} or \gls{UEQ-S} to evaluate the differences in those
|
|
categories \cite{nguyen_ueq, olshevsky_ueq, gkoumas_ueq}. While the full
|
|
\gls{UEQ} provides a total of 26 questions divided into six scales
|
|
(attractiveness, perspicuity, efficiency, dependability, stimulation and
|
|
novelty), the \gls{UEQ-S} only features 8 questions and two scales (pragmatic
|
|
and hedonic quality). Because of the limited explanatory power of the
|
|
\gls{UEQ-S}, it is recommended to only use it, if there is not enough time to
|
|
complete the full \gls{UEQ} or if the participants of a study are required to
|
|
rate several products in one session \cite{schrepp_ueq_handbook}.
|
|
|
|
\begin{phga_sum*}
|
|
Measuring metrics related to data entry tasks can be performed with the help
|
|
several commercially available tools and equipment. Especially muscle activity
|
|
has to be measured with appropriate tools and accurate placement of the
|
|
electrodes is important to ensure quality results \cite{takala_emg, halaki_emg,
|
|
kim_typingforces, gerard_keyswitch}. Metrics related to performance such as
|
|
\gls{WPM}, \gls{CER} and \gls{UER} are well defined and can be applied in almost
|
|
any experimental setup concerning the transcription of text
|
|
\cite{soukoreff_metrics, mackenzie_metrics}. In addition to the measured data,
|
|
questionnaires can help to gather subjective feedback about the keyboards and
|
|
thereby reveal differences that cannot be easily acquired by a device or formula
|
|
\cite{rowley_surveys}.
|
|
\end{phga_sum*}
|
|
\pagebreak
|
|
\subsection{Observer Bias and a Possible Solution}
|
|
\label{sec:bias}
|
|
As already discussed in Section \ref{sec:metrics}, it is common practice in
|
|
research related to typing to present a text that has to be transcribed by the
|
|
participant. Usually, the text was chosen by the researcher or already available
|
|
through the used typing test software. If the understandability of text is of
|
|
concern, the binary choice of, is understandable or not, made by the researcher
|
|
could lead to a phenomenon called the observer bias \cite{hrob_observer,
|
|
berger_observer, angrosino_observer}. Thus, the text could potentially be to
|
|
difficult to understand for the participants if not evaluated with e.g. the
|
|
\gls{FRE} or other adequate formulas. Further, if there is previous knowledge
|
|
about the requested participants, the researcher could subconsciously select
|
|
text that is familiar to, or well received by some of the subjects and could
|
|
thereby conceivably influence the outcome of the study\cite{hrob_observer,
|
|
berger_observer}. The same problem arises, if the typing test software already
|
|
provides such texts but the researcher has to select some of them for the
|
|
experiment. Furthermore, the difficulty of the provided texts should be verified
|
|
to ensure accurate results across multiple treatments. A possible solution to
|
|
this problem is crowdsourcing. Howe describes crowdsourcing as the act of
|
|
outsourcing a problem to a group of individuals that are voluntarily working
|
|
together to solve it \parencite[1-11]{howe_crowd_book} \&
|
|
\cite{howe_crowdsource, schenk_crowdsource}.
|
|
|
|
Observer bias can also occur while conducting the experiment when the researcher
|
|
has to give instructions to the subject. Therefore, it is important to treat
|
|
every participant equally by following a predefined procedure and minimize
|
|
unnecessary interaction where possible to further minimize the risk of bias
|
|
\parencite[674]{angrosino_observer}.
|
|
|
|
\begin{phga_sum*}
|
|
Summarizing, even seemingly arbitrary decisions or actions can have a potential
|
|
undesirable impact on the results of a study. If it is possible to implement
|
|
automated checks for the suitability of text e.g., a platform that verifies
|
|
submitted text based on \gls{FRE} scores, crowdsourcing could be used to
|
|
completely exclude the researcher from the text selection process and therefore
|
|
mitigate the risk of unwanted bias. In addition, the aspect of time in the
|
|
preparation phase of a study could be another factor to consider crowdsourcing
|
|
to acquire larger amounts of text with equal difficulty.
