1994 Afstudeerverslag IPO

t(i3 TECHNISCHE UNIVERSITEIT EINDHOVEN
Faculteit Wiskunde & Informatica
AFSTUDEERVERSLAG
Tactile Fields and
Target Acquisition
in the User Interface
door
Guido Leenders
augustus 1994
Afstudeerdocent dr. L.J.A.M. Somers
Technische Universiteit Eindhoven
Begeleider M.Sc. D.V. Keyson
Instituut voor Perceptie Onderzoek

Abstract
The research discussed in this thesis was aimed at the extension, both in width and depth, of the
knowledge on tactile feedback as an information channel for user interfaces. A trackball was used
as a research tool. This trackball had been extended by an electrical motor on each axis as a mean
of transporting tactile information. Three areas were studied: modelling the tactile feedback as
produced by the input device, effects of tactile target forms and force levels in target acquisition,
and effects of an interfering target, visual workload and relation between input device movement
and displayed movement (DC-gain).
Tactile fields were modelled based on gravity and friction functions. Results from experiments
indicated that the addition of tactile feedback can decrease time for target acquisition tasks of
approximately 900 ms by 150 ms, dependent on tactile type and strength. This gain is composed
of decreases in both reaction time and movement time towards the target. Reaction time seems
to have decreased through a more simple relation between stimulus and response, whereas the
decrease in movement time for tactile feedback was contributed to the awareness of subjects that
tactile feedback would catch the pointer inside the target. The performance improvement for tactile
feedback in time for target acquisition was found to be reduced by the presence of an interfering
target and increased visual workload. The performance improvement by the introduction into a
visual target acquisition task with constant DC-gain of tactile feedback and variances in DC-gain,
based upon the muscular effort associated with the tactile feedback, was shown to be independent
of the employed fixed DC-gain.
Keywords: tactile feedback, navigation, user interface, models, target acquisition, DC-gain, con-
textual DC-gain, interfering targets, workload.

Contents
1 Introduction
1.1 Organisation ............... .
1.2 Available Hardware and Knowledge Base
1.3 Problems and Approaches . . . . . . . . .
2 Hardware Description
2.1 IPO-trackball ....
2.2 Force Measurement Device
3 Software Description
3.1 Introduction . . . . . . . . . . . . . . . . .
3.2 Limitations of OOP with Borland Pascal .
3.3 Modules . . . . . . . . . . . . . . . . . . .
3.4 User Interface Class Hierarchy Motivation
4 Models for Tactile Fields
4.1 Introduction .....
4.2 Literature Overview
4.3 General Model . .
4.4 Subspaces . . . . .
4.5 Desktop Subspace
4.6 Heights . . . . . .
4.7 Static Graphical Subspace Representation
4.8 Negative Friction
4.9 Conclusions ................. .
5 Performance Effects of Type of Tactile Feedback
5.2 Literature Overview . . . . . .
5.3 Field Study . . . . . . . . . . .
5.4 Description of the Experiment .
5.5 Data Collection .
5.6 Results . . .
5.7 Discussion .
5.8 Conclusions
6 DC-gain, Interfering Targets and Visual Workload
6.2 Literature Overview ..... .
6.3 Goals ............. .
6.4 Description of the Experiment .
6.5 Data Collection .
6.6 Results . . . . . . . . . . . . . .
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II CONTENTS
6.7 Discussion . . 52
6.8 Conclusions 54
References 57
A Tactile Fields 61
A.l Constants 61
A.2 Functions 62
B Analysis of Variance 65
B.l Introduction . 65
B.2 Definition .. 65
B.3 Notation ... 66
B.4 Requirements 66
c Source code 67
C.l Expl.pas 67
C.2 Exp2.pas 70
C.3 LihglO.pas . 77
C.4 LibvarlO.pas. 79
C.5 LibuilO.pas 81
C.6 Convgraf.pas 86

Preface
This report describes my graduate project at the Institute for Perception ResearchfiPO ('Stich-
ting Instituut voor Perceptie Onderzoek'). The IPO constitutes a cooperation between Eindhoven
University of Technology (BUT) and Philips Research Laboratories, Eindhoven. The initial as-
signment was to develop and test an application for a trackball with contextual tactile feedback,
developed at the IPO. This trackball can influence the movements of the ball by means of two
electrical motors to inform the user of events.
However, soon after the start of this project it became clear that this project was not feasible,
unless some preparatory studies were completed. During my time at the IPO two experiments
were conducted to consider in depth the performance implications of the application of tactile
feedback in target acquisition tasks.
In chapter 1 an introduction and some background is given. Chapter 2 and 3 discuss the
hardware and software used for the experiments. Chapter 4 provides a mathematical model for
describing and implementing tactile feedback. This model is used to model the tactile feedback
tested with the experiments described in chapters 5 and 6. These experiments tested the perfor-
mance effects of various types of tactile feedback and various aspects of user interfaces, such as the
presence of an interfering target. The appendices give a mathematical description of the tactile
fields tested, an introduction to analysis of variance and the source code to the programs used to
run the experiments.
I would like to thank the IPO and BUT for this great opportunity to merge computer-science,
experimental psychology and human factors into one synergetic approach towards user interfaces
and input devices. This thesis could not have been written without the continuous support of
David Keyson and Lou Somers. Several other people supported the work in various fashions:
Don Bouwhuis, who reviewed my complete thesis; Cynthia Grover, who enthousiasticly reviewed
the second experiment; Aad Houtsma, who advised me on the collection and interpretation of
subjective measures; Don Bouwhuis, who also advised me on the complete design of the second
experiment and especially on the design of the visual search task; Teddy McCalley, who reviewed
the discussion and conclusions sections; Scott MacKenzie, who advised me on applications of Fitts'
law; Jim Juola, who advised me on the visual search task of the second experiment; Bob Solso,
who reviewed the design of the second experiment; Rudi van Hoe from whom I learnt more about
statistics than I ever knew before; Rudi van der Made and Paul Beerkens with whom I discussed my
experimental designs from an engineering view; Jane Boulton, who advised me for the explanation
of an unexpected trend; Marielle Leenders, who advised me on the force measurement method,
and Tanja Middelkoop who gave the necessary support at the home-front.
Guido Leenders, August 1994
III

Chapter 1
Introduction
In this chapter a short introduction to the research on tactile feedback will be given. Tactile
feedback is a process by which information about the results of an action are communicated
through the tactile senses. The tactile senses are located in the skin and contain receptors for
vibration and pressure on the skin (Krueger, 1982). Common examples of tactile feedback include a
felt click in switches and the feeling of a door handle after the hand was laid on it. Tactile feedback
is often accompanied by proprioceptive feedback, which communicates the position of the body
in space, based on receptors in muscles, tendons, joints and the vestibular system. Sometimes
a differentiation is made between two types of touch perception: haptic and tactile perception.
Haptic perception refers to exploratory touching objects, whereas tactile perceptions is caused by
objects moving along touch senses, which are held at a fixed position.
In the first two sections the institute and the available hardware-base for tactile research inside
the institute are discussed. In the third section the problems and the approaches are stated. No
theoretical background is given in this chapter. Each major topic in this thesis includes a separate
literature overview where all theoretical backgrounds, necessary to understand the topic on hand,
are discussed.
1.1 Organisation
The foundation Institute for Perception Research/IPO ('Stichting Instituut voor Perceptie On-
derzoek') constitutes since 1957 a cooperation between Eindhoven University of Technology and
Philips Research Laboratories, Eindhoven. Within the Research Laboratories, the IPO forms part
of the Information & Software Technology Division. On the EUT side, the institute resides under
the Perception Studies Department of the Faculty of Philosophy and Social Sciences. Around 100
people work at the IPO.
In general IPO research is concerned with sensory and cognitive information processing and
communication by humans interacting with flexible information systems. There are six (overlap-
ping) main streams in IPO research: hearing and speech, vision, cognition and communication,
language, information ergonomics and communication resources. The first four streams are dis-
cipline groups. They study questions derived from gaps in existing knowledge. Their aim is to
develop and broaden theories. The last two streams apply knowledge from the discipline groups to
questions from practical fields and consider possible applications for existing know-how. Research
on tactile feedback is conducted inside the cognition and communication stream.
1.2 Available Hardware and Knowledge Base
The IPO has made available three PC-based systems for tactile research. Two PCs are each
connected to a two-dimensional trackball with force feedback and one PC is connected to an one-
dimensional turning-knob with force feedback for research on movement-prediction. The trackball
1

2 CHAPTER 1. INTRODUCTION
Figure 1.1: The trackball with contextual force feedback. A slightly modified version of the
depicted trackball was used for the experiments.
(depicted in figure 1.1) is built of standard components, except that for force feedback two electro-
motors have been attached along the x- and y-axis. These electro-motors can influence the actions
of the user. For example, a user might experience a dip when the pointer passes an icon in a
graphical user interface. The turning-knob gives force feedback by a motor, attached on the knob
axis.
The main goal of the research on the tactile senses is to study the influence of tactile feedback on
user interface navigation. User interface navigation consists of low level aspects, such as pointer
movement, and high level aspects, such as an internal model of the interface's workings. Two
research themes are currently being addressed (Keyson, 1994):
• How can movements in the user interface be assisted efficiently by tactile feedback during one
or more tasks?
• How can tactile information be used to build a spatial and contextual understanding of the
workspace?
1.3 Problems and Approaches
The research, described in this thesis, tackled three issues to advance research involving the IPO-
trackball. The issues were addressed in the following order:
Design of models: A model was designed to simplify communication and reproduction of all
types of tactile feedback that the IPO-trackball can generate. Two models were developed.
The general model captured all possible types of tactile feedback by enumeration over the
mechanical attributes of the IPO-trackball. The subspace model simplified design and com-
munication further, while being able to express only part of the types of tactile feedback that
can be described by the general model.
Performance eff~c;ds of different types of tactile feedback: It was determined whether
different types of tactile feedback have a different influence on performance in target acquisi-
tion tasks. A target acquisition task is a task where the user has to select items on the screen
(such as icons). The influences of both strength and shape of tactile feedback on objective
performance and user satisfaction were investigated. This was accomplished by an experiment
which took the shape of a target acquisition task.
Performance effects of DC-gain, interfering targets and visual workload on tactile
and visual performance: The relation between motoric and displayed movement (DC-
gain), the presence of an interfering target and visual workload were considered as potential

1.3. PROBLEMS AND APPROACHES 3
candidates, which might cause invalidation of experimental results for application in user
interfaces. The presence and size of these effects in a target acquisition task were studied for
the visual-only condition, the combined tactile/visual condition and their interaction.

