Kortum P. (ed.) HCI Beyond the GUI. Design for Haptic, Speech, Olfactory, and Other Nontraditional Interfaces

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studies on perception of high-frequency vibrations and surface texture, the tactile

pathway serves as the primary information channel, whereas the kinesthetic

information is supplementary. Early tactile perception studies concluded that

the spatial resolution on the finger pad is about 0.15 mm for localization of a point

stimulus (Loomis, 1979) and about 1 mm for the two-point limen (Johnson & Phil-

lips, 1981). Other parts of the body have much less spatial resolution. For exam-

ple, the palm cannot discriminate between two points that are less than 11 mm

apart (Shimoga, 1993).

A related measure, the successiveness limen (SL), is the time threshold for

which subjects are able to detect two successive stimuli. An approximate SL value

for the mechanoreceptors is 5 msec, with a required interval of 20 msec to

perceive the order of the stimuli. The human threshold for the detection of vibra-

tion of a single probe is reported to be about 28 dB for the 0.4- to 3-Hz range. An

increase in level of 6 dB represents a doubling of amplitude, regardless of the

initial level. A change of 20 dB represents a change in amplitude by a factor of 10.

This threshold is shown to decrease at the rate of 5 dB per octave in the 3-

to 30-Hz range, and at the rate of 12 dB per octave in the 30- to about 250-Hz

range, with an increase for higher frequencies (Rabinowitz et al., 1987; Bolanowski

et al., 1988).

2.1.4 Sensory Motor Control

In addition to tactile and kinesthetic sensing, the human haptic system incl udes

a motor subsystem. Exploratory tasks are dominated by the sensorial part of the

sensory motor loop, whereas manipulation tasks are dominated by the motor

part (Jandura & Srin ivasan, 1994). The key aspects of human sensorimotor con-

trol are maximum force exertion; force-tracking resolution; compliance, force,

and mass resol ution; finger and hand mechanical impedance; and force control

bandwidth.

Maximum Force Exertion

A maximum grasping force of 400 N for males and 228 N for females was

measured in a study by An and coworkers (An et al., 1986). In a study on maxi-

mum force exertion by the pointer, index, and ring fingers, it was found that

the maximum force exerted by the pointer and index fingers was about 50 N,

whereas the ring finger exerted a maximum force of 40 N (Sutter et al., 1989).

These forces were found to be constant over 0 to 80 degrees of the metacarpal

(MCP) joint angle. This work was later extended to include the proximal-

interphalangeal (PIP) joints and MCP joints, as well as the wrist, elbow, and shoul-

der (with arm extended to the side and in front) (Tan et al., 1994). Note that the

maximum force exertion capability is dependent on the user’s posture. It was

found that maximum force exertion grows from the most distal joint in the palm

to the most proximal joint (shoulder). In addition, it was found that controllability

2 Haptic Interfaces

over the maximum force decreased from the shoulder to the PIP joint. In order to

ensure user safety, a haptic interface should never apply forces that the user

cannot successfully counter.

Sustained Force Exertion Prolonged exertion of maximum force leads to

fatigue. Fatigue is an important consideration when designing feedback for appli-

cations like data visualization where force feedback may be present for extended

periods of time. Wiker and colleagues (1989) performed a study of the relationship

between fatigue during grasping as a function of force magnitude, rest duration,

and progression of the task. The tests showed a direct correlation between magni-

tude of discomfort and magnitude of pinch force. The work-versus-rest ratio was not

found to be important for low forces but was effective in reducing fatigue for high

pinch forces.

Force-Tracking Resolution

Force-tracking resolution represents the human ability to control contact forces in

following a target force profile. Srinivasan and Chen (1993) studied fingertip force

tracking in subjects using both constant and time-varying (ramp and sinusoid)

forces. For some participants, a computer monitor provided a display of both the

actual and target forces. Subjects also performed the tests under local cutaneous

anesthesia. It was found that when no visual feedback was available, the absolute

error rate increased with target magnitude. When visual feedback was present, the

error rate did not depend on target magnitude.