|
|
\end{phga_sum*}
|
|
|
|
\subsection{Influence of Actuation Force on Keyboard Use}
|
|
\label{sec:finger_force}
|
|
Section \ref{sec:kb_ks} discussed the differences of various keyswitch
|
|
models. One difference was the applied force, a keyswitch required to
|
|
activate. A study by Akagi tested the differences in performance and preference
|
|
across four visually identical keyboards with different keyswitches. The
|
|
keyswitches differed in actuation force and type. Two keyboards used tactile
|
|
keyswitches with 70.9 g (\gls{KB} A) and 32.5 g (\gls{KB} C) the other two
|
|
linear switches with 70.9 g (\gls{KB} D) and 42.5 g (\gls{KB} B). The (n=24)
|
|
subjects were required to type on each keyboard for 7 to 8 minutes where speed
|
|
and errors were recorded. The results showed, that \gls{KB} D (linear, 70.9 g)
|
|
produced the lowest error rate followed by \gls{KB} A (tactile, 70.9 g),
|
|
\gls{KB} C (linear, 42.5 g) and \gls{KB} B (tactile, 35.5 g). Further, the
|
|
difference in typing speed between the slowest (tactile, 70.9 g) and fastest
|
|
(linear, 42.5 g) keyboard was only 2.61\% and according to Akagi too small to be
|
|
significant in practical use. The study also revealed, that the preference for
|
|
neither of the four keyboards was significantly different
|
|
\cite{akagi_keyswitch}. A follow up survey by Akagi concerning the model of
|
|
keyboard typists would prefer to use in the future revealed, that 69\% of the 81
|
|
participating decided for a newly proposed keyboard with 56.7 g resistance and
|
|
light tactile feedback \cite{akagi_keyswitch}. Further, a study by Loricchio,
|
|
were (n=16) participants typed on two identical keyboard models that only
|
|
differed in actuation force (58 g and 74g), also yielded moderate differences in
|
|
typing speed. The keyboard with lower actuation force was 8.25\% faster and
|
|
preferred by 15 out of the 16 subjects compared to the keyboard featuring
|
|
keyswitches with higher actuation force \cite{loricchio_force_speed}. A study by
|
|
Hoffmann et al. even designed a keyboard that utilized small
|
|
electromagnets―instead of the typically used spring―to dynamically alter the
|
|
resistance of keys to prevent erroneous input by increasing the force required
|
|
to press keys that do not make sense in the current context of a word. This
|
|
design reduced the number of required corrections by 46\% and overall lowered
|
|
typos by 87\% compared to when the force feedback was turned off (n=12)
|
|
\cite{hoffmann_typeright}.
|
|
|
|
\begin{phga_sum*}
|
|
So far, studies concerning keyboards with uniform actuation force yielded
|
|
different results pertaining speed, but agreed that actuation force influences
|
|
the error rate during typing related tasks. To our best knowledge, there are no
|
|
studies that evaluated the effect of non-uniformly distributed actuation forces
|
|
across one keyboard on speed, accuracy, error rate or preference. This is why we
|
|
want to reevaluate the influence of actuation force on speed and determine, if
|
|
keyboards with non-uniform actuation forces have a positive impact on all
|
|
metrics mentioned so far. The next section gives insights, into why such
|
|
keyboards could make sense.
