\section{Literature Review}
% To better understand which metrics and methods are meaningful in the domain of keyboards and especially when

% To investigate whether or not solely the actuation force of individual keys can make a difference in terms of efficiency or satisfaction an ....
\subsection{Keyboards and key switches}

\begin{figure}[ht]
  \centering
  \includegraphics[width=1.0\textwidth]{images/keyboard_models.jpg}
  \caption{Different keyboard models}
  \label{fig:keyboard_models}
\end{figure}

Keyboards are well known input devices used to operate a computer. There are a
variety of keyboard types and models available on the market, some of which can
be seen in Figure \ref{fig:keyboard_models}. The obvious difference between
those keyboards in Figure \ref{fig:keyboard_models} is their general
appearance. What we see is mainly the shape of the enclosure and the keycaps,
which are the rectangular pieces of plastic on top of the actual keyswitches
which sometimes indicate which letter, number or symbol, also known as
characters, a keypress should send to the computer. These keycaps are mainly
made out of the two plastics \gls{ABS} and \gls{PBT} which primarily differ in
feel, durability, cost and sound \parencite[8]{bassett_keycap}.

\begin{figure}[ht]
  \centering
  \includegraphics[width=1.0\textwidth]{images/keyboard_layouts.png}
  \caption{The three major physical keyboard layouts all labeled with the
    alphanumeric characters of the most popular layout―\gls{QWERTY}
    \cite{wiki_kb_layouts}}
  \label{fig:keyboard_layouts}
\end{figure}

Nowadays, there are three main standards for the physical layout of keyboards
namely ISO/IEC 9995 \cite{iso9995-2}, ANSI-INCITS 154-1988
\cite{ansi-incits-154-1988} and JIS X 6002-1980 \cite{jis-x-6002-1980}, that
propose slightly different arrangements of the keys and some even alter the
shape of a few keys. Figure TODO\ref{fig:keyboard_layouts} shows the layouts
defined by the three standards mentioned and shows the main differences. In
addition to the physical layout, there are also various layouts concerning the
mapping of the physical key to a character that is displayed by the
computer. Most of the time, the mapping happens on the computer via software and
therefore the choice of layout is not necessarily restricted by the physical
layout of the keyboard but rather a personal preference. As seen in Figure
\ref{fig:keyboard_models}, there are also non standard physical layouts
available which are often designed to improve the posture of the upper extremity
while typing to reduce the risk of injury or even assist in recovering from
previous \gls{WRUED} \cite{ripat_ergo}. Those designs often split the keyboard
in two halves to reduce ulnar deviation and some designs also allow tenting of
the halves or provide a fixed tent which also reduces forearm pronation
\cite{baker_ergo, rempel_ergo}. Besides the exterior design of the keyboard,
there is another part of interest—the keyswitch. This component of a keyboard
actually sends the signal that a key is pressed. There are different types of
keyswitches available to date. The more commonly available ones are scissor
switches and rubber dome switches which are both subsets of the membrane
switches. Scissor switches are often found in keyboards that are integrated into
notebooks while rubber dome switches are mostly used in workplace
keyboards. Both variants use a rubber membrane with small domes underneath each
key. When a key is pressed, the corresponding dome collapses and because the
dome's inner wall is coated with a conductive material, closes an electrical
circuit \cite{ergopedia_keyswitch, peery_3d_keyswitch}. Another type of switches
are mechanical keyswitches. These switches are frequently used in gaming and
high quality workplace keyboards as well as by enthusiast along with prosumers
which build and then sell custom made keyboards to the latter audience
\cite{bassett_keycap, ergopedia_keyswitch}. These keyswitches are composed of
several mechanical parts which can be examined in Figure
\ref{fig:mech_keyswitches_dissas}. The housing is made up of two parts, the
bottom and top shell. The actual mechanism consists of two conductive plates,
which when connected trigger a keypress, a stainless steel spring which defines
how much force has to be applied to the switch to activate it and a stem which
sits on top of the spring and separates the two plates. The shape of the stem,
represented by the enlarged red lines in Figure
\ref{fig:mech_keyswitches_dissas}, defines the haptic feedback produced by the
keyswitch. When pressure is applied to the keycap, which is connected to the
stem, the spring gets contracted and the stem moves downwards and thereby stops
separating the two plates which closes the electrical circuit and sends a
keypress to the computer. After the key is released, the spring pushes the stem
back to its original position \cite{bassett_keycap, peery_3d_keyswitch,
  ergopedia_keyswitch, chen_mech_switch}. Usually, mechanical keyswitches are
directly soldered onto the \gls{PCB} of the keyboard but there are also
keyboards where the \gls{PCB} features special sockets where the keyswitches can
be hot-swapped without soldering at all \cite{gmmk_hot_swap}. It is also
possible to equip an already existing \gls{PCB} with sockets to make it
hot-swappable \cite{te_connect}.