Compliance Resolution

Compliance, or softness, resolution is critical in certain applications such as train-

ing for palpation tasks or telesurgery, since many medical procedures require

accurate discrimination of tissue properties. The following discussion presents a

short summary of the literature on compliance resolution both with and without

the presence of additional visual or auditory clues. If a haptic interface is to be

used for exploratory tasks that require discrimination among objects based on

their compliance, then designers should ensure that the simulated virtual objects

appear sufficiently different to the human operator.

Human perception of compliance involves both the kinesthetic and tactile

channels since spatial pressure distribution within the contact region sensed

through the tactile receptors plays a fundamental role in compliance perception.

However, for deformable objects with rigid surfaces, the information available

through the tactile sense is limited and kinesthetic information again becomes

the dominant information channel. In such cases, human perceptual resolution

is much lower than the cases for compliant objects with deformable surfaces

(Srinivasan & LaMotte, 1995). In studies involving deformable objects with rigid

surfaces, Jones and Hunter (1990, 1992) reported the differential thresholds for

stiffness as 23 percent. Tan and colleagues (1992, 1993) observed that for such

2.1 Nature of the Interface

objects held in a pinch grasp, the JND for compliance is about 5 to 15 percent

when the displacement range is fixed, and 22 percent when the displacement

range is randomly varied. Moreover, they reported a minimum stiffness value of

25 N/m (Newtons per meter) for an object to be perceived as rigid (Tan et al., 1994).

In further studies, Tan and coworkers (1995) investigated the effect of force

work cues on stiffness perception and concluded that JND can become as high

as 99 percent when these cues are eliminated. Investigating the effect of other

cues on compliance perception, DiFranco and colleagues (1997) observed the

importance of auditory cues associated with tapping harder surfaces and con-

cluded that the objects are perceived to be stiffer when such auditory cues are

present.

In a similar study, Srinivasan and coworkers (1996) reported dominance

vision in human stiffness perception. In related studies, Durfee et al. (1997) inves-

tigated the influence of haptic and visual displays on stiffness perception, while

O’Malley and Goldfarb (2004) studied the implications of surface stiffness for size

identification and perceived surface hardness in haptic interfaces. Observing

the importance of the initial force rate of change in stiffness perception,

Lawrence and colleagues (2000) proposed a new metric for human perception of

stiffness, called rate hardness.

Force Resolution

In related experiments, human perceptual limitations of contact force perception—

when the kinesthetic sense acts as the primary information channel—have been

studied. The JND for contact force is shown to be 5 to 15 percent of the reference

force over a wide range of conditions (Jones, 1989; Pang et al., 1991; Tan et al.,

1992). Accompanying experiments revealed a JND value of about 10 percent for

manual resolution of mass (Tan et al., 1994), while a JND value of about 34

percent has been observed for manual resolution of viscosity (Jones & Hunter,

1993). Recently, Barbagli and colleagues (2006) studied the discrimination thresh-

olds of force direction and reported values of 25.6 percent and 18.4 percent for

force feedback only and visually augmented force feedback conditions, respec-

tively. Special attention is required when designing feedback for applications like

grasping and manipulation, where subtle changes in force can be important, such

as in making the difference between holding and dropping an object in the virtual

environment.

Mechanical Impedance

The impedance of the human operator’s arm or finger plays an important role in

determining how well the interface performs in replicating the desired contact

force at the human–machine contact point. Hajian and Howe (1997) studied the

fingertip impedance of humans toward building a finger haptic interface. Over

all subjects and forces, they estimated the equivalent mass to vary from 3.5 to

8.7 g, the equivalent damping from 4.02 to 7.4 Ns/m, and stiffness from 255 to

2 Haptic Interfaces

1,255 N/m. It was noted that the damping and stiffness increased linearly with

force. In similar work, Speich and colleagues (2005) built and compared two-

and five-DOF models of a human arm toward design of a teleoperation interface.

