Project: Implementing Fitts' Law and Machine Learning for HCI Analysis

This project investigates the application of Fitts' Law in conjunction with machine learning to enhance human-computer interaction (HCI). The core focus is on predicting the speed and time a user takes to interact with a target on a computing device. By leveraging Fitts' Law, which considers target size and distance, the project aims to create predictive models for user movements. The integration of machine learning provides a systematic approach to recording and predicting outcomes based on user actions, such as navigating between targets on a screen. The project explores how these principles can inform user interface design, optimizing the ease and efficiency of movements. Factors like screen size and target characteristics are examined to understand their impact on user interaction speed and overall accuracy. The goal is to define and measure HCI, providing insights into the time taken for users to move between targets and how their speed influences these interactions. The project includes an implementation of a machine learning algorithm, incorporating factors like target size and screen dimensions to enhance accuracy in predicting human interaction with computer interfaces.

ABSTRACT
Fitt’s law is used in the field of computing in collaboration with machine learning which targets
improvements in human computer interaction. Predicative models that are used in the measure and
prediction of human speed while interacting with a computing device can be measured and the outcome
predicted accurately using the law. This project focuses on the use of fitts law and machine learning to
determine the speed and the amount of time a human interacting with a target can make.
Using the law, the amount of time taken to move from one target to another can be determined
by using the size of the target and the distance of the target from the pointer. Fitts’ law as a model can
be used to help designers come up with decisions to improve the designs of user interfaces. The
interface is designed to ease the movements between the target and the origin.
Machine learning incorporation into fitts’ law is used as a generic way to provide a series of steps to
predict and record the outcomes based on the type and the movements of the user from one point to
another.
For instance, if the user is navigating between one point on the screen to another point while
maintaining reference to the distances moved. Since the size of the targets is a constant, the amount of
time can therefore be determined using the law and incorporation of techniques in machine learning.
The main focus of this project is to define human computer interaction and the amount of time taken to
move from one target to another with respect to the speed moved by the user.
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Table of Contents
ABSTRACT................................................................................................................................................i
CHAPTER 1..............................................................................................................................................1
INTRODUCTION............................................................................................................................1
PROJECT SCOPE............................................................................................................................1
MEASURE OF ACCURACY..........................................................................................................2
CHAPTER 2..............................................................................................................................................4
IMPLEMENTATION.......................................................................................................................4
ADJUSTMENT FOR ACCURACY................................................................................................5
CHAPTER 3..............................................................................................................................................7
RESULTS AND DISCUSSION.......................................................................................................7
OPERATION....................................................................................................................................8
ISOLATED TARGETS.....................................................................................................................8
CHAPTER 4............................................................................................................................................12
PYGAME ARCHITECTURE AND FEATURE............................................................................12
PYGAME FEATURES...................................................................................................................13
WORKING OF THE PROJECT....................................................................................................18
DIFFERENCE BETWEEN SMALL AND LARGE SCREEN.....................................................24
CHAPTER 5............................................................................................................................................27
OBSERVATION.............................................................................................................................27
CONCLUSION........................................................................................................................................28
REFERENCES.........................................................................................................................................29
APPENDIX 1...........................................................................................................................................31
APPENDIX 2...........................................................................................................................................32
APPENDIX 3...........................................................................................................................................33
APPENDIX 4...........................................................................................................................................34
APPENDIX 5...........................................................................................................................................35
APPENDIX 6...........................................................................................................................................36
APPENDIX 7...........................................................................................................................................37
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CHAPTER 1
INTRODUCTION
Machine learning is statistical method that is used in data analysis to automate the process of
building models. The models that are used for the analysis of the data are usually automated through
machine learning mechanisms. Machine learning is a built from artificial intelligence and is based on
the idea of data, patterns and decision making (Schmidt, 2000). To identify patterns, the machine
learning systems, learn the data and predict the best outcomes to enable aid in the process of decision
making without the need to involve human being. The process is usually faster if the models are given
a wide range of data to learn. The outcomes are based on the data learnt by the models.
Fitt’s algorithm is model based and is used to predict the outcome of movements made by
human being (MacKenzie, 2018). If a human makes a movement in a rapid motion, fitts law can be
used to predict the movements based on previous moves. Fitt’s law is commonly used in the field of
human computer interaction to provide as a guideline that is used in designing interfaces (Bi et al.,
2013). The way in which human beings interact with computer is based on movements. The speed with
which the user makes the motion can easily be determined using fitts law by making a record of the
previous movements.
The field of human computer interaction can be related to the operations of machine learning.
Machine learning involves training of models to enable determine and predict the outcomes of some
event. The models are provided with some set of data, the models analyze the data, and predicts the
outcome for some event. If the models are highly trained, the outcome contains high levels of accuracy.