\begin{figure}[ht]
  \centering
  \includegraphics[width=1.0\textwidth]{images/mech_keyswitches_dissas.jpg}
  \caption{Disassembled tactile, clicky and linear mechanical keyswitchs. The
    red lines resemble the shape of the stem which is responsible for the haptic
    feedback and thus, in combination with the strength of the spring, the
    required actuation force}
  \label{fig:mech_keyswitches_dissas}
\end{figure}

Mechanical keyswitches also have three main subcategories. Those categories
primarily define if and how feedback for a keypress is realised:
\begin{enumerate}
  \item \textbf{Tactile Switches} utilize a small bump on the stem to slightly
  increase and then instantly collapse the force required immediately before the
  actual actuation happens \cite{cherry_mx_brown}. This provides the typist with
  a short noticeable haptic feedback and which should encourage a premature
  release of the key. An early study by Brunner and Richardson suggested, that
  this feedback leads to faster typing speeds and a lower error rate in both
  experienced and casual typists (n=24) \cite{brunner_keyswitch}. Contrary, a
  study by Akagi yielded no significant differences in terms of speed and error
  rate between tactile and linear keyswitches and links the variation found in
  error rates to differences in actuation force (n=24)
  \cite{akagi_keyswitch}. Tactile feedback could still assist the typist to
  prevent \gls{bottoming}.
  \item \textbf{Tactile and audible Switches (Clicky)} separate the stem into
  two parts, the lower part also features a small bump to provide tactile
  feedback and is also responsible for a distinct click sound when the actuation
  happens \cite{cherry_mx_blue}. Gerard et al. noted, that in their study
  (n=24), keyboards with audible feedback increased typing speed and decreased
  typing force. This improvement could have been due to the previous experience
  of participants with keyboards of similar model and keyswitch characteristic
  \cite{gerard_keyswitch}.
  \item \textbf{Linear Switches} do not offer a distinct feedback for the
  typist. The activation of the keyswitch just happens after approximately half
  the total travel distance \cite{cherry_mx_red}. The only tactile feedback that
  could happen is the impact of \gls{bottoming}, but with enough practice,
  typist can develop a lighter touch which reduces overall typing force and
  therefore reduces the risk of \gls{WRUED} \cite{gerard_keyswitch,
    peery_3d_keyswitch, fagarasanu_force_training}.

\end{enumerate}
The corresponding force-displacement curves for one exemplary keyswitch of each
category by the manufacturer Cherry are shown in Figure
\ref{fig:ks_fd_curves}. The Operational position indicates the activation of the
keyswitch.

\begin{figure}[ht]
  \centering
  \includegraphics[width=1.0\textwidth]{images/ks_fd_curves.jpg}
  \caption{Actuation graphs for Cherry MX BROWN \cite{cherry_mx_brown} | BLUE
    \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}
  \label{fig:ks_fd_curves}
\end{figure}


All types of keyswitches mentioned so far are available in a myriad of actuation
forces. Actuation force, also sometimes referred to as make force, is the force
required to activate the keyswitch \cite{radwin_keyswitch,
  ergopedia_keyswitch}. That means depending on the mechanism used, activation
describes the closing of an electrical circuit which forwards a signal, that is
then processed by a controller inside of the keyboard and finally send to the
computer. The computer then selects the corresponding character depending on the
layout used by the user. Previous studies have shown, that actuation force has
an impact on error rate, subjective discomfort, muscle activity and force
applied by the typist \cite{akagi_keyswitch, gerard_keyswitch,
  hoffmann_typeright} and as suggested by Loricchio, has a moderate impact on
typing speed, which could be more significant with greater variation of
actuation force across tested keyboards \cite{loricchio_force_speed}.