Chapter 2
Hardware Description
2.1 IPO-trackball
The complete hardware environment used to develop and run applications with the IPO-trackball
consists of the following components {depicted in figure 2.1):
• a PC,
• a RTI 815 I/O-card,
• a Quadrature I/O-card,
• an amplifier and
• an IPO-trackball.
The PC is an off-the-shelf PC with !SA-bus, including VGA-card and colour monitor. Two
I/O-cards have been added to enable two-way communication with the trackball. A RTI 815
I/O-card is included to convert the digital motor currents into the appropriate analog equivalents
for both x and y direction. Another function of this card is to transport the status of the button.
The button is located at the bottom-left of the cover, making the system only applicable for right-
handed users. The (low power) analog motor current from the RTI card is fed to an amplifier,
whose output is connected to the motors located along the x- andy-axis of the trackball (a detailed
picture is shown in figure 2.2). Two wheels with rubber rings transport the motor movement to
the ball. Changes in the position of the ball are sensed by two optical sensors, located on the shaft
of the motors. These sensors have a resolution of approximately 1060 dpi (dots per inch).
An alternative design is available, using two separate optical sensors instead of the support
wheels. This design decreases the device's sensitivity for slip between the driving shaft and the
trackball. The alternative design uses also a Teflon surface to reduce the effect of irregularities in
the movement, caused by the bearing which is underneath the ball in the used design. However,
both the static and dynamic friction (respectively, friction to overcome when starting a movement
and friction felt during movement) are drastically larger for the alternative design. The alternative
design was not used for the research described in this thesis since the profits of low friction were
considered more important than the disadvantages of increased slip. Only a low friction level
enables ballistic (throwing) movements of the ball.
The optical sensors generate a number of cycles proportional to the size of trackball move-
ments. These cycles, indicating relative movements, are integrated into 24-bit absolute position
coordinates by the Quadrature I/O-card. The current position can be read by the CPU at any
time. This mechanism does not require interrupt-handlers, thereby eliminating disturbances in
the real-time behaviour of the system.
For each motor a. feed-forward circuit is implemented within the amplifier-casing to reduce
the induction current from hand-induced ballmovements which increase the experienced friction
5

6
position x y
'
(digital)
PC
buttonstatus
(digital)
motorcurrents x, y
(digital)
CHAPTER 2. HARDWARE DESCRIPTION
position changes x, y
Quadrature
I/O-card
RTI &15
UO-card
motorcurrents x, y
(analog)
(digital)
buttonstatus
(digital)
Amplifier
Trackball
motorcurrents x, y
(analog)
Figure 2.1: The components of the system used to develop and run applications with the IPO-
trackball.
rubber ring
motor
suppon wheel
button
Figure 2.2: Detailed picture of the trackball.

2.2. FORCE MEASUREMENT DEVICE 7
Newton-meter
force
Figure 2.3: A device to measure the force on the surface of the trackball.
when moving the ball. These circuits can be adjusted individually. Ideally, these feed-forward
circuits will eliminate the induction current completely (Moolhuysen, 1991). However, the current
design only allows for partial compensation, since total compensation at low ball speeds creates
overcompensation ("stampede") at high ball-velocities.
2.2 Force Measurement Device
To measure the force on the surface of the trackball a force measurement device has been designed
(depicted in figure 2.3). It consists of a precision Newton-meter and a small iron frame, attached
to the trackball-device and the Newton-meter. A special ball with a small hole is required to
perform the measurements. It can only be used offline, i.e. when nobody is interacting with the
trackbalL
Before this device was built, the actual force on the surface of the ball was unknown. It
was not possible to calculate the force from the few known constants of the input-device since
documentation was lacking and non-linear effects occurred. Two important reasons for the actual
force to be measured were:
• reproduction of tactile feedback between experiments and
• communication of findings on tactile feedback towards people without access to the IPO-
trackball.
A method was developed to derive a formula for the force, generated by the motors, on the surface
of the ball, given the digital output force. This method requires a large number of measurements
with this device.
The method assumes a linear relationship between the force on the ball and the digital output.
This assumption has been verified by analysis of the measurements, indicating a reasonable fit
of the measurements to a linear function with a correlation coefficient of 94.6% and significance
smaller than 0.01%. However, the size of systematic errors remains unknown and should be
studied. The method consists of the following steps for the motors on both axes:

8 CHAPTER 2. HARDWARE DESCRIPTION
pin
Figure 2.4: Position of the pin before a measurement.
Foroe (mN}
550.
500
450
400
350
300
250.
200
150
100
50
0
I I I
0 50 100 150 200 250 300 350 400 450 500 550
Digital output (-)
Figure 2.5: Plot of a possible table of measurement results.
• Before attaching the force measurement device to the trackball and replacing the ball, the
static friction ko along the axis is measured. ko is measured as the average digital output
value at which the ball starts to roll. k0 is reduced by 20 to obtain a safely low approximation,
resulting in k1 .
• Next, the device is attached to the device and the ball is replaced by the ball with hole. For
several digital output values several measurements each are made.
• At the start of each measurement a null value is output to the aropliaer. The ball is then
rotated till the iron pin barely touches the edge of the hole on the opposite side as the
movement ·will be directed at (figure 2.4). Next, a known value d, increased by k1, is output.
After two seconds, the known value d and the value f on the Newton meter are registered.
• From the final table of tuples (d, f) (an example is shown in figure 2.5), all entries with
f 0 are eliminated. Otherwise, these items will influence the fitting of the table to a linear
function.
• This table is then matched to a linear function f = r * (d - k2 ) using linear regression.
Generally, the measured static friction k2 is larger than k0 . This increase in static friction is
caused by the addition of the force measurement device.

2.2. FORCE MEASUREMENT DEVICE 9
• The function is then translated along the x-axis by -20 - k2 to obtain a new function. This
relation describes ball force in mN as a function of digital output value, relative to kt =ko-20.
The difference between dynamic and static friction is neglected in this method. A necessary
and sufficient assumption is that dynamic friction is equal to a constant times the static friction.
Replication is achieved by measuring the static friction k1 of the IPO-trackball when starting an
application and applying the mentioned relation. Correct replication is guaranteed since the usage
of a different reference point than k1 during measurements and the running of applications results
in an equal force on the ball.
However, communication might be hindered, since the actually experienced forces might be
higher when in motion. Lacking knowledge, this calls for further study. Given the assumption, all
forces actually experienced are a constant larger than the forces based on a static friction reference
point. In the forthcoming, communication of force levels will be based on a static friction reference
point.

10 CHAPTER 2. HARDWARE DESCRIPTION

Chapter 3
Software Description
3.1 Introduction
Several researchers (Moolhuysen, 1991; Goossens, 1992; Keyson & Houtsma, 1994) worked with
the hardware setup described in the previous chapter. The software development took place using
the Borland Pascal development environment (Borland, 1992) under MS-Dos. These researchers
developed or bought several software modules. They applied an object oriented approach (for
an introduction into object oriented programming refer to (Robson, 1981; Meyer, 1988; Meyer,
1992; Cox, 1986)), but the degree of adaptation towards the concept of OOP varied. The same
development environment was used for the work described in this thesis.
The development of experiments takes a magnitude more of iterations over the development-
phases than conventional software, since a complete functional specification has to be found by
testing. Conventional methods, such as the waterfall-method, do not excel in support for such a
development-trajectory. Instead, a less structured method has been applied, consisting of three
stages/documents:
• a short requirements document, containing the hypothesis to be tested,
• a precise description in natural language of the experimental setup and
• an implementation conforming to the description.
To increase ease of adaptation of the implementations towards updated requirements, a strict
coding scheme, requiring modular programming, and strict usage of the key principle "avoid du-
plication of constants" were combined with au OOP (object oriented programming) approach.
An effort was made to combine the potential benefits of OOP with the limitations of the im-
plementation of this concept in Borland Pascal. These limitations will be discussed in the next
section.
Historically, the software was divided over several modules (depicted in figure 3.1}. Several
elements of these modules are redundant. However, the modules have not been revised since all
future development wilJ take place in a C++ environment. This decision was made because of
• the advantages of C++ over Borland Pascal for the development of object-oriented software
and
• the higher speed of C++ executables.
For the design and evaluation of the experiments described herein, several new modules and
object-definitions have been added on top of this set of modules. All new modules have been
named 'LIBname'. In section 3.3, the relevant parts of the set of modules and the objects they
define will be discussed. The source code is listed in appendix C.
11

12 CHAPTER 3. SOFTWARE DESCRIPTION
Experiment
I
I I I
LIBVAR LIBG LIBUI
I
I I
Legenda l!~;:,j
INP_DEV3
D newmodule
"'
D oldmodule
[J bought module
Figure 3.1: New and old modules used for the development of the experimental software.
3.2 Limitations of OOP with Borland Pascal
Borland Pascal and its predecessor, Turbo Pascal with Objects, are not particularly well suited for
OOP programming, as was already motivated by Leenders et al. (1992). The prime concepts of
OOP, encapsulation and inheritance, are hindered by several limitations of Borland Pascal. C++,
another commercially available language, designed by Stroustrup (1986), places less limitations
on OOP programming. Since both have a large installed base, the limitations of Borland Pascal
over C++ will be discussed.
Some might argue that an OOP approach can not be hindered by the choice of implementation
language, since the design is independent of programming language. Even when a language must be
used which only implements part of the necessary support for OOP, it is beneficial to use an object-
oriented design. However, the program code is the ultimate embodiment of the specification, so
the way in which it is written is important for maintainability and extensibility. It requires greater
care and discipline to preserve the object-oriented structure of the program when the language
has only small or no support for OOP. Also, the language does not support the programmer in
finding violations (Rumbaugh et al., 1991). The following disadvantages can be noticed for the
implementation of an OOP design when considering the limitations of Borland Pascal, compared
to C++:
• No overloading of operators: operators such as'+' and '>'can not be assigned new functiona-
lity when applied to classes such as matrices or complex numbers. This leads to the addition
of methods to these classes, hindering readable functional programming. An expression on
complex numbers, such as
would have to be coded in Borland Pascal as
cl.multiply(c2.im).