PROJECT SCOPE
Human computer interaction and its communication with human agents is determined using
computation. The way in which the computer and the humans interact together can be measured and
determined using an algorithm. The best performance measure is carried out using fitt’s law which
provides ways in which the speed and movements can be traced to provide an efficient way of tracking
the performance of the users.
The project is based on machine learning to determine the level of competency of human being
while interacting with a computer screen (Hassan et al., 2019). The human is given a target in a
computer screen. The speed with which the human interacts with the computer is measured and the
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accuracy is determined using an algorithm based machine learning program. The work flow for the
interaction can be quantified using fitts law which focuses on human interaction with a computer.
The project works on the principles used in fitts law to determine the amount of time and the
speed of a human interacting with a computer screen. Several factor are taken into account while using
the law. Such factors include the width and the screen size (Roig-Maimó et al., 2018). The size of the
screen affects the amount of time the user takes to navigate between the screen. The amount of time to
move from one point to another is greatly reduced if the screen is of a large size and increases with
reduction in the size of the screen (Shneiderman et al., 2016).
The algorithm implemented contains a specific target where the user aims, and the amount of
time taken for each of the respective move is recorded. Computer learning algorithms are modelled on
the basis that they must take in data to enhance the accuracy of prediction and the outcomes. If the
models are not able to learn and take into account the amount of data for learning, the model is likely to
be biased. The measurements for the time and the speed of the pointers are determined by an algorithm.
The algorithm is designed to record the performance in real time.
Some of the factors which affects the operation and the use of the algorithm effectively include
limitation to adjustments in the size and the width of the measuring instruments. For instance, if the
size of the screen in use cannot be adjusted, there is a limitation in used screens of different sizes.
MEASURE OF ACCURACY
The accuracy of time and speed are measured in terms of the interaction of the user with the
targets. If the user misses the target, the values for the time and the speed are not recorded. Accuracy is
a measure of the amount of time spent by the user when hitting a certain target. The best measure of
accuracy can be determined if the user hits the target with minimal time. The amount of time for hitting
the target can be reduced if the size of the screen is reduced and the targets made to rotate at the same
point.
The values of the time can then be analyzed to determine the average amount of time the user
spent hitting the target with different distances for the width and the difference in the speed. If the
speed for hitting the target is high, means that the amount of time taken by the user to hit the target is
reduced. The main aim of the project is to determine the amount of time and the speed of the user if the
user is provided with different targets.
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If the targets are adjusted automatically, the amount of the time taken by the user to adapt to the
changes in the targets can also be determined. The use of fitt’s law is to define the interactions between
the computer and the human which constitutes human computer interaction. The interaction between
the computer and the humans as a field is measured using defined algorithms.
Some of the algorithms are provided with data as an input to enable them have the best
outcomes. If the models are accurate enough, the speed for the user interacting with the computer can
then be measured without the involvement of the user in the operation.
The advantages of using models to measure the amount of time and the speed used to hit the
target is to increase the level of accuracy. Time can be determined as a unit function, the timing
function takes the width and the size of the screen as parameters.
Mapping of the targets can also be an aim to improve the accuracy of the user. The targets can
be mapped in such a way that the distances from one target to another is equidistant such that the user
is able to navigate easily through the targets. Factor which determines the level of accuracy for the user
include the relative mapping of the targets to each other. The mapping improves the level of accuracy
with which the user is able to hit the target with minimal time.
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CHAPTER 2
IMPLEMENTATION
Fitts’ law contains several factors of importance which are used to measure the degree of accuracy.
The factors include the following:
 The time taken to hit the target.
 The distance from the starting point to the center of the target.
 The width of the target.
Fitts law has the limitation that it does not provide prediction based on the performance of the
device that is used. The problem is that there is high rate for errors if the user is using a low performing
input device. The performance of the law can be best measured using high performing devices. The
target size and the screen of the device under test is a factor to be considered while testing the
performance of the law on different devices.
The project is an implementation of a machine learning algorithm that uses fitt’s law to determine a
measure of accuracy for an interaction between the user and a computing device. If the user is made to
hit the targets, then the amount of time taken to hit each of the given targets depends on the distance
from one target to another. If the targets are far away from each other, then the amount of time taken
increases with the distance moved from the target.
If the user travels longer distances while traversing through the screen, the speed of interaction
between the computer and the user is reduced (Yeo et al., 2015). To reduce the distance that the user
has to travel, a screen of proper size is recommended for use.
Incorporation of machine learning into the interaction between the computer and the humans plays a
great role in the improvement of the accuracy and the amount the prediction of the outcomes. The
principles that outline the way in which the prediction of the outcomes relates to the way in which the
models are assigned a set of data. For the models to have a greater level of accuracy then, they must
analyze the data provided. Machine learning plays a major role in the adoption and incorporation into
the fitts law. The mechanisms in which the data provided is laid out depends on the aspect that the
models use. If the amount of time taken to predict the outcomes is more, the speed with which the
models can determine the level of accuracy reduces.