\subsubsection{Relevance for this thesis}
Since this thesis is focused around keyboards and especially the relation
between the actuation force of the keyswitch and efficiency (speed, error rate)
and also the differences in satisfaction while using keyswitches with varying
actuation forces, it was important to evaluate different options of keyswitches
that could be used to equip the keyboards used in the experiment. The literature
suggested, that the most common switch types used in the broader population are
rubber dome and scissor switches \cite{ergopedia_keyswitch,
  peery_3d_keyswitch}. Naturally, those keyswitches should also be used in the
study, but one major problem due to the design of those keyswitches arises. It
is not easily possible to alter the actuation force of individual keyswitches
\cite{peery_3d_keyswitch}. This will be necessary to create a keyboard where
each key should have an adjusted actuation force depending on the finger that
normally operates it. It should be mentioned, that it is theoretically possible
to exchange individual rubber dome switches on some keyboards, e.g. keyboards
with \gls{Topre} switches, but the lacking availability of compatible keyboards
and especially the limited selection of actuation forces (30g to 55g for
\gls{Topre} \cite{realforce_topre}) makes this not a viable option for this
thesis \cite{keychatter_topre}. Therefore, we decided to use mechanical
keyswitches for our experiment, because these keyswitches are broadly available
in a variety of actuation forces and because the spring which mainly defines the
actuation force can be easily replaced with any other compatible spring on the
market, the selection of actuation forces is much more appropriate for our use
case (30g to 150g) \cite{peery_3d_keyswitch}. We also decided to use linear
switches because they closest resemble the feedback of the more wide spread
rubber dome switches. Further, linear switches do not introduce additional
factors beside the actuation force to the experiment. In addition, based on the
previous research we settled on using a keyboard model with hot-swapping
capabilities for our experiment to reduce the effort required to equip each
keyboard with the required keyswitches and in case a keyswitch fails during
the experiment, decrease the time required to replace the faulty switch.

\subsection{Measurement of typing related metrics}
\label{sec:metrics}
Nowadays, a common way to compare different methods concerning alphanumeric
input in terms of efficiency is to use one of many typing test or word
processing applications which are commercially available. Depending on the
software used and the experimental setup, users have to input different kinds of
text, either for a predefined time or the time is measured till the whole text
is transcribed \cite{chen_typing_test, hoffmann_typeright,
  fagarasanu_force_training, akagi_keyswitch, kim_typingforces,
  pereira_typing_test}. Text used should be easy to read for typists
participating in studies that evaluate their performance and are therefore is
chosen based on a metric called the \gls{FRE} which indicates the
understandability of text \cite{fagarasanu_force_training,
  kim_typingforces, flesch_fre}. The score ranges from 0 which implies very poor reading
ease to 100 suggesting that the style of writing used causes the text to be very
easy to comprehend \cite{flesch_fre}. Immel proposed an adjusted formula of the
\gls{FRE} that is suitable for German text \cite{immel_fre} and can be seen in
(\ref{eq:fre_german}).

\begin{equation}\label{eq:fre_german}
  FRE_{deutsch} = 180 - \underbrace{ASL}_{\mathclap{\text{Average Sentence Length}}} - (58,5 * \overbrace{ASW}^{\mathclap{\text{Average Syllables per Word}}})
\end{equation}

According to Flesch, the values retrieved by applying the formula to text can be
classified according to the ranges given in Table \ref{tbl:fre_ranges} \cite{flesch_fre}.
\begin{table}

  \centering
  \caption{Categories for different FRE scores to classify the understandability
    of text \cite{flesch_fre}}
  \label{tbl:fre_ranges}
  \begin{tabular}{l|c}
    \hline\hline
    \multicolumn{1}{c|}{FRE}      & Understandability  \\
    \hline
    \multicolumn{1}{c|}{0 - 30}   & Very difficult     \\
    30 - 50                       & Difficult          \\
    50 - 60                       & Fairly difficult   \\
    60 - 70                       & Standard           \\
    70 - 80                       & Fairly easy        \\
    80 - 90                       & Easy               \\
    \multicolumn{1}{r|}{90 - 100} & Very easy          \\
    \hline
  \end{tabular}
\end{table}

There are several metrics to measure the performance of typists. Typical methods
to measure speed are
\begin{enumerate}
  \item \textbf{\Gls{WPM}}
  \begin{equation}\label{eq:wpm}
    WPM = \frac{|T| - 1}{S} * 60 * \frac{1}{5}
  \end{equation}
  In Eq. (\ref{eq:wpm}), $|T|$ is the length of the transcribed text, $S$ the
  time in seconds taken to transcribe $T$, $\frac{1}{5}$ the average word length
  and $60$ the conversion to minutes. $|T| - 1$ counteracts the first input
  which starts the timer in many typing tests \cite{mackenzie_metrics}.
  \item \textbf{\Gls{AdjWPM}} is especially useful if participants are allowed to
  make mistakes and at the same time not forced to correct them. This method adds
  an adjustable factor to lower the \gls{WPM} proportionally to the uncorrected
  error rate $UER := [0;1]$ defined in Eq. (\ref{eq:uer}). The exponent $a$ in
  Eq. (\ref{eq:cwpm}) can be chosen depending on the desired degree of correction
  \cite{mackenzie_metrics}.
  \begin{equation}\label{eq:cwpm}
    AdjWPM = WPM * (1 - UER)^{a}
  \end{equation}
  \item \textbf{\Gls{KSPS}} measures the raw input rate of a typist by capturing
  the whole input stream including backspaces and deleted characters ($IS$)
  \cite{mackenzie_metrics}.