Sensing and Control Bandwidth

Sensing bandwidth refers to the frequency with which tactile and/or kinesthetic

stimuli are sensed, and control bandwidth refers to the frequencies at which the

human can respond and voluntarily initiate motion of the limbs. In humans, the

input (sensory) bandwidth is much larger than the output bandwidth. As noted

earlier, it is critical to ensure that the level of haptic feedback is sufficient for task

completion while being comfortable for the user. In a review paper, Shimoga

showed that the hands and fingers have a force exertion bandwidth of 5 to

10 Hz, compared to a kinesthetic sensing bandwidth of 20 to 30 Hz (Shimoga,

1992). Tactile sensing has a bandwidth of 0 to 400 Hz. Keeping this in mind, if

we design an application that requires repetitive force exertion by the user, to

guarantee user comfort the required rate should not be more than 5 to 10 times

a second. Similarly, any kinesthetic feedback to the user should be limited to 20

to 30 Hz.

2.2

TECHNOLOGY OF THE INTERFACE

Haptic interfaces are a relatively new technology, with increased use for human

interaction with virtual environments since the early 1990s. A primary indicator

of the proliferation of haptic devices is the number of companies that now market

devices, including Sensable Technologies, Immersion, Force Dimension, Quanser,

and Novint, among others. The commercialization of haptic devices is due primar-

ily to technological advances that have reduced the cost of necessary components

in haptic systems, including materials, actuation, sensing, and computer control

platforms.

Novel materials, such as carbon fiber tubing, have enabled the design and fab-

rication of light-weight yet stiff kinematic mechanisms that are well suited to the

kinesthetic type of haptic display. Power-dense actuators, such as brushless DC

motors, have allowed for increased magnitude force output from haptic devices

with minimal trade-offs in terms of weight. However, it should be noted that

actuation technology is still a key limitation in haptic device design, since large

forces and torques obtained via direct drive actuation are often desired, while still

achieving minimal inertia (mass) in the mechanism. Improved sensor technology

has also enabled an increase in the availability of high-quality haptic interface

hardware. The key requirement of sensors for haptic applications is high resolu-

tion, and many solutions such as optical encoders and noncontact potentiometers

are providing increased resolution without compromising the back-drivability of

haptic devices due to their noncontact nature.

2.2 Technology of the Interface

The final set of technological advances is in the area of computational plat-

forms. First, data acquisition systems, which enable transformation from analog

and digital signals common to the sensors and actuators to the digital computation

carried out by the control computer, are achieving higher and higher resolutions.

Second, real-time computation platforms and increasing processor speeds are

enabling haptic displays (typically rendered at a rate of 1,000 Hz) to exhibit

increasingly greater complexity in terms of computation and model realism. This

in turn broadens the range of applications for which haptic feedback implementa-

tion is now feasible. Finally, embedded processors and embedded computing are

enabling haptic devices to be more portable.

2.3

CURRENT INTERFACE IMPLEMENTATIONS

Over the last several years, a variety of haptic interfaces have been developed for

various applications. They range from simple single-DOF devices for research

(Lawrence & Chapel, 1994) to complex, multi-DOF wearable devices (Frisoli et al.,

2005; Kim et al., 2005; Gupta & O’Malley, 2006). DOF refers to the number of vari-

ables required to completely define the pose of a robot. A higher-DOF device has a

larger workspace—the physical space within which the robot end point moves—

as compared to a low-DOF device of similar size. Haptic devices are also used in

various applications (Hayward et al., 2004). For instance, haptic interfaces have

been employed for augmentation of graphical user interfaces (GUIs) (Smyth &

Kirkpatrick, 2006), scientific data visualization (Brooks et al., 1990), enhancement

of nanomanipulation systems (Falvo et al., 1996), visual arts (O’Modhrain, 2000),

CAD/CAM (Nahvi et al., 1998; McNeely et al., 1999), education and training, partic-

ularly surgical training (Delp et al., 1997), master interfaces in teleoperation (Kim

et al., 2005), rehabilitation (Bergamasco & Avizzano, 1997; Krebs et al., 1998), and

the scientific study of touch (Hogan et al., 1990; Weisenberger et al., 2000).