The interaction between machine learning and human computer interaction depends on the
types of target (Amershi et al., 2014). Some of the targets requires some training using some kind of
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models where the models are provided with a set of data. The data is used to determine the next cause
of action whereas some models do not require training and therefore the user is involved manually.
If the user is involved, there must be a target which are in motion to provide different targets to
ensure versatility in recording the values of the outcome.
The type of target involved depends on the user. Sometimes machine independent models are
used and given a certain target.
ADJUSTMENT FOR ACCURACY
An informative technique to improve the accuracy and varying values for the trials can be
determined by using different sets of predefined data. By adjusting the specified width of the target
device the spatial degree of accurate results can be improved (Roig-Maimó et al., 2018). The outcomes
of the models are as a result of different values for the adjustments of the widths for the devices. The
speed of the motion for the input devices varies with the width of the device and the time taken to make
a movement from one point to another within the device.
The throughput and the adjustments for the accuracy are dependent on the accuracy and the
speed of motion. The targets are adjusted at equals lengths and distances to ensure accuracy in the
speed and the timing function used to determine the amount of time taken to hit the target (Bi et al.,
2013). The timing function takes several parameters into account which include speed aimed at
predicting the outcomes effectively.
The adjustments in terms of the width and the size of the screen affect the speed of the of the
pointing device and the amount of time taken to hit the target. If the width is adjusted to a greater size,
then the amount time increases exponentially with the increase in the width.
Accuracy is a measure that the user never misses the target such that the target is successively
hit. Accuracy can be measured in terms of the amount of time taken to successively hit a target. If the
user is first enough to hit the target, the correspondence in the amount of time taken by the model to
analyze and predict the outcomes is equivalently lower.
OVERVIEW
The project is basically a client application that functions depending on the interaction of the
user with the device. The more the interaction between the user and the target, the higher the values in
the correspondence to the results.
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Implementation of other projects which depend on the same principle of the user interacting
with the target. The more the time that the user interacts with the target, the more the accuracy of the
measured results. The accuracy increases with the improvement in the amount of records that the user
is able to make interaction with the target.
The main reason why I implemented this project was to involve the use of human beings in the
process of interacting with computer devices. If the interaction is not based on humans, then the aim of
the project does not correspond to the working and the functionalities of the application.
The main dependencies of the project include, the amount of time taken by the user and the
speed with which the user is able to make interaction with the target.
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CHAPTER 3
RESULTS AND DISCUSSION
For a user interaction with a desktop the mouse has some higher performance based on the
specific interactions with the selected points. If a user is made to target different points on the screen,
with the time and the speed of the user being recorded for every movement. It is identified that the time
taken to move from a screen of smaller size to screen of larger size increases with the increase in the
size of the screen. If the width of the screen is adjusted the user takes more time to move from one
target to another.
The aim of fitt’s law is to describe the time taken to acquire a target using some movements
(Gillies et al., 2016). If the width of the target is measured along the path with which the motion is
taking place, the average amount of time taken can then be estimated by using the width and the time
taken to hit the target.
The time and other constants vary depending on the pointing device, input and the ratio of the
distance and the distance that the stylus or the cursor moves in the screen. To determine the amount of
time taken, an experiment is performed with the width and the size of the screen been varied for each of
the consecutive clicks of the cursor and the stylus.
Rapid movements constitute an increase in the speed and the accuracy which results to an
increase in the ratio of the distance to the width of the screen. This shows that if the distance from a
target is increased by some factor with some greater range on the accuracy, then it is observed that the
width of the screen is reduced which results to an increase in the product of time and the motion in any
of the given directions.
The index of performance can be based on some throughput. Throughput can be defined as the
number of times that the user is able to transmit the movements to a given target regardless of the size
of the screen. The best way to describe fitt’s law is to use a deterministic correlation algorithm which is
used to measure the motion at equals sections and at an equal duration of time.
The expansion of the size of the target is aimed at increasing the amount of time that the user
takes to hit the screen. Each of the sub movements are measured independently to increase the accuracy
with which the targets are hit at equal intervals (Card, 2018). The amount of time taken to hit the target
and the accuracy for hitting the targets can be improved by using adjustments for the values of input
fields for the size and the width. The width affects the speed and the time with which the user hits the
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target (Cruz-Benito et al., 2016). An increase the size results to a decrease in the amount of time and
the speed of moving to the target.
Machine learning is an area that depends on the data set and the and the use of models to predict
and determine the mechanisms that need to be utilized to come up with results.