  \begin{equation}\label{eq:ksps}
    KSPS = \frac{|IS| - 1}{S}
  \end{equation}
\end{enumerate}

In addition to speed, the error rate of typists can be measured with the
following two methods

\begin{enumerate}
  \item \textbf{\gls{CER}} is the ratio of erroneous input that got fixed
  ($IF$) to any character typed during transcription, including $IF$
  \cite{soukoreff_metrics}.
  \begin{equation}\label{eq:cer}
    CER = \frac{|IF|}{|T| + |IF|}
  \end{equation}

  \item \textbf{\gls{UER}} is the ratio of erroneous input that was \textbf{not}
  fixed ($INF$) to any character typed during transcription, including $IF$
  \cite{soukoreff_metrics}.
  \begin{equation}\label{eq:uer}
    UER = \frac{|INF|}{|T| + |IF|}
  \end{equation}
\end{enumerate}

In several other studies, in addition to the metrics mentioned so far, \gls{EMG}
data was captured to evaluate the muscle activity or applied force while typing
on completely different or modified hardware \cite{kim_typingforces,
  fagarasanu_force_training, gerard_audio_force, gerard_keyswitch, martin_force,
  rose_force, rempel_ergo, pereira_typing_test}. \gls{EMG} signals, are captured
with the help of specialized equipment that utilize electrodes which are either
placed onto the skin above the muscles of interest (non-invasive) or inserted
directly into the muscle (invasive). The disadvantage of non-invasive surface
level electrodes is the lacking capability to capture the distinct signal of one
isolated muscle \cite{reaz_emg}. Nevertheless, because this type of electrode is
more likely to find acceptance among participants and is also easier to apply by
non-medically trained researchers, it finds wide adoption among studies
\cite{takala_emg}. To make \gls{EMG} data comparable across subjects, it is
necessary to conduct initial measurements where each individual participant is
instructed to first completely relax and then fully contract (\gls{MVC}) the
muscles of interest. These values are used to normalize further data obtained in
an experimental setting. The mean signal yielded by complete relaxation is
subtracted to reduce noise and the \gls{MVC} is used to obtain the individuals
percentage of muscle activity (\%MVC or EMG\%) during tests \cite{halaki_emg,
  takala_emg, rempel_ergo}. Muscles typically measured during typing exercises
are the \gls{FDS}, \gls{FDP} and \gls{ED}. The main function of the \gls{FDS}
and \gls{FDP} is the flexion of the medial four digits, while the \gls{ED}
mainly extends the medial four digits. Therefore, these muscles are primarily
involved in the finger movements required for typing on a keyboard
\cite{netter_anatomy, kim_typingforces, gerard_keyswitch, gerard_audio_force}.
A method frequently used to measure applied force is to place one or multiple
load cells under the keyboard \cite{gerard_keyswitch, rempel_ergo,
  bufton_typingforces}. Load cells are electronic components that are able to
convert applied force to an electrical signal. This signal usually gets
amplified by specialized circuits and then further processed by a micro
controller, computer or other hardware \cite{johnson_loadcell}.

Lastly, subjective metrics e.g., comfort, usability, user experience, fatigue
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 survey 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}.

\subsubsection{Relevance for this thesis}
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}.


\subsection{Crowdsourcing / Observer Bias}
As shown by the previous research 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}. 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 \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. Further, the
difficulty of the provided texts should be verified to ensure accurate results
across multiple treatments. A possible solution for this problem is
crowdsourcing.

Howe CONTINUE


\cite{howe_crowdsource}. If there are automated checks for text
difficulty in place, this method completely excludes the researcher from the
text selection process.


\subsubsection{Relevance for this thesis}

% \subsection{Keyboard usage}
% \subsection{Finger strength}
% \subsection{Traditional methods}
% \subsection{Alternative methodology}
% - Available Methods (Impact vs load)
% - Load cells