3.3. MODULES 13
Even more restrictive is the lack of possibilities for overloading when operations such as
writing to streams are considered. To write a complex number and a string to a stream, C++
employs a construct such as
stream << c1 << sl
with the << operator representing the output of a type on a stream. However, the same
functionality can only be achieved in Borland Pascal by:
cl.write(stream);
sl.write(stream);
or
stream.write(cl.string_representation).write(sl.string_representation)
• No automatic conversion between classes: Borland Pascal offers no functionality to enable
automatic conversion between new classes. The C++ expression
rl.Im(cl)
with rl a real and c1 a complex number would be coded in Borland Pascal as
ReaLTo_Complex(rl).multiply(cl.im).
• No multiple inheritance: Pascal offers no functionality to easily combine a class for linked
lists with a class for complex numbers into a class for linked lists of complex numbers.
• No automatic initialisation and destruction when coming into focus: objects within Borland
Pascal need to be initialised and destroyed manually. Neglecting to do so can be the cause of
irritating and hard to find bugs and memory leaks.
Of course is C++ not a complete implementation of the OOP concept. For example, it lacks
aspects such as garbage collection, class variables and passivation/activation (dumping and re-
trieving objects to files) which can be found, for example, in Eiffel. A practical study of the
OOP approach in several high level languages, including C++, Eiffel, Turbo Pascal and Ada, is
discussed by Floyd (1993).
3.3 Modules
The software is distributed among several modules. The classes defined by these modules are
depicted using the Object Modelling Technique (OMT}. In OMT, classes are represented by boxes.
Lines represent relations between classes. The class name, its (derived) attributes and methods
are listed in the box. A complete description of this method is given by Rumbaugh et al. (1991).
The modules written for this thesis have been named 'LIBname', whereas the older modules are
named 'INP..DEV3' and 'PCR-SUP'. The description of a small conversion tool is included in the
following discussion of these modules:
LIBG10: This module implements various useful routines, such as conversion between various
number formats and their string representations, and arithmetic functions. All these function
are implemented in a way which is not OOP conform, since a handy OOP-implementation
requires overloading of operators which is at present not available for Borland Pascal. The
source code can be found in appendix C.3.
LIBVAR10: Four separate object classes are defined in this module: Log, Timer, Image and Tactile
Mem (figure 3.2). Their functions are as follows:

TactileMem Log
Memory: array
Init Init(Name)
Done Done
Assign(x,y,TactCon,Fx,Fy) Log(txt)
Get(x,y): TactCon,Fx.Fy Flush
Image Timer
Image: record Elapsed: real
Width: integer Split Time: real
Height: integer Init
Init Done
Done Reset
Drop Start
Get(x l,y l,x2,y2) Stop
Put(x,y,BitBit)
Save(f: file)
Load(f: file)
Figure 3.2: The OMT representation of the Log, Timer, Image and Tactile Mem classes. They
are defined in the LIBVAR10 module.

3.3. MODULES 15
Log: this class defines an interface for the handling of log files.
Timer: a normal PC software timer has a resolution of circa 55 ms, which is too imprecise for
the collection of data on movement time. This class implements a timer with a resolution
smaller than 1 microsecond and is based on code from the SWAG-collection. Functions
are available for resetting (Reset), starting (Start) and stopping the timer (Stop). If
the timer is running, intermediate times can be determined using Split Timer. After
the timer has been stopped, the total elapsed time is available through Elapsed.
Image: the creation (Get), handling (Put) and storage in files (Load, Save) of bitmap pictures
is simplified by this class. A utility (CONVGRAF, discussed below) is available to convert
graphics, matching a limited set of the PCX-standard (documented by Rimmer (1993)),
into the custom format used by this class. This class is based on code from the SWAG-
collection.
Tactile Mem: this class was created to increase the frequency with which the position of
the trackball can be read and the tactile feedback can be updated. An increase was
necessary to avoid oscillation problems with the trackball-device. Oscillation occurs
when the motor force changes much repeatedly and rapidly.
The class enables the storage (Assign) and fast retrieval (Get) oftactile force fields. This
is implemented by calculating the tactile force vector required for every discrete position
inside every possible target and storing these values in an array. Retrieval of the tactile
forces is done by look-ups instead of computational extensive operations. Tactile Mem
was not integrated with the ur class since it is not generally applicable because of the
64 Kb limit on the size of segments.
LIBUI10: The user interface with all its I/0 aspects, such as pointer and keyboard input, and
visual, audio and tactile output, is handled by this module. The hierarchy of the interface
is depicted in figure 3.3. This hierarchy was designed to ensure that the natural view on
user interfaces was combined with an elegant interface towards the applications. A complete
motivation for the chosen hierarchy is given in the next section.
The user interface consists of an aggregation of classes across several levels into the Ul class.
The first level below the UI class is made up of input devices (Keyboard, Pointer) and output
devices (Tactile, Audio, Visual). These classes and their children will be discussed next:
UI: the interface is initialised by Init which takes the pointer type as an argument. Two
pointers are available: a small square for experiments with two-dimensional screen layout
and a rectangle with small width and large height for experiments with one-dimensional
screen layout. Callback functions are provided by the Pointer and Tactile classes
for updates of the screen pointer position and the tactile feedback. These allow the
experimental software to control directly the relation between motoric movement and the
screen pointer position and the tactile feedback. These callback functions are activated
after the function Update Pointer And Tactile notices a trackball movement.
Keyboard: the Keyboard class only offers functionality for delaying until a key is pressed
(Wait For Key).
Pointer: the screen pointer and its movement are implemented in this class. Besides regular
functions such as switching the pointer on or off (Switch On, Switch Off) and position-
ing (Warp To New Position), hooks are offered where user-supplied functions can be
inserted. The relation between displayed and motoric movement can be influenced by
the application using Set Gain Function and Set Contextual Gain. A function can
be supplied (Set Update Target Function) to calculate which target is currently un-
derneath the pointer. Finally, a function is available to activate these callback functions
{Update). Two classes have been aggregated into this class:
Button: indicates the status of the button through Pushed.

!
Keyboard Input
I Ul Audio Output
Is Off: boo!
lnit 0 lnii(Pointtr type)
A Current Frequency: real
i
v
Done
I
Done Swi11:h: {off. on}
Wait ForKey Update Pninter And Tactile Stored Stations: array
I
!nil(Address)
Done
t
Set Audio(Vol, Bal. Treble, Bass)
l
Set Fn:quency(Fn:q)
Store Station(Nr, Fn:q)
Tactile Output Pointer Input Select Station(Nr)
Is On: bool Swill:hOff
Init X position: int Swill:hOn
Done Y position: int
Set Function X(l) Last Move X: int
Set Function Y(l) Last Move Y: int
lGet Force X(d,x,y): int Rerum Pos: position
Get Force Y(d,x,y): int lnit(Type)
Update Force(dX, dY, X, Y) Done Visual Output
I
Switch Off
Switch On Init
Warp to New Position(Pos) Done
Motor Output Set DC Gain X(Gain) Clear
Static Friction X: int Set DC Gain Y(Gain) Draw Centered Box X(x,w)
Static Friction Y: int Update Draw Centered Box XY(x,y,w,h)
lnit Set Contextual Gain(Type) o- Draw Box XY(xl,yl,x2,y2)
Done Set Gain Function(fx,fy) Save Stare
Set Force X(Fx) Set Update Target Function(!) Restore Slate
Set Force Y(Fy) 0 Set Color(i)
Calibmtellterations) Set Fill Color(i)
I
Out Text XY(x,y,txt}
Out Text XY Righl(x,y,txt}
Buuon Input Out Text XY Right Erase(x,y,txt}
Input Devlee (INP_DEV3) Pushed: bool Out Text XY Center(x,y.txt)
Is Button Down: bool 0 !nit Fill Ellipse(x.y,rx.ry)
Get Ball Position X: int Done Not Filled Ellipse(x,y,rx,ry)
Get Ball Position Y: int Circle(x,y,rad)
Init
Read Position TrackbaU Input
Reset Force A X position: integer
v
,___
Add Force(Fx,Fy) Y position: integer
Actuate Momrs Init
, Read Push Button Done
Figure 3.3: The OMT representation of the class hierarchy of the user interface. The small
diamonds indicate that an object from the class at the side of the diamonds is assembled of
object(s) from the other class(es).

3.4. USER INTERFACE CLASS HIERARCHY MOTIVATION 17
Trackball: returns the current x- and y-position of the trackball through X position
and Y position.
Tactile: tactile feedback is implemented by this class. It offers callback functions (Set
Function X, Set Function Y), thereby enabling the application to freely shape the
type and strength of the tactile feedback. The force in a certain position is returned by
Get Force X and Get Force Y. Finally, a function is available to activate the callback
function (Update Force). The motor control is done by the Motor class:
Motor: besides offering functionality for calibration of the static friction (Calibrate), it
offers two functions to set the motorforce (Set Force X, Set Force Y). These two
functions compensate static friction by enlarging the forces by a component of the
static friction found during the calibration phase.
Audio: the Audio class integrates a radio I/O-card into the user interface. Operations on this
radio include switching on or off (Switch On, Switch Off), the selection of a frequency
(Set Frequency) and setting of audio parameters (Set Audio). It is possible to store
stations (Store Station) and recall a previously stored station {Select Station).
Visual: this class covers several graphical primitives such as the drawing of circles (Circle)
and text (Out Text XY). Included are methods that save (Save State) and restore
(Restore State) the graphics state.
The Motor, Button and Trackball class rely on the Input Device class, defined in INP-DEV3,
for correct low-level driver implementation.
INP-DEV3: INP-DEV3 and its child modules take care of the low-level calls to the trackball hardware.
Its responsibilities include: setting the hardware-port such that a certain force is generated
and reading the value of the position as indicated by the sensors on the trackball.
PCR..SUP: This module supports the low-level control of a radio-card. Initially, auditory feedback
was chosen to be part of the research. Later, decision was made against auditory feedback,
since auditory and visual feedback spread the workload over two modalities. A high visual
workload was necessary to simulate a normal user interface where the emphasis is on visual
feedback.
CONVGRAF: Although CONVGRAF is a program and not a module, it is discussed here since it is
used in combination with the Image class. It is capable of converting graphics, matching a
limited set of the PCX-standard, into the custom standard employed by the Image class. The
program can handle only one bit deep (two colour) PCX-files with either none or runlength
encoding and a ma.'<imum size of 640 pixels width and 480 pixels height.
3.4 User Interface Class Hierarchy Motivation
The hierarchy of the UI class was based on a natural view towards the user interface, combined
with an elegant interface towards applications. The user interface is seen as composed of many
input and output media. Possible input media are keyboards, pointing-devices such as mice and
trackballs, and gesturing devices such as datagloves and touchscreens" A complete classification
of input devices is given by Mackinlay et al. {1990), whereas Buxton (1986) demonstrates the
various important aspects of input devices. All regular input devices are controlled by muscular
movement. Output media include screens, speakers and tactile pads. Normally, output is given
through the visual, acoustic or tactile modality·(respectively, sight, hearing and touch).
The only input media in the user interface for the experiments are the pointer, controlled by
trackball movements, and the keyboard. Output media are limited to one audio device, one screen
and one trackball with tactile output. Of course, many more attachments such as touch pads or
support for multiple screens could have been added, but their addition was not necessary. Only
when the need arose, a new input or output device was added. The user interface class was

