% MORE INFO % WRUED: https://www.ccohs.ca/oshanswers/diseases/rmirsi.html \section{Literature Review} In this section, we gathered information about conventional methods, tools and metrics that are used in the domain of keyboard related research. We were particularly interested in how keyboard usage is related to health risks, the status quo of keyboard design, which metrics to use when conducting a typing related experiment and previous studies that evaluated the impact of key actuation force on those metrics. The information collected during the literature review ensured a profound understanding of those topics, which helped us during the design phase of our two preliminary studies and the main study. Additionally, we partially established our hypotheses based on the results of previous research. \subsection{Work Related Upper Extremity Disorders} \label{sec:wrued} \Gls{WRUED} is a term to describe a group of medical conditions related to muscles, tendons and nerves in shoulder, arm, elbow, forearm or hand, such as \gls{CTS}, \gls{RSI}, Tendinitis, \gls{TNS}, etc. Symptoms of \gls{WRUED} are aching, tiredness and fatigue of affected regions that either occur while working or even extend to phases of relaxation. A common way to treat \gls{WRUED} is to avoid the potentially harmful activities that cause discomfort in affected areas \cite{ccfohas_wrued}. Pascarelli and Hsu reported, that out of 485 patients with \gls{WRUED} 17\,\% were computer users \cite{pascarelli_wrued}. Since computers have become an essential part of many jobs in almost any sector of employment, restrictions of computer related activities would result in either reduced productivity or the complete inability to fulfill required tasks, which in the worst case could require a change of profession \cite{ccfohas_wrued}. Potential problems with current keyboard designs and possible solutions are discussed in the following sections. \begin{phga_sum*} \gls{WRUED} are a serious problem of modern society and since there is evidence pointing towards computer related work to be a possible factor for these diseases, it is likely that especially keyboards, as the main input device, are responsible for a portion of people affected by \gls{WRUED}. \end{phga_sum*} \subsection{Keyboards and Keyswitches} \label{sec:kb_ks} \subsubsection{Keyboard Models and Layouts} \label{sec:kb_layout} \begin{figure}[ht] \centering \includegraphics[width=1.0\textwidth]{images/keyboard_models.jpg} \caption{Different keyboards, including alternative split models, smaller form factors and traditional layouts such as ISO/IEC 9995 \cite{iso9995-2} and ANSI-INCITS 154-1988 \cite{ansi-incits-154-1988}} \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. The keyboards feature different enclosures and keycaps, which are the rectangular pieces of plastic on top of the actual keyswitches that sometimes indicate what 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 that define the physical layout of a keyboard―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}. These layouts propose slightly different arrangements of the keys and some even alter the shape of a few keys entirely. Figure \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, tittiranonda_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}. \subsubsection{Membrane Keyswitch} \label{sec:mem_switch} 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 most commonly used ones are scissor switches and rubber dome switches which are both subsets of the membrane switch family. 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}. \subsubsection{Mechanical Keyswitch} \label{sec:mech_switch} 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. However, there are also keyboards with \gls{PCB}s that feature special sockets where the keyswitches can be \gls{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, which should encourage a premature release of the key. An early study by Brunner and Richardson suggested, that this feedback leads to faster typing speed 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 nor 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}. However, 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 sent 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}. \begin{phga_sum*} Since this thesis is focused on 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 (30\,g to 55\,g 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. 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 (30\,g to 150\,g) \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. \end{phga_sum*} \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, baker_ergo}. \subsubsection{Readability of Text} \label{sec:meas_fre} The texts used should be easy to read for typists participating in studies that evaluate their performance and are therefore 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}). This formula was necessary, because all participants were Germans. \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 \small \ra{1.3} \begin{tabular}{?l^c} \toprule \multicolumn{1}{c}{\emph{FRE}}& \emph{Understandability} \\ \midrule \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 \\ \bottomrule \end{tabular} \caption{Categories for different FRE scores to classify the understandability of text \cite{flesch_fre}} \label{tbl:fre_ranges} \end{table} \subsubsection{Performance Metrics} \label{sec:meas_perf} 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 obligated 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} \subsubsection{Electromyography} \label{sec:meas_emg} 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}. \subsubsection{Subjective Metrics} \label{sec:meas_sub} 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 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 too 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, where (n=16) participants typed on two identical keyboard models that only differed in actuation force (58\,g and 74\,g), 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} In addition, 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\footnote{\url{https://www.realforce.co.jp/en/products/}}), 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.