The PHANToM desktop haptic interface (Sensable Technologies), shown in

Figure 2.3, is probably the most commonly used haptic interface. It is a pen- or

stylus-type haptic interface, where the operator grips the stylus at the end of the

robot during haptic exploration. The PHANToM desktop device has a workspace

of about 160 W  120 H  120 D mm. The device provides feedback to the opera-

tor in three dimensions with a maximum exertable force capability of 1.8 foot-

pounds (lb

) (7.9 N) and a continuous exertable force capability (over 24 hours)

of 0.4 lb

(1.75 N). A number of device models are available that vary in workspace

and force output specifications. Several other haptic interfaces are commercially

available, such as the six-DOF Delta haptic device (Force Dimension), the three-

DOF planar pantograph (Quanser), and the force feedback hand controller (MPB

Technologies) (Figure 2.3).

The common feature of most commercially available haptic devices is that

they are point contact devices, in that the end point of the robot is mapped to a

2 Haptic Interfaces

FIGURE

2.3

Selected commercially available haptic interfaces.

(a) PHANToM desktop, (b) six-DOF Delta haptic interface, (c) three-DOF

planar pantograph, and (d) force feedback hand controller. (Courtesy of

(a) SensAble Technologies, Inc.; (b) Francois Conti; (c) Quanser Inc.;

and (d) MPB Technologies Inc.

2.3 Current Interface Implementations

position in the virtual environment and forces are applied back to the user at the

same point. Thus, within the virtual environment, the user can interact with only

one point. One can think of this as being similar to interacting with objects in the

real world with the aid of tools like a pen, screwdriver, or scalpel. Even with this

limitation, these types of devices have been employed in applications such as sci-

entific visualization, augmentation of GUIs, CAD, and psychophysical studies. The

choice of a specific device depends on the desired workspace and DOF, the type of

force feedback desired, and the magnitude of forces to be displayed. For example,

the PHANToM can move within the three-dimensional (3D) physical space, but

can apply forces only on the user’s hands. In comparison, the three-DOF panto-

graph is restricted to moving in a plane, but can apply a torque or wrench to

the user’s hand in addition to forces in the two planar directions.

In the following subsections, we take a closer look at selected current imple-

mentations of haptic interfaces. The examples presented have been chosen to dem-

onstrate essential features, and do not necessarily represent the state of the art but

rather basic features of their respective categories. These devices demonstrate the

wide range of technologies involved in haptics.

2.3.1 Nonportable Haptic Interfaces

Haptic Joysticks

Joysticks are widely used as simple input devices for computer graphics, indus-

trial control, and entertainment. Most general-purpose joysticks have two DOF

with a handle that the user can operate. The handle is supported at one end by

a spherical joint and at the other by two sliding contacts (Figure 2.4). Haptic joy-

sticks vary in both mechanical design and actuation mechanisms. Adelstein and

Rosen (1992) developed a spherical configuration haptic joystick for a study of

hand tremors. Spherical joysticks, as the name implies, have a sphere-shaped

workspace. Cartesian joysticks, on the other hand, have two or three orthogonal

axes that allow the entire base of the handle to translate. An example is the

three-DOF Cartesian joystick comprising a moving platform that slides using

guiding blocks and rails proposed by Ellis and colleagues (1996). The moving block

supports an electric motor that actuates the third DOF (rotation about the

-axis).

This Cartesian joystick (Figure 2.5) has a square-shaped planar workspace, and

each axis is actuated using DC motors and a cable transmission.

Other examples of haptic joysticks include a four-DOF joystick based on the

Stewart platform (Millman et al., 1993) and a magnetically levitated joystick

(Salcudean & Vlaar, 1994). The magnetically levitated joystick has no friction at

all and is particularly suited for display of small forces and stiff contact.