constructed in such a way that it is easy to add new devices, an approach also followed by the X
Window System (Nye, 1988).
Several frameworks exist for the presentation of applications to the user, acceptation of input
and invocation offunctions (Dodani et al., 1989). Most frameworks separate the application's func-
tionality {interior) from its appearance (exterior). Such an approach avoids massive code changes
when the interface changes. A common framework is the model-view-controller framework which
separates the interior (model) from the exterior (view). The controller manages communication
between these two layers, driven by input of the user.
Since the software for the experiments tries to test hypotheses regarding such a user interface
framework, the software must be able to control the framework itself. This hinders an implemen-
tation of the user interface along a standard framework, such as MVC. It is even such that the
model (functionality) of the application includes the view and control aspect.
Currently, the UI class integrates the input and output devices and does not take care of the
control and view aspect. For example, the appearance of objects and the movement of the visual
output of the pointer are controlled by the software using the user interface class. One might
argue that the UI class is just a graphics package, providing the facilities to manipulate the basic
elements of in- and output. However, it provides several possibilities for callback functions for
updates of the visual and tactile output of the pointer. These callback functions, realising part of
the controller, make the class more than just a graphics package.
Also, one might argue that a pointer is not an input medium. The relative position sensors
and the button should be considered as input media instead and be made members of the user
interface. However, the only part of the user interface influenced by this pointing and selection
device is the pointer, so that the pointer and pointing device can be identified as one separate
system that acts as an input device.
Another argument against this hierarchy is that the pointer normally is part of the visual part
of the user interface. In this hierarchy, the pointer's position can be translated in parallel by
all three output media into a signal in the appropriate modality. Another possibility could have
been to insert the pointer class as a common child of these output media. However, it is the
responsibility of the top layer of the user interface, and not of an output medium (view), to define
the functionality of a pointing action (control), as is defined by the model-view-controller concept
of SmallTalk.

Chapter 4
Models for Tactile Fields
4.1 Introduction
A general model was developed on unambiguous mathematical terms and physical foundations in
order to systematically define and evaluate the tactile fields using subjective and objective human
performance data. The model includes all known physical parameters of the IPO trackball which
control and elicit the tactile feedback and includes dependencies based upon external forces such
as hand pressure.
Theoretically the general model could have been based on haptic shape perception rather than
mechanical attributes of the device, however there is a lack of empirically based data on the dis-
crimination of static shapes for complete modellation. The available literature in general discusses
the difference between active and passive touch and scanning directions (Gibson, 1962; Magee &
Kennedy, 1980; Heller & Boyd, 1984; Heller et al., 1989). Some progress has been made on the
discrimination of static objects (Kappers et al., 1992; Kappers et al., 1993). Furthermore, studies
on haptic perception typically do not account for factors such as movement velocity which can
influence perception of tactual forms.
While the general model can account for a large range of tactile fields, a submodel was derived to
capture intuitive concepts, such as friction and gravity, in simple terms. Secondly, the submodel
enabled the visualisation of the tactile fields. Thirdly, the submodel simplifies the integration
of tactile feedback in the design of graphical user interfaces whereby objects can have multiple
physical attributes (e.g., colour, roughness, and pitch) across modalities (e.g., visual, tactile, and
auditory).
A common approach in modelling tactile feedback is to represent the amount of tactile feedback
as a gravity force, based on a function of pointer-position (Minsky et al., 1990; Atkinson et al.,
1977). .
Minsky et al. (1990) used a heightmap to simulate different types of texture. Given a height
map, and the cursor-position on this map, the tactile feedback was computed using gradients
(figure 4.1). Tactile feedback was given in two dimensions, x andy, as the device was a joystick
with force feedback. The computed two-dimensional force-vector F, based upon the height map,
19

20 CHAPTER 4. MODELS FOR TACTILE FIELDS
h
X
Figure 4.1: A plot of a heightmap and the gravity force for several positions. Extension to two
dimensions is trivial.
can be described as
f = ( oh~;v), oh~~ y))
with
F : tactile feedback force
h : heightmap
x : current x-position
y: current y-position
(4.1)
In addition to modelling the tactile forces of the device, the response of the human arm to radial
(forward/backward) and tangential (left/right) motion was considered for an optimal representa-
tion of perceived texture.
In the model presented by Atkinson (1977), tactile feedback was determined based on the
position, using the three-dimensional Cartesian coordinate system. The device, 'Touchy Feely',
consisted of a pyramid with four faces (tetrahedron) with shaft encoders and torque motors at
each of the four vertices. Attached to the shaft of each motor is a take-up drum for a steel cable
tied to a small ball at the centre of the pyramid. The operator grasps the ball and controls its
position within the tetrahedron, while the computer controls the force on the ball via the torques
on the motors.
The values from the four position sensors were translated into the three-dimensional Cartesian
position. The three-dimensional tactile force vector was computed from the x, y and z-position
and a mapping function. The computed tactile force vector was then mapped and communicated
to the four motors. The used model for tactile feedback can be described by:
with
F = f(x,y,z)
F : force for tactile feedback
x : current x-position
y: current y-position
z : current z-position
Atkinson also notes in his article that additional input-variables for the tactile force function f
(e.g., velocity or time) can extend the range of possible feedback.

4.3. GENERAL MODEL 21
4.3 General Model
4.3.1 Device Characterisation
The IPO-trackball consists of a conventional trackball with two servo motors, positioned along
the x- and y-axis of the ball, which generate tactile feedback. Two optical position sensors, one
on each motor shaft, are used to monitor ball position. A PC is used to evaluate the information
from the position sensors and control the servo motors. Altogether, the state of this device can
be characterised by four scalars:
• The x- andy-position, expressed as rational numbers {R) using the metric scale. This can
be noted as:
xEX
yE y
X,Y=R
• The total force exerted on the trackball along x- and y-axis, expressed in Newton using
rational numbers. This two-dimensional force vector f is taken from the set of possible force
vectors F, equal to R2
. This force is equal to the addition of the force exerted by the motors
(Fmotor} plus the force exerted by the user of the device (Fuser}·
In the sequel, the following conventions will be used:
• units such as Newton are to be understood implicitly,
• the x- andy-component of a force F will be noted as Fp, with p equal to 'x' or 'y',
• for both position (x and y) as force (F., and Fy} the upper-right quadrant is associated with
positive values,
• ball position is identified with pointer position.
4.3.2 Model Derivation
The smallest spawning space S of all positions of the ball and forces on the ball is the Cartesian
product of the domains of these:
S=XxYxF (4.2)
All possible states of the trackball are in Sand vice versa: if s E S, then s constitutes a possible
state of the trackball.
The system (in this case a PC) can control only the force exerted by the motors (Fmotor)
directly. Determination of x- and y-position is straightforward since the trackball is equipped
with two independent position-sensors for the x- and y-axis. However, it is more difficult to
determine the force exerted by the user (Fuser), since it is not measured. Instead, Fuser has to be
derived by physical formulas from knowledge inside the system. This knowledge should include,
besides a mechanical model of the device, the previous x- andy-positions of the trackball and the
Fmotor applied.
The tactile response of the system can be modelled by a function f that defines the general
model for tactile fields generated by the IPO-trackball:
Fmotor = f(x, y, m}
with
x x-position
y y-position
m internal state of the system
(4.3)

Figure 4.2: The relation between the general and submodel. The general model enables expression
of tactile fields using a complete enumeration of all possible combinations of all known physical
parameters. The submodel contains some of these tactile fields and none not also included in the
general model.
m can hold older values of x, y and Fmotor• as well as the time at which these values occurred. Fuser•
velocity, acceleration and other derived measures present in m might also be used for determination
of Fmotor·
4.4 Subspaces
The function f of equation 4.3 can easily be executed by a computer. However, a tactile feedback-
class designer will have troubles interpreting and manipulating f To reduce the complexity of
j, they should have the opportunity to work with (graphical representations of) subspaces of the
space occupied by the model. These subspaces could be mapped into f Such interactions with
simple subspaces allows designers to intuitively manipulate the tactile feedback, without losing
the capability to manipulate fat the most complex level. This approach has the advantage that
if more knowledge on tactile perception comes available, a new subspace can be added to the
available subspaces. The subspace could take into account these new insights, without requiring
a massive overhaul of the design-software.
4.5 Desktop Subspace
In the following, a simple and powerful subspace will be discussed. Its relation to the general
model is depicted in figure 4.2. This subspace will be called the 'desktop subspace' since it is a
simple subspace that can model the tactile properties of objects found on an office desktop. A
similar approach has been used for the visual properties of the ViewPoint user interface of the
Xerox Star (Smith, 1985; Johnson, 1987; Johnson et al., 1989).
The subspace can be graphically represented on a colour screen, as will be shown in subsec-
tion 4.7. Another advantage of a submodel for tactile feedback, based on the desktop metaphor,
is easy future integration with a visual user interface, also based on this metaphor. To reduce the
number of variables involved in determining Fmoton the complex system state m will be replaced
by the direction of ball movement d. This is possible since:
• Models for the design of graphical user interfaces in general separate the static design from
the creation and destruction of objects (icons). Applications for a tactile user interface should
take care of the creation and destruction1 of tactile fields and should not rely for this on the
definition of the tactile field.
1
Many relevant operations on tactile fields can be simulated by creation and destruction. E.g. movement of a
tactile field is equal to the destruction of the tactile field and recreation at the new position.