OPERATION
The user is made to click different targets at the same time. The targets are distant from each
other to ensure that the values of the output recorded are different. Once a hit is made, the user is
provided with a different target located at a different position from the original one (Hassan et al.,
2019.). The targets are marked with red to make them distinguishable from the rest of the environment.
The width of the screen can be adjusted equal intervals by inputting different values in the input
field. Change in the values in the input field changes the width of the screen. The size of the target can
also be changed in the input field provided. Once the values are committed in the input field, the values
changes effectively.
Once a user hits the target, the values of the time are recorded simultaneously for each of
successive hit on the target. The operation and the use of the models depends and relates to the fitts law.
The fitt law is used together with the principles in machine learning to provide outcomes in human and
the interactions between them.
ISOLATED TARGETS
If the targets are isolated the amount of time it takes to move one point to another depends on
the distance of the points. The main aim of expanding the targets is to increase the level of accuracy if
each of the respective movements for are recorded. If there is high demand for an increase in the
measure of accuracy for the input devices, then the movements are slower for each of the respective
movements (Silva et al., 2015). The targets do not need be distinct from each other as they the amount
of time and the speed of the movements for the user depends on the distance travelled by the user
before hitting the target.
If the targets are close enough, this affects the spontaneous movements of the user from one
target to another since, the user moves to the next target with a higher speed which affects the accuracy
of the measurements.
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The targets are equidistant to each other to ensure that the user moves the same distance from
one point to another (Issa and Isaias, 2015). Distance is a measure of the amount of time, that the user
uses to move to different targets.
The measure of the inputs can be determined based on the following factors.
 Position
 Rate
Position
The accuracy of moving the pointer and hitting the target depends on the distance of the pointer
from the target. The larger the distance between the target and the pointer, the higher the amount of
time taken to hit the target. Time increases exponentially with an increase in the distance of the target
from the pointer. If the distance is reduced, the amount of time taken is also reduced. The position is
also a measure for the rate control i.e. the rate at which the pointer hits the target can be controlled by
adjusting the positions. The positions of the targets are adjusted at equals intervals to avoid overlap
and the time taken by the user to hit the target.
Rate
The rate of the pointer is controlled by the position which depends in the speed and the direction
in which the pointer moves in (Shneiderman et al., 2016). relative mapping is the rate at which the
position and the direction of the pointer can be controlled and mapped into a flexible display. Relative
mapping is meant to reduce the amount of time taken to hit the target.
Human computer interaction is the field concerned with how human beings interact with
computers (Shneiderman et al., 2016). Fitt’s law has been extensively being used in human computer
interaction to define and explain how humans interact with computers. Human computer interactions
aims to ensure that humans and computers interact efficiently with each other to provide a user system.
The process consists of computer, humans the interactions between them.
Usability in HCI is an aspect that is triggered to ensure that the interaction between the
computer and the user are done effectively and efficiently and satisfying to the user (Gillies et al.,
2016). HCI is more concerned with provision of an understanding how systems are incorporated into
computation and how the systems can be made more usable (Ren, 2016).
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The project is based on human computer interaction which is used to determine the level of
competency of human being while interacting with a computer screen. The main aim of the project is to
determine the level of accuracy for the mouse movement during interaction with a computer screen
which is based on the fitt’s law case study which is based on computer interaction.
I simply created a project that can be used to measure the amount of time and the speed with
which the users can be able to move from one target to another. The targets are separated at equal
distances and therefore the amount of time for each of the movement and the amount of time taken by
the user to hit the target can be determined. If for instance the user is made to hit one target and the
time is set to zero, then the amount of time is calculated based on the difference between the amount of
time taken to hit the second target from the previous target. All the amounts of time are recorded in a
csv file which can be used for later reference to identify the approximate values.
The speed of the cursor movement from one target to another varies from one user to another.
The project uses fitt’s law as a measure of interaction between the user and the computer screen. Once
the user is able to transition from one target to another, then the amount of time can be well recorded
based on the inputs from the user.
The main concepts discussed in fitt’s law is the interaction of human and a computer. Based on the
concepts I came up with a program which can then be used to measure the amount of time and the
speed with which the humans use to interact with a computer.
The main idea of the program is that, when a user is provided with a target and the user is made
to hit the target with the targets separated at equal distances. Once a user is able to hit one target, the
next move is based on another target. If the user is able to transition between the targets, then the
responsiveness of the user with the interaction to the computer can be measured.
The responsiveness and the interaction can then be measured in terms of the speed and the
amount of time taken by the user. The factors of time and speed depends on the relative distance and
the adjustments of the targets. For instance, the difference between a smaller screen and a bigger
screen. The difference in the outputs between the types of the screens depends on the size and the width
of the computer.
The size of the screen can be adjusted based on the number of pixels that a certain screen can be
able to support. If the size of the screen is large enough, then the responsiveness of the user to the
screen is fast as compared to a smaller screen.
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