|
|
\end{phga_sum*}
|
|
|
|
\subsection{Strength of Individual Fingers}
|
|
As already mentioned in Section \ref{sec:mech_switch}, the force applied to a
|
|
keyswitch is the concern of multiple studies that evaluate the relation between
|
|
keyboarding and \gls{WRUED}. Further, multiple studies came to the conclusion,
|
|
that there is a significant discrepancy in strength between individual fingers
|
|
\cite{bretz_finger, martin_force, baker_kinematics, dickson_finger}. Bretz et
|
|
al. found, that when participants squeezed an object between thumb and finger,
|
|
differences in applicable force between different fingers ranged from 1.6
|
|
\gls{N} up to 25.9 \gls{N} (n=16) \cite{bretz_finger}. Dickson and Nicolle
|
|
observed the effects of surgery on patients with rheumatoid hands. The pre and
|
|
post surgery force of finger flexion was recorded and the post surgery results
|
|
yielded a difference in flexion force, which is similar to the force required to
|
|
actuate a keyswitch, that ranged from 1 \gls{N} to 4 \gls{N}
|
|
\cite{dickson_finger}. Martin et al. measured applied average and peak force of
|
|
individual digits while typing on a keyboard (n=10). The measured differences
|
|
ranged from 0.10 \gls{N} to 1.49 \gls{N} for peak force and 0.01 \gls{N} to 0.08
|
|
\gls{N} for mean force \cite{martin_force}.
|
|
|
|
\begin{phga_sum*}
|
|
The goal of this thesis is to evaluate the possible advantages of keyboards with
|
|
non-uniform actuation forces. The fairly small difference of only 0.08 \gls{N} in mean
|
|
force applied to keyboards recorded by Martin et al. \cite{martin_force} but
|
|
rather big difference in finger strength measured by Bretz et
|
|
al. \cite{bretz_finger} could indicate, that albeit the difference in strength,
|
|
all fingers have to apply equal force to generate a keypress because of the
|
|
uniform actuation force used in commercially available keyboards.
|
|
\end{phga_sum*}
|
|
|
|
\subsection{Summary}
|
|
\label{sec:lr_sum}
|
|
Keyboards are still the most commonly used input method for data entry to date
|
|
and so far the majority of keyboard users still operates non-alternative
|
|
keyboard designs. Thus, modifications that ideally could be implemented into
|
|
manufacturing processes of existing designs have to be explored, to ensure
|
|
availability and therefore adaption, which could help to reduce the risks of
|
|
\gls{WRUED}. One factor related to \gls{WRUED} is the actuation force of the
|
|
keyswitches \cite{bufton_typingforces, rempel_ergo, rempel_force,
|
|
gerard_keyswitch}. Especially higher actuation forces have shown to be the
|
|
reason for discomfort in the upper extremity. On the other hand, higher
|
|
actuation forces also led to lower error rates while typing and therefore
|
|
enhance user satisfaction and performance \cite{gerard_keyswitch}. Therefore, a
|
|
desirable input method should offer enough resistance to prevent accidental key
|
|
presses but also reduce the stress induced on weaker fingers. With the help of
|
|
several methods to measure typing relate metrics such as muscle activity
|
|
(\gls{EMG}), error rates (\gls{CER} and \gls{UER}), typing speed (\gls{WPM}),
|
|
text readability (\gls{FRE}) and user satisfaction (\gls{UEQ} and \gls{KCQ}) it
|
|
is feasible to evaluate possible alternative input methods to the more
|
|
traditional keyboard. The availability of affordable surface level \gls{EMG}
|
|
measurement devices makes it possible for researchers that are not medically
|
|
trained to conduct non-invasive muscle activity measurements \cite{takala_emg}
|
|
and load cells in combination with micro controllers are a reliable, low-cost
|
|
solution to visualize the strength of different fingers and monitor applied
|
|
forces while typing \cite{gerard_keyswitch, rempel_ergo,
|
|
bufton_typingforces}. Although, the strength of individual fingers has already
|
|
been measured in different studies \cite{bretz_finger, martin_force,
|
|
baker_kinematics, dickson_finger}, to our best knowledge, there are no
|
|
measurements concerning the maximum force each individual finger can apply in
|
|
different positions related to a key on the keyboard. Further, during our
|
|
research we only found one manufacturer of keyboards (Realforce), that already
|
|
offers models with variable actuation force. These keyboards feature two types
|
|
of keys and require less force towards the edges and more force towards the
|
|
middle \cite{realforce_topre}. We therefore try to provide a sensible
|
|
distribution of actuation forces across a non-uniformly equipped keyboard and
|
|
evaluate the possible advantages and disadvantages of such a design to encourage
|
|
other manufacturers to produce similar alternative keyboard designs.
|