4.6. HEIGHTS 23
• The major tactile forces are those created by gravity for heightdifferences (Fgravity) and friction
(Frriction)· dis a sufficient parameter for friction and gravityforce.2
• Strictly necessary dependencies of tactile fields on parameters only contained in m can be
realised as described before.
When m is replaced by d, the function for motorforce becomes:
Fmotor =f' (X, y, d) · (4.4)
The gravity (Fgravity) and friction (Frriction) force can be be extracted from f', leading to two new
functions f~ and iJ for, respectively, the gravity and friction force:
Fgravity=/~(x, y, d)
Frriction=fJ(x, y, d)
The motorforce then equals3
Fmotor =Fgravity- Frriction
with
- JFrriction =Frriction *jdj·
Note that
Fgravity +Frriction -:f. f' (X,Y, l) •
(4.5)
{4.6)
(4.7}
(4.8)
Please also note that the friction can be larger than the gravity force. Normally, the amount of
friction is smaller than or equal to the sum of all other forces. If necessary, this restriction can
be implemented. However, it increases the number of tactile feedback types that are described by
the model, without increasing the difficulty of understanding the model.
4.6 Heights
Function f~ offers more freedom than the gravityforces possess as we experience them in ev-
eryday life. For example, f~ can define a tactile field that rotates around an origin, as shown in
figure 4.3. The complexity contained in this freedom is very hard to understand and interact with.
A constraint is imposed on f~ to allow only gravity fields that can occur in everyday physics. A
function h is introduced which maps coordinates to height:
h : X x Y --+ Z with Z in meters. (4.9)
Gravityforce Fgravity can be expressed as the gradient of the heightmap:
(4.10)
with c a constant (c ~ 0) representing the weight of the object whose gravityforce is calculated.
The minus-sign is present since a positive gradient of the heightmap should create a negative force
and vice versa.
2
0f course is texture another important parameter for tactile perception. However, it can be implemented by
friction and gravity
3 Formula 4.6 does not capture the resulting function completely as will be explained in the forthcoming.

ty
x -
Figure 4.3: A rotating tactile gravity field.
4.7 Static Graphical Subspace Representation
It is trivial to represent the gravityforce as a static 3D-picture on a screen. The height-function
uniquely determines the gravityforce using three dimensions. A visual representation might map
the x and y-position on the x- andy-axes and h(x, y) on the z-axis. To enable easy visualisation
of a complete tactile field, it is desirable that friction is included in the same picture. However,
only colour is left as an easily perceived dimension, whereas friction requires three dimensions,
namely those of J and fJ.
Since the scalar friction requires itself one dimension for presentation, the function for friction
can only include x, y and h(x, y) as parameters. To ensure easy interaction with tactile fields
presented in the submodel, friction and gravity should be independent. This motivation leads to
a new function fJ, depending only on x and y:
Frriction =fJ(x, y) {4.11)
f1 can not express all the functionality of physics such as materials with different kinds of friction,
depending on the direction of movement. But also note that this function maps to a superrange of
the range of friction in physics! The function fJ does not assume that the friction is restricted to
positive values. Negative friction is a powerful extension, introducing very little extra complexity
in understanding and interaction with tactile forces depicted using the subspace. This extension
compensates to some degree the deletion of l from fJ, as will be explained in the next section.
4.8 Negative Friction
Using negative friction, a designer can create tactile fields of the subspace with areas where Fmotor
differs (possibly both in sign and size) depending on the approach angle. Normally, the total motor
force is always reduced by friction. However, when the sign (and direction) of Frriction changes,
friction is able to increase motor force. For example, in figure 4.4 two one-dimensional functions
for Fgravity and Frriction are plotted for positions on a line, with Fgravity = ! and Frriction = t.
When the points on the line are approached from the left, the resulting motor force is equal to L
whereas the force is zero when approached from the right (figure 4.5}. The inclusion of negative

4.9. CONCLUSIONS 25
Fgravity
~--------------------------------
0 ~------------------------------~X
~------------------------------Ffriction
-l ~
~---------------------------------
Figure 4.4: Gravity and friction force for positions on a line.
friction enlarges the subspace with some of the capabilities of function 4.5, where friction was
direction dependent.
When friction would be constrained to positive values or zero, only the size and not the
direction of Fmotor would be subject to change. A tactile force function as described above can
not be constructed without negative friction. This can be proven as follows:
Suppose
Frriction ?: 0. (4.12)
and
Fmotor = IFmotorl
Fmotor for a movement from left to right should be 1. However, Fmotor for a movement from right
to left should be 0. Given
Fmotor = Fgravity - Frrictlon (4.13)
leads to the following equations for movements, respectively, from left to right and right to left:
l=Fgravity - IFrrictionl
O=Fgravity + IFrrictionl
Some calculus leads to a unique solution:
Frriction = -1/2 1 Fgravity =1/2
(4.14}
(4.15}
This solution is in contradiction with equation 4.12. It completes the proof that allowing negative
friction increases the number of tactile feedback types that are contained in the desktop-subspace.
4.9 Conclusions
The two models, described by equation 4.3 and the combination of equations 4.10 and 4.11, offer,
respectively, a general model and a submodel for the IPO-trackball. The general model can
represent all possible tactile stimuli that can be generated by the IPO-trackball and provides an
excellent starting-point for smaller and less complex models. The submodel is a simple model,
based on the general model, that adds friction to the models of Minsky et al. (1990) and Atkinson
(1977). One of its attracting features is that ·tactile fields, modelled with this model, can be
depicted by a static graphical representation on a colour-screen since the parameters stem from
a four-dimensional space. Also, this model has been proven to describe an interesting range of
categories of tactile fields, as was proven by Minsky et al.
However, the submodel, inspite of being comprehensive and powerful, will probably not stand
the test of time, as more and more research is conducted on the tactile senses. In time, a complete

Figure 4.5: The resulting motorforce when moving along the line, respectively, from left to right
and from right to left.
model will be made up that includes the human point of view, thereby making the submodel
obsolete for the design of tactile fields. The desktop model will be used as a basis for further
research on tactile senses because of its comprehensiveness and probably more limited range of
factors affecting tactile feedback.

Chapter 5
Performance Effects of Various
Types of Tactile Feedback
5.1 Introduction
Recently, there has been more research into the use of tactile feedback in relatively simple and
inexpensive input devices such as the joystick and the mouse. While previous studies demonstrated
performance gains when adding tactile feedback to visual feedback (e.g., Goossens (1992), Gilson &
Fenton (1974), Keyson (in press) and Akamatsu et al. (in press)) the qualitative and quantitative
aspects of the tactile feedback were not addressed. For example, the strength of the tactile force
or form may influence performance in simple target acquisition tasks (i.e. selection tasks). This
study was conducted to explore the performance effects of various types of tactile feedback in a
target acquisition task using a trackball with tactile feedback.
Similar to the design of visual interfaces, tactile displays can be constructed using a combination
of physical attributes. While guidelines and handbooks exist for the evaluation and design of visual
user interfaces such materials are lacking in the construction of tactile interfaces. For example,
visual attributes can be shape, colour, size and layout. Mayhew (1992) lists several guidelines for
optimising the design of a visual interface.
Among the many objects that make up a visual user interface are icons; graphical conveyers of
information with behavioural and intrinsic properties (Johnson et al., 1989). An icon is defined
by a set of visual attributes and its behaviour. The behaviour determines the response of an
icon to user input, time or machine state. Both the visual attributes and behaviour of icons have
been systematically studied and demonstrated in terms of combined effects on human performance
(Gittins, 1986; Brems & Whitten II, 1987).
A user interface with tactile feedback can be composed of tactile fields, some of which are global
and provide a common context, while others may be object-like tactile conveyers of information. A
visual analogy here would be a desktop background image versus an icon. The term 'tactile field'
was used to refer to tactile objects which can be manipulated and convey information. Similar
to icons, a tactile field can be defined by a set of physical attributes and their behaviour. For
example, one physical attribute of a tactile field may be its degree of roughness. The behaviour
could be the amount of roughness felt, depending on user movement speed.
The input device used in the current study is a trackball with tactile feedback developed at
IPO. To support the target acquisition task several tactile fields were modelled and evaluated.
The fields were designed to represent a range of felt dips on a flat surface, varying in force level
and form. The fields remained static and did not change as a result of user interaction.
In the next section an overview of relative literature pertaining to the mechanical modelling and
human evaluation of tactile feedback is given. Section 5.3 discusses the results from a preliminary
field study, followed in section 5.4 by a description of the design of the experiment conducted. The
remaining sections give the results, discussion and conclusions.
27