These haptic joysticks are point contact devices, and each type varies accord-

ing to workspace shape and size. While the spherical joystick can be used with just

wrist movements, Cartesian joysticks require the user to employ other joints of

2 Haptic Interfaces

the arm, like the elbow or the shoulder. Consequently, the workspace and force

output of Cartesian joysticks can be greater than that of similarly sized spherical

models. Note that most commercially available force feedback joysticks, typically

marketed for computer gaming applications, lack the quality necessary to achieve

Handle

Swing arm

Axis #1

Axis #2

Spherical

joint

Potentiometer

FIGURE

2.4

Two-DOF slotted swing arm joystick.

Source

: From Adelstein and Rosen (1992).

FIGURE

2.5

Three-DOF Cartesian joystick.

The joystick comprises a central stage that moves using a guiding block and rails.

Source

: From Ellis et al. (1996).

2.3 Current Interface Implementations

high-quality feedback for exploratory or manipulative tasks. While they may suf-

fice to provide haptic cues that can be detected, high-quality hardware and a fast

computer platform are necessary to ensure proper discrimination of cues.

Pen-Based Masters

Pen-based haptic devices allow interaction with the virtual environment through

tools such as a pen (or pointer) or scalpel (in surgical simulations). These devices

are compact with a workspace larger than that of spherical and magnetically levi-

tated joysticks and have three to six DOF. The best-known example of a pen-based

haptic interface is the PHANToM, mentioned earlier in this section. Originally

developed by Massie and Salisbury (1994), the PHANToM is an electrically actu-

ated serial-feedback robotic arm that ends with a finger gimbal support that can

be replaced with a stylus (Figure 2.6). The gimbal orientation is passive and the

serial arm applies translational forces to the operator’s fingertip or hand. A six-

DOF interface that can apply forces as well as torques to the operator is presented

Table

attachment

Finger attachment

Thimble

gimbal

Cable and pulley

Force feedback arm

Position encoder

Analog control

lines

DC electrical

actuator

PHANT

FIGURE

2.6

Schematic of the PHANToM desktop haptic interface.

Source

: From Massie and Salisbury (1994).

2 Haptic Interfaces

in Iwata (1993), extending the complexity of force and torque interactions

between a human operator and the remote or virtual environment.

Floor- and Ceiling-Mounted Interfaces

Generally, floor- and ceiling-mounted interfaces are larger and more complex and

expensive than desktop devices. They have a large force output, and as a result

user safety becomes critical. This is especially true for exoskeletons where the

operator is inside the device workspace at all times. Figure 2.7 shows one of the

first generalized master arms that was developed at the National Aeronautical

and Space Administration (NASA) Jet Propulsion Laboratory (JPL) (Bejczy &

Salisbury, 1980). It is a six-DOF interface with a three-axis hand grip that slides

and rotates about a fixed support attached to the floor. The hand grip can apply

forces up to 9.8 N and torques up to 0.5 N/m. The JPL device is another example

of a point contact haptic interface where the forces are applied at the user’s hands.

As compared to joysticks or desktop devices, though, it provides a much larger

work volume with greater force output capabilities, coupled with greater freedom

of arm movement. These larger devices are useful for remotely manipulating

large robotic manipulators like those used in space.

An example of a grounded exoskeletal haptic interface is the MAHI arm exo-

skeleton (Figure 2.8) built at Rice University (Gupta & O’Malley, 2006; Sledd &

O’Malley, 2006). This five-DOF exoskeleton was designed primarily for rehabilita-

tion and training in virtual environments. The device encompasses most of the

human arm workspace and can independently apply forces to the elbow, forearm,

or wrist joints. Note that this is no longer a point contact device, but can provide

independently controlled feedback to various human joints. This feature makes it

extremely suitable as a rehabilitation interface that allows the therapist to focus

treatment on isolated joints.

FIGURE

2.7

Six-DOF JPL arm master.

Two hand controllers used by a human operator.

Source

: From O’Malley and

Ambrose (2003).

2.3 Current Interface Implementations