28 CHAPTER 5. PERFORMANCE EFFECTS OF TYPE OF TACTILE FEEDBACK
5.2.1 Background
Little research has been reported that addressed the quantitative and qualitative aspects of tactile
feedback. Typically, studies involving tactile feedback (Gilson & Fenton, 1974; Hinton, 1993;
Akamatsu et al., in press; Goossens, 1992) contrast tactile versus visual or audio feedback. The
form and force level of the tactile feedback is not generally stated nor defined. The lack of modeling
techniques for tactile input devices reflects the approach which researchers, such the above, have
taken. Secondly, as a result of the tactile versus no tactile feedback approach, there exists a lack of
research pertaining to the subjective and objective evaluation of various types of tactile feedback.
5.2.2 Tactile Feedback and Simple Navigation
The potential benefits of tactile feedback in a simple navigation task such as in a point~and~select
task have been demonstrated under a range of human performance measures. However, there
appear to be differing results for the same measure across similar studies.
The time needed to complete a maze task and number of errors, using a trackball with force
feedback was investigated by Goossens (1992). Addition of tactile feedback to visual feedback
significantly decreased the time needed to complete a maz~tracking task by 34% and the number
of errors by 76%.
Goossens also considered the bandwidth of human performance in a target acquisition task.
Bandwidth (Fitts, 1951) can be described as a measure for the amount of information a person
processes per second in a target acquisition task. Bandwidth is typically calculated from the
time needed to complete the task, the distance to the target and the width of the target. A
higher bandwidth indicates a higher performance level in terms of movement time and accuracy.
Goossens found that the bandwidth increased by approximately 50% (from 6.4 to 9.83 bitsfs) by
the addition of tactile feedback to a target acquisition task.
In a study on target acquisition by Akamatsu et al. (in press), using a mouse with a pin for
tactile feedback, bandwidth, response time and error rate remained constant under conditions of
tactile and no tactile feedback. However, reaction time, defined as the time between entering the
target region and selecting the target, did vary as a factor of tactile feedback. Reaction time
decreased from 298 ms in the visual feedback condition to 237 ms in the combined tactile/visual
feedback condition.
The effectiveness of tactile feedback appears to be related to the extent in which the visual
and possibly other modalities (i.e. a human sensory mechanism, for example sight or hearing
(Berchem-Simon, 1982)) are loaded as well as the degree of required skill. For example, Gilson
(1974), using a control stick with tactile feedback, found that in a highly structured approach
and landing task comparable results were obtained by using either visual or tactile feedback for
presenting critical plane control information. But, in a task requiring the pilot to make tight
turns about a point, Gilson found a significant decrease of deviation in the desired angle of attack
when tactile feedback was provided. Additionally, tactile feedback decreased the variations in the
maximum altitude and speed. The approach and landing task did not put a high burden on the
visual modality, since it was highly structured. However, the turning task created much more
arousal on the visual modality, thereby enlarging the performance impact of tactile feedback.
5.2.3 Subjective and Objective Performance Measures
The use of subjective and objective human performance measures in the study of human-computer
interaction has been widely discussed by a number of authors (e.g., Leep (1963) and Nielsen
(1993}). In exploring the use of tactile feedback as a relatively new and as yet not clearly un-
derstood modality for human-computer communication, the use of subjective measures plays an
important role. While objective measures such as reaction time, movement time and number
of errors can be recorded, one may question whether such parameters can fully characterise and

5.3. FIELD STUDY 29
predict human performance. In the current study subjective measures, such as quality of a tactile
field, were used to complement the objective measures.
5.3 Field Study
A preliminary field study (unpublished) indicated that the objective and subjective performance
depended indeed on type and strength of tactile feedback. This field study took the form of a
target acquisition game with tactile feedback. This game was played by approximately 300 children
during an open house of the Eindhoven University of Technology.
However, this study did not give sufficiently valid and significant results on performance dif-
ferences between differences types of tactile feedback, since the environment was insufficiently
controlled and the IPO-trackball contained too much friction. The trackball was modified to run
more smoothly and a slightly modified version of the experiment was rerun under a laboratory
condition.
5.4 Description of the Experiment
An exploratory study was conducted to consider the degree to which various aspects of human
performance in a target acquisition task are influenced by different tactile forms and forces in
order to optimise tactile feedback. To evaluate human performance both subjective and objective
measures were used.
5.4.1 Apparatus
The setup consisted of the original IPO trackball with force feedback (Engel et al., 1994) connected
to a PC (Dell 433/M) with a 14" VGA colour screen (Philips Brilliance 1410) at 640x480 pixels.
The trackball was used to move a pointer on the screen and to generate tactile stimuli. Two servo
motors positioned on the x- and y-a:x.es had been added to transport tactile information. Exact
ball position was monitored by two optical sensors on the motor-axes. The DC-gain, defined as
the displayed movement divided by the control movement, was fixed at 20 em movement on the
screen for each em of control movement of the ball. The cover of the device consisted of a 4 mm
thick Plexiglas surface with a 53 mm diameter hole. The ball itself had a diameter of 57 mm and
extended 8 mm above the Plexiglas.
5.4.2 Subjects
To control for handedness factors (Varney &: Benton, 1975) right-handed subjects were chosen
with normal or corrected-to-normal vision. Twelve subjects participated, ranging in age from 21
to 33, with a mean age of 24. With the exception of three subjects, none of the subjects had
previously used the IPO trackball. All subjects participated on a voluntary basis.
5.4.3 Procedure
The experiment consisted of 36 blocks with 25 trials (each consisting of one target acquisition task)
per block. The experiment was concluded by a subjective questionnaire. Each block represented
a unique feedback condition using four tactile force levels, three tactile forms and three levels of
target difficulty. All variables will be described in the following subsections. Using a repeated
measures design each subject completed the blocks in random order over two sessions with a five
minute break between sessions.
Each subject was seated alone in a quiet room in front of the monitor with the keyboard on
their left and IPO-trackball on their right. The seat had elbow-rests to avoid fatigue. The upper
and lower arm were at an angle of approximately 90 degrees. Subjects were told to keep their

Table 5.1: Index of difficulty ID, distance A and width W of the tested targets.
ID (-) A (mm) W (mm)
1.3 23.4 16
35.0 24
46.7 32
1.8 39.7 16
59.5 24
79.4 32
2.2 57.4 16
86.2 24
114.9 32
hand level with the trackball and to maintain control of the trackball with a grasp-like gesture of
the hand. Their progress and performance were remotely monitored.
Prior to running the experiment, each subject was given an oral explanation of the test proce-
dure and the follow-up questionnaire. The instructions were also given on paper to the subjects.
Subjects were instructed to acquire the target (a circle) as fast and accurately as possible once
the target appeared on the screen.
Each trial began with a random delay from 250 ms to 1250 ms to avoid an effect whereby
subjects would move according to a rhythm while selecting targets. A 25 ms-500 Hz beep was
given to signal the target appearance and beginning of the trial. At this time a 2.0 mm square-
pointer appeared in the centre of the screen. The angle of the target in relation to the centre of
the screen varied across trials on a random basis. The subject pressed the space bar to acquire the
target. If the pointer was over the target when the space bar was pressed, a high, 25 ms-500 Hz
beep was given to acknowledge successful acquisition. If the target was missed a low, 25 ms-250
Hz beep was given.
5.4.4 Target Difficulty
The size and the distance from the centre of the screen for each target was based upon three
levels of target acquisition difficulty as defined by Fitts' law (Fitts, 1954; Fitts & Peterson, 1964).
According to Fitts' law the difficulty in selecting a target, as measured by total response time, is
based upon a positive, linear relation between total response time and a function of the width W
and the distance A of the target. The inverse of the slope in this relation is called 'bandwidth'
and represents performance. Difficulty is expressed according to the index of difficulty (ID) by
the following formula:
ID =2
1og(AJW + 1)
This slightly modified version of the original formula was derived by Shannon (1949). It is used
since it provides a slightly better fit with observations, exactly mimics the information theorem
underlying Fitts' law and always gives a positive rating for the index of difficulty (MacKenzie,
1989; MacKenzie, 1992). Using three levels of difficulty on Fitts' ID index, nine combinations of
target distance and width were tested (table 5.1).
5.4.5 Tactile Form
Three different circular tactile forms were contrasted. Vhen approached from any direction, the
forms were felt. as a dip towards the centre of the target. The tactile forms corresponded in surface
area to the visual targets. For reference the three tactile target forms are referred herein as the
'fiat', 'hole' and 'combined' form. The flat form was felt as constant force, the hole form was felt

5.4. DESCRIPTION OF THE EXPERIMENT 31
Height Height Height
Figure 5.1: The heightmaps of the contrasted tactile forms 'fiat', 'hole' and 'combined' along any
arbitrary axis through the center of the tactile field.
Force Force Force
Figure 5.2: The forcemaps of the contrasted tactile forms 'fiat', 'hole' and 'combined'. Force was
directed towards the centre.
as a diminishing force towards the centre and the combined form was felt as a constant force in
the outer area of the form and a diminishing force towards the centre in the inner area.
The heightmaps for each of the forms are illustrated in figure 5.1. In figure 5.2 a three dimen-
sional view of the forms is given, showing the level of force towards the centre of the form as a
function of horizontal (x) and vertical (y) position. The mathematical description of the tactile
forms can be found in appendix A. To prevent ball oscillations, the inner 4% of the circular area
within the centre of target contained a zero force level. This was necessary given the hardware
limitations of the current device.
5.4.6 Maximum Tactile Force Level
The maximum force levels applied to the ball, independent of the hand, were 0 mN for the no
tactile feedback condition and 100, 225 and 350 mN for the tactile feedback conditions. In the
case of the flat form the force level was always equivalent to the maximum force level up to the
centre area of the target. From herein, force level will always refer to maximum tactile force level.
5.4.7 Questionnaire
After completion of all blocks, the subject was confronted with a screen depicting 36 different
target conditions at random in a six times six matrix. Three different possible target diameters
(16, 24 and 32 mm) were shown, combined with. the different force levels and forms. The subjects
were instructed to feel all of the targets and rate each one individually in terms of strength and
qualitative feeling for tactile feedback. The subjects rated the targets using a matrix form which
matched the layout of the screen. Each target was rated for tactile strength and quality using a
five point scale. The perceived presence of tactile feedback was rated from "bad" (1) to "good"
(5). Tactile quality was rated from "unpleasant" (1} to "pleasant" (5).

5.5 Data Collection
The following measures were recorded for each trial:
tmav: movement time, i.e. time (since the start of the trial) at which the target was entered for
the final time,
trea.ct: reaction time, i.e. difference between the time at which the target was entered for the final
time and the time at which the spacebar was pressed
Oversh: whether an overshoot occurred. An overshoot occurred when the target was entered at
least twice.
A serie of pilot tests using three subjects was conducted to assess the face validity of these
measures. Secondly, the pilot data confirmed the settings for target force, target difficulty and
tactile form in terms of having an influence upon performance. Two of the pilot subjects indicated
that they overshot the target more often when no tactile feedback was given. This lead to the
addition of the Oversh measure. The subjects from the pilot experiment did not participate in
the actual experiment.
5.6 Results
All data were analysed for statistical measures and significance levels using SAS (SAS Institute
Inc., 1990}. Results from the 25 trials per block indicated that performance in the first trial across
all blocks showed no correlation with the remaining trials. Given that subjects were unaware of
the feedback condition when beginning a new block, the first trial was omitted from the data
analysis. Trials which were completed while the pointer was outside the target area, were not
analysed. Extremely low or extremely high scores, across all objective dependent variables, were
defined as those which fell into the bottom or top 2.5% of the variable's distribution. Extreme
scores were removed from the analysis to eliminate time rounding errors of the data collection
software and unrealistic bad performance.
A MANOVA analysis for main effects indicated that movement time was significantly affected by
all of the target variables: target difficulty, target form and target force level. Reaction time was
significantly affected by target force level. The subjective measures and percentage of overshoots
also showed similar trends, but were not analysed for significance level. The analysed dataset
with the stochastic variable movement time contained 9595 samples, the dataset of reaction time
contained 9592 samples and the dataset of overshoot contained 9830 samples. For each of the
subjective variables 432 samples were coJJected and analysed.
5.6.1 Target Difficulty
The influence of target difficulty on movement time was highly significant {F(2, 10} = 340.60,
p = 0.0001].1 With increasing target difficulty, movement time increased from 504 ms to 685
ms. A contrast of means (table 5.2) indicated that each individual target difficulty level was
significantly different compared to the other levels [F(1, 11) = 312.14 ... 703.24, p = 0.0001]. The
percentage of overshoots also tended to increase linearly with target difficulty at an average rate of
4.7% per unit of target difficulty. Reaction time was not significantly influenced by target difficulty
and averaged 337 ms.
The data on total response time have been tested for congruence with Fitts' law for all force
levels and forms.2
The resulting bandwidths indicated the same trends as movement time and
reaction time (table 5.6). However, bandwidth will not be listed in the forthcoming analysis and
discussion to enable analysis of significance.
1Please refer to appendix B for an explanation on this notation.
2 A good fit (p > 0.96) of the data to Fitts' law was found when a zero intercept was used. However, when a
free intercept was used, the fit was poor (0.24 < p < 0.45). This supports the findings of MacKenzie (1989) that
the intercept should be zero or sma.ll.

5.6. RESULTS 33
Table 5.2: Means and standard deviations of movement time, reaction time and overshoot per-
centage by index of difficulty.
trnov {ms) treact {ms) Oversh (%)
ID (-) mean sd mean sd mean sd
1.3 504 130 335 98 3.7 5.5
1.8 598 149 330 96 6.4 7.2
2.2 685 174 347 105 7.9 9.1
Table 5.3: Means and standard deviations of movement time, reaction time, percentage of over-
shoots, perceived presence of tactile feedback and tactile quality by visual-only and combined
tactile/visual feedback.
Feedback
visual
tactilefvisual
tmov {ms}
mean sd
636 191
583 158
5.6.2 Tactile Feedback
treact {ms)
mean sd
371 124
327 88
Oversh (%)
mean sd
13.4 9.9
3.5 4.5
Presence (-)
mean sd
1.4 0.8
3.6 1.3
Quality(-)
mean sd
2.7 0.9
3.2 1.3
Movement time and reaction time were significantly affected by the addition of tactile feedback
to the targets [F(l, 11) = 82.36, p = 0.0001 and F(1, 11} =20.15, p =0.0009 respectively]. Both
movement time and reaction time decreased by approximately 50 ms with the addition of tactile
feedback.
5.6.3 Tactile Force Level
Both reaction and movement time were lower across all force levels compared to the no tac-
tile feedback target condition. A main effect for tactile force level occurred by movement time
[F(3, 9) = 30.80, p = 0.0001] and reaction time [F(3, 9) = 8.40, p = 0.0056]. The changes in
movement time and reaction time between the tactile force levels were smaller than the observed
differences between tactile and no tactile feedback (table 5.4). The difference in movement time
between the 100 and 350 mN level was significant [F(1, 11) = 10.21, p = 0.0085], as well as
the difference in reaction time between the 100 and 225 mN level [F(1, 11) =5.36, p = 0.041].
Additionally, the percentage of overshoots decreased with increasing force level from 4.4% to
approximately 3.0%. Subjective quality was highest at the 225 mN level.
Table 5.4: Means and standard deviations of movement time and reaction time by tactile force
level.
tmov (ms) treact (ms} . Oversh (%) Presence (-) Quality(-}
Force (mN) mean sd mean sd mean sd mean sd mean sd
100 591 158 332 88 4.4 4.9 2.4 1.2 3.1 1.1
225 582 159 319 84 3.0 4.6 3.8 1.0 3.6 1.3
350 576 158 329 92 3.1 4.0 4.5 0.7 2.9 1.3

Table 5.5: Means and standard deviations of movement time and reaction time by forms with
tactile feedback.
tmov (ms) treact (ms) Oversh (%) Presence (-) Quality(-)
Form mean sd mean sd mean sd mean sd mean sd
flat 580 156 323 92 2.5 4.1 4.0 1.2 2.7 1.4
hole 572 151 324 83 3.2 4.6 3.2 1.3 3.4 1.1
combined 596 167 334 89 4.8 4.7 3.6 1.3 3.5 1.1
~~~S) ~----------------------------------------------~650
620
610
600
590
580
570
- .... combined
•M•M•K• hole
+-+-·+ flat
----- overall
-·-·--~-- ......... ___.. _._·-......
----·------
............ ")« ...............~~~.~~~~.~:-~....
580 T---------------~--------------~--------------~
0 100
Max. fofce (mN)
Figure 5.3: Movement time (tm.ov) by form and total average across force level.
5.6.4 Tactile Form
The tactile form of the target had a significant effect on movement time [F{2, 10} = 20.61,
p = 0.0003]. Depending on the tactile target form, movement times varied from 572 ms to
596 ms, (table 5.5). The movement times with the combined form differed significantly with the
performance of the flat [F(l, 11) = 9.90, p = 0.0093] and hole form [F(1, 11) =35.81, p = 0.0001].
The hole form scored 3.4, the combined 3.5 and the flat 2.7 on subjective quality. Form also had
an influence on the percentage of overshoots, which ranged from 2.5% for the flat from to 4.8%
for combined form. Reaction times were not influenced by the form of the tactile target.
5.6.5 Tactile Form and Force Level
Tactile form and force level interacted to affect movement and reaction times (tables 5.6 and 5.7,
figure 5.3-5.7}. To consider the overall performance of each tactile form, at a given force level,
performance on ea.ch of the objective and subjective measures was considered. The hole tactile
fields at the 225 and 350 mN level were found to perform best. The combined tactile fields
performed significantly worse on the objective performance measures. The flat tactile fields and
the hole tactile field at the 100 mN level scored more than half a point lower on subjective quality.
5.7 Discussion
The observed results supported the hypothesis that qualitative and quantitative differences in
perceivable-tactile feedback can influence performance in a target acquisition task. The tactile

5.7. DISCUSSION
Reaction lime (ms)
380
370
380
350
340
320
310
Tadt1e form
0 100
-·
225
Max.force(mN)
............. flat
---overall
-·
....-· ...
-·-
Figure 5.4: Reaction time (trea.cd by form and total average across force level.
~~~~) r--------------------------------------------,4
3
2
0
0 100
Taclile loon
225
Max. fon::e (mN)
+·+·+- llal
-overall
350
Figure 5.5: Overshoot percentage by form and total average across force level.
35

Table 5.6: Means and standard deviations of movement time, reaction time, overshoot percentage,
perceived presence and quality of tactile feedback by force level F and form. Bandwidth BW is
also listed, but not further considered.
tmov (ms) treact (ms) Oversh (%) BW (-) Presence (-) Quality(-)
F mN) Form(-) mean sd mean sd mean sd mean mean sd mean sd
0 fiat 635 184 367 123 13 10 1.81 1.3 0.7 2.7 1.1
hole 642 190 376 131 14 10 1.77 1.4 0.9 2.9 0.9
combined 630 200 369 118 13 10 1.80 1.4 0.9 2.6 0.8
100 flat 583 152 327 91 3 5 1.99 2.9 1.1 3.2 1.2
hole 581 156 331 88 4 5 1.99 2.0 1.1 2.9 1.1
combined 607 164 338 86 6 5 1.92 2.3 1.2 3.2 l.l
225 flat 585 161 312 85 3 5 2.01 4.3 0.8 3.1 1.5
hole 566 148 320 76 3 5 2.04 3.3 1.1 3.8 1.1
combined 593 167 326 91 3 4 1.97 3.9 0.8 3.8 1.0
350 flat 570 157 329 99 1 2 2.00 4.7 0.5 1.8 0.9
hole 570 148 321 85 3 4 2.02 4.3 0.7 3.6 1.1
combined 588 169 338 89 5 5 1.95 4.4 0.8 3.4 1.2
Table 5.7: F(l, 11)-levels of movement time and reaction time between the combined form at
various force levels and the hole form at the 225 mN force level. A • footnote mark indicates
p::;; 0.01, whereas a+ footnote mark indicates p::;; 0.05.
Force (mN)
100
225
350
tmov (ms)
20.75*
5.47+
treact (ms)
11.92*
~(-) .---------------------------------------------------.5
4
3
2
0
Taelile form
100
-...,.. oomb'ned
·)f • M • K' hole
Max lOree (mN)
350
Figure 5.6: Perception of presence of tactile feedback on a 5 point rating scale by form and total
average across force leveL

5. 7. DISCUSSION 37
Qumey(-) ~-------------------------------------------------------,4
........... ""'-'": ':...:..,·: :..:...· .......
3
2
lllctile form
0 100 350
Figure 5.7: Quality of tactile feedback on a 5 point rating scale by form and total average across
force level.
force level, as a quantitative parameter, affected reaction times and movement times, while the
tactile form, as a qualitative variable, affected movement times. The subjective perception of
tactile quality was also influenced by combinations of tactile force level and tactile form. The hole
and flat form enabled subjects to decrease both movement times and reaction times across force
level as compared to the combined form. However, the hole and combined form were generally
preferred above the flat form on quality of tactile feedback.
The differences between tactile form and tactile force level, in terms of the former having an
affect only on movement times, can be attributed to adaptations in movement behaviour, as
contrasted to a combination of adaptation in movement behaviour and simple stimulus-response
reactions. Depending on the tactile form and force level, subjects were able to recognise that
the tactile field in the target area had the effect of 'catching' the pointer. Subjects appeared
to adapt their behaviour to take advantage of this phenomenon. By assessing movement times
and percentage of overshoots, it was concluded that the flat and hole form caught the pointer
significantly better than the combined form.
The fact that reaction times were not significantly influenced by the tactile form, yet were
influenced by tactile force, suggests that reaction times may reflect a simple stimulus response
relationship, as contrasted to a change in the user's behaviour. A fast information processing
channel for responding to a tactile stimulus, which requires minimal interpretation, was observed
by Frith & Done (1986). They found that subjects could react faster to tactile stimuli if only the
presence of a stimulus needed to be registered, than if the stimulus type defined the reaction.
However, the fast reaction to registration of stimulus occurrence required focussed attention,
whereas the conditional reactions did not.
In the current study, subjects had to press the space bar once they felt they were in the target
area. This simple judgement appeared to be made on the basis of recognising that the target
border area was crossed as contrasted to feeling the entire tactile form. Furthermore, the time in
performing a judgement appeared to be influenced by the tactile force level.
The flat form, which had a maximum force at the target border area, performed well on the
reaction time measure. However, the combined form, which also had a strong force at the target
border area, performed significantly worse. The combined form might have confused subjects since
two target entry points could be felt: one on the actual border and one on the transition from
the flat shape towards the hole shape. This form might have caused delays in reaction times and
limited the perception of a catching force, thus increasing movement times compared to the hole

and flat form.
The hypothesis that reaction time is related to a simple-stimulus response mechanism and that
movement times reftect a change in behaviour caused by direct intervention of the user's move-
ment through force feedback, may explain some of the findings in the study on target acquisition
using a mouse with a tactile feedback pin by Akamatsu et al. (in press). Total response time
(and bandwidth) did not vary significantly across the tactile and visual-only feedback conditions.
However, reaction times varied significantly between combined tactile/visual and visual-only con-
ditions. Although the mouse enabled a simple stimulus response relationship for target acquisition
by rising the tactile feedback pin, changes in behaviour as measured by movement time, were not
found. The pin did not have the effect of grabbing the pointer and thus movement times were not
influenced.
5.8 Conclusions
The two primary properties of tactile fields examined, tactile force level and tactile form, signifi-
cantly influenced movement times, reaction times and percentage of overshoots. Both tactile force
level and form were found to inftuence movement behaviour since subjects were aware that the
pointer would be 'caught' into the target to some degree, depending on tactile force level and
form. Additionally, reaction times were found to be dependent on tactile force level.
The changes in performance measures varied, based upon tactile force level, tactile form and their
combination. This suggests that tactile feedback, when used to improve performance in a target
acquisition task, should be optimised in terms of at least two physical properties, namely tactile
force level and tactile form. The present study demonstrated that the submodel, as discussed in
the previous chapter, contains a range of tactile fields that can influence objective performance
and subjective perception of tactile feedback. As such, the submodel can serve as a starting point
for further research into the relationships of modelled tactile fields and the inftuences of these
relations upon performance.
The distinction made in the present study between changes in behaviour versus changes in
the stimulus-response relationship suggest that tactile feedback can further improve performance
beyond simple reaction time gains. The direct intervention of tactile feedback with the subject's
movements was found to improve performance on movement trajectories without tactile feedback.
To take advantage of this performance gain, future input devices with tactile feedback should
include features which can directly inftuence the user's movements.
However, the direct intervention of the user interface with the user's movements might decrease
performance when intervention occurs at undesired moments. For example, the presence of other
(interfering) tactile fields around the target might hinder a user's movement towards the target.
The possible presence of such a factor is very important to the !PO-trackball since tactile feedback,
given by the device, is intimately coupled to the intervention with the user's movements.
Further research is needed to develop user interfaces which can optimally take advantage of direct
tactile intervention while limiting such undesired effects. Secondly, the performance gains of tactile
feedback for a task should be considered in relation to optimised visual feedback conditions, i.e.
when visual movement feedback is optimised, including the pointer speed and the visual feedback
in the target area.

Chapter 6
Performance Effects of DC-gain,
Interfering Targets and Visual
Workload
6.1 Introduction
Recently, there has been more research into the use of tactile feedback in relatively simple and
inexpensive input devices such as the joystick and the mouse. Previous studies demonstrated
performance gains when adding tactile feedback to visual feedback (e.g., Goossens (1992), Gilson
(1974), Keyson (in press) and Akamatsu et al. (in press)). Tactile feedback was found to improve
performance for target acquisition task in an open navigation environment. A target acquisition
task involves a pointing and selection action which is aimed at a target. An open navigation
environment allows users free navigation in the interface without restraining the user to certain
paths through the interface, e.g. by using menus. Open navigation is an important property of
stateless user interfaces such as MS-Windows.
Recent insights indicate that studies on these performance improvements can contain exper-
imental design factors that might (unintentionally) favor the conditions with tactile feedback.
This study was conducted to improve the validity of forthcoming studies on (both objective and
subjective) performance with tactile and visual feedback in target acquisition tasks with open
navigation.
The presence of an interfering target, the workload and the relation between control movement
of the input device and displayed movement will be discussed in the following literature overview
as factors that might influence the validity of a study on performance, concluded with a discussion
of literature on the importance of performance feedback. ·
6.2.1 Presence of an Interfering Target
The validity of an experiment on tactile feedback in user interfaces is compromised when no con-
ditions involving multiple targets are considered. Existing user interfaces display simultaneously
many possible targets for selection. For example, an application such as the file manager of SunOS
(depicted in figure 6.1) contains many candidates for selection that are all likely to be selected.
Generally, it is almost impossible to determine,·before any movement takes place, which target is
going to be selected next. Once a certain part of the movement is known, it is possible to indicate
to some degree in which area the movement will end.
Vander Made (1993; 1994) studied one-dimensional movements of a rotary dial, aimed at known
targets. A large variability in movement parameters such as position, velocity and acceleration was
found. The tested distance/width ratios for targets were 2, 4 and 8. Several formulas were derived
39

40 CHAPTER 6. DC-GAIN, INTERFERING TARGETS AND VISUAL WORKLOAD
I!J file ..._. 13 (tiona] : /biiiJift~eenders
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LJ [i ~ I D Dnew new_trackbal ::new_trackbal ~ notes notitie oohalen
g LJ LJ D ~ LJpapers.call private radio radlobras S'"'1'1e.au suuser
r<:. n
""""' r<:. r<:. ...... =
Figure 6.1: The file manager of SunOS contains many candidates for selection that are all likely
to be selected.
from theoretical backgrounds. Using the first quarter of the actual movement, these formulas tried
to predict the intended end position of the movement. Even the best fitting formula could not
predict for 75% of the cases, whether the end position was inside the known target.
Experiments on the gains of combined tactile/visual feedback can be invalidated when the
number of targets in the desired application user interface is not considered. For example, tactile
feedback might employ very strong forces that catch the pointer inside a target, thereby making
it hard to overshoot a possible target. This will improve performance when only one target is
present. However, consider a user interface with multiple possible targets. Some of these will have
to be passed during the selection of the intended target and might interfere with the movement. If
all targets share the same tactile behaviour, performance might be hindered by the tactile fields of
targets passed. It is suggested that experiments on addition of tactile feedback to visual interfaces
should include conditions where multiple similar targets are present and subjects are required to
pass a target frequently. A target which might interfere with the movement towards another target
will be called 'interfering target'.
6.2.2 Workload
To increase the validity of experiments on tactile feedback in user interfaces several levels of
workload should be studied, whereby workload is defined as the level of activity required of a
human operator to meet the performance requirements (Berchem-Simon, 1982). When several
levels of workload have been studied, a better prediction can be given of the impact of tactile
feedback in user interfaces.
The difficulty of an activity, and therefore the load on the modalities (i.e. human sensory
mechanisms, for example sight or hearing (Berchem-Simon, 1982)), can be altered by changing
the task difficulty and adding a secondary task. Addition of a secondary task can deteriorate
or improve performance. This twofold outcome on performance by the addition of a secondary
task is predicted by the theory of arousal (Duffy, 1962; Stennett, 1957). A relationship was
shown between arousal and performance which is shaped as an inverted U as shown in figure 6.2.
Arousal is defined as 'operator arousal', which refers to the amount of brain activity (Oborne,
1987). According to this theory, people perform best when moderately aroused. Bother under
and over arousal reduce performance.

6.2. LITERATURE OVERVIEW 41
High
Performance
Low
Low Arousal High
Figure 6.2: The inverted-U relationship between arousal and performance (Oborne, 1987).
Another variable which influences task performance is SR compatibility. SR compatibility is a
phenomenon thought to determine the complexity of the transformation (number of recodings}
between a stimulus (S) and a response (R) (Rogers, 1979). People tend to perform less well on
tasks that have a complex relation between stimulus and response as on tasks that have a simple
relation. The complexity of the transformation is determined by several variables, including the
relation between the stimulus and response channel and the complexity of the function through
which the appropriate response is generated for the stimulus. For example, a simple function
would be to turn the steering-wheel right for making a right turn. A more complex function would
require the steering-wheel to be turned left for a right turn. The relation between stimulus and
response channel might be more direct by enabling the driver to look in the desired direction,
thereby equating the channels for stimulus (recognising a right turn) and response (looking at the
turn}.
As is discussed by Keyson (in press}, Greenwald (1972) demonstrated that subjects could ef-
ficiently say the word 'left' or 'right' while hearing it and at the same time move a switch in
response to a visual arrow pointing either left or right. Error rates and reaction times were higher
when the subjects had to respond motorically and verbally to a verbal stimulus and visual cue
respectively. The effect of incompatible situations where the response direction is counter to the
stimulus direction has been shown in several sense modalities. Fitts and Seeger (1953) demon-
strated SR compatibility with visual stimuli, Broadbent and Gregory (1965) with tactile stimuli,
and Simon, Hinrichs and Craft (1970) with auditory stimuli.
Another influence on secondary task performance has been identified, beside the level of arousal
and SR compatibility. The utilisation of an extra modality was found to enable the human
system to process more information. Burke (1980) tested two simultaneous single-dimensional
compensatory tracking tasks, one with the left hand and one with the right hand. The primary
task was performed with the left hand using a visual display or a quickened kinesthetic-tactual
(KT) display (also employed by Gilson (1974)). The right-handed tracking was carried out only
with a visual display. Although in the single-t~k condition performance of the two hands was
equal, in the dual-task condition usage of the KT display resulted in more accurate and faster
total task performance. This effect can not be attributed to SR compatibility since the increase in
performance was not present in the single-task condition. The utilisation of the tactile modality
beside the visual modality enabled the human system to process more information.
A similar result was found by Keyson (in press). Keyson tested the replication of movement

1994 Afstudeerverslag IPO

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1994 Afstudeerverslag IPO