Identification of Vibrotactile Patterns: Building Blocks for Tactons

Mojtaba Azadi and Lynette Jones*

Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA USA

ABSTRACT

Vibrotactile stimuli vary along a number of dimensions including

frequency, amplitude, waveform and temporal profile all of which

can be varied to create tactons. The objective of the present

experiment was to measure tactile pattern recognition using eight

vibrotactile stimuli that varied with respect to frequency,

amplitude and pulse duration. An absolute identification paradigm

was used in which each stimulus was presented eight times to the

index finger or forearm and participants had to identify the visual

image associated with the tacton. The results from the experiment

indicated that in the absence of spatial cues, tactons were

relatively difficult for participants to identify, with an overall

mean recognition rate of 57% correct and an IT of 1.72 bits.

However, there were significant differences in the identification

rates among the tactons, with mean scores ranging from 30% to

83% correct. Tactons created using higher frequencies and

amplitudes were easier to identify than those with lower

frequencies and amplitudes. Surprisingly, there was no difference

between the finger and the forearm in tacton identification. The

dimension that appeared to be most difficult to encode was

amplitude, as reflected in the patterns of misidentification in the

confusion matrices. These findings indicate that the specific

dimensions and stimulus ranges selected to create tactons can

profoundly affect the ability to identify tactile patterns and that

differences in spatial and temporal acuity across the skin are not

predictive of these abilities.

KEYWORDS: tactile display, touch, vibration

INDEX TERMS: H1.2 [Model and Principles]: User/Machine

System; H5.2 [Information Interfaces and Presentation]: User

Interfaces – Theory and methods; User-centered design

1 INTRODUCTION

Tactile displays have been shown to be effective in presenting

spatial information to users that assists in navigation in unfamiliar

environments or directs attention in visually complex scenes

[1][2][3]. In these applications the spatial sequence of activation

of a set of motors in a display or the location of a single activated

motor conveys the relevant cue. If tactile displays are to be used

to convey messages of some complexity then a vocabulary is

required, in which each tactile word or tacton is associated with a

specific concept or instruction. The development of such a

vocabulary should be based on a conceptual framework that

specifies which stimulus parameters are readily distinguishable

and how they can be combined optimally [2]. Vibrotactile signals hold particular promise for this application

because they are multi-dimensional and the dynamic ranges of the

various stimulus parameters are larger than those available for electrotactile stimuli. The four basic dimensions of vibrotactile stimuli are frequency, amplitude, waveform, and temporal profile, and these define any vibration delivered to the skin. The frequencies to which mechanoreceptors in the skin respond range from 0.4 to 1000 Hz, and at the frequencies to which the skin is most sensitive (150-300 Hz), displacements as small as 0.03 µm can be detected [4][5]. In comparison to the ear which is exquisitely sensitive to timbre, the skin is not particularly sensitive to different waveforms (e.g. a sine wave as compared to a monophasic and tetraphasic pulse) [6], although various waveforms (sine, square and sawtooth waves) have been used effectively to create tactile textures [7]. Brown et al. [8] also showed that amplitude modulation of sinusoids could be used to create tactile signals that perceptually varied in roughness and that roughness increased as the modulation frequency decreased. The temporal profile of a vibrotactile stimulus includes aspects such as the pulse duration (typically 80-500 ms), the repetition rate of the pulses, and the number of pulses presented. Temporal patterns can be created by varying the pulse repetition rate and as with the auditory modality these are perceived as rhythms and can be used effectively to encode aspects of a signal such as urgency or proximity [9][10].

A further factor that influences the design of tactons is the performance of the actuators used in the tactile display. The limited bandwidth of most actuators mounted on the body means that it is not possible to make full use of the range of frequencies people can perceive or to vary the waveform of the signal [8]. In addition for eccentric mass or dc pager motors it is not possible to control the frequency and amplitude of vibration independently. These motors are also limited by the spin-up time after a voltage is applied to the motor, which can be in the order of 50-100 ms before maximum vibration amplitude is reached [11][12][13]. The more recently available small linear resonant actuators use a movable mass, permanent magnet, voice coil and spring to generate vibrations. With these motors it is possible to control the amplitude and frequency of vibration independently and more complex waveforms can be generated than is possible with eccentric rotating mass actuators [14]. In addition these motors have fast rise times of less than 5 ms which is an important feature given the temporal resolution of the skin.

There have been several studies of tactons created by varying various parameters of vibrotactile stimuli which have been informative in terms of identifying those stimulus dimensions that are most readily identifiable and those that are easily confused. In general the location of tactile stimulation has been shown to be a very effective component of a tactile pattern that users easily encode. However, the spatial sequence of motor activation in an array does influence identification. Jones et al. [2] found that tactile patterns presented in a 3-by-3 array of motors mounted on the forearm were easier to identify if they involved sequential activation of the motors in a transverse (mediolateral) direction as compared to the longitudinal (distal-proximal) direction, even though the distance between the motors was the same in both directions. Patterns that combined both directions of motor activation were even harder to identify [15]. These anisotropies of

* Email: ljones@mit.edu

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IEEE World Haptics Conference 201314-18 April, Daejeon, Korea978-1-4799-0088-6/13/$31.00 ©2013 IEEE

tactile perception on the arm have been observed in other tasks such as gap detection thresholds [16] and the perceived distance between two points of stimulation [17]. They do not occur when tactile patterns are presented on the back [15], indicating that tactile anisotropies are site specific and so tactons must be evaluated on each body site being considered for communication.

A number of metrics have been used to evaluate the accuracy with which participants can perceive sets of tactons, ranging from percent correct scores to measures of information transfer (IT). The latter measures the increase in information about the signal transmitted from knowledge of the signal received and has the advantage that it can be compared across different stimulus sets [18][19]. It is usually independent of task conditions such as the number of stimuli in the identification task and can increase with the dimensionality of the stimuli. Estimates of IT for tactile patterns presented on displays mounted around the waist, and on the forearm and back range from 2.2 to 2.8 bits [15][20]. Higher values of IT have been achieved with tactile patterns presented to the hand although with estimates ranging from 4-6 bits the superior spatial and temporal acuity of the hand is not associated with dramatically improved perceptual performance [21][22].

Many of the proposed applications of tactile displays involve presenting cues to a single site such as the index finger or thumb in contact with a screen on a mobile device or other computing platform. In this context it is important to know how accurately people can identify tactile patterns when only a single location is receiving information and to determine how variations in different stimulus parameters influence identification. These parameters need to be studied within a framework that systematically varies stimulus values orthogonally and redundantly so that the relations among dimensions can be specified precisely from a perceptual perspective. The primary objective of the present experiment was to create a set of tactile patterns that did not use spatial cues as a stimulus dimension and determine the accuracy with which these could be identified at two sites typically considered for presenting vibrotactile information: the tip of the index finger and the forearm.

2 EXPERIMENT

The experiment was an absolute identification study in which

participants had to identify which of eight tactile patterns that

varied with respect to frequency, amplitude and pulse duration

had been presented.

2.1 Participants

Eight normal healthy participants, four males and four females,

ranging in age from 20 to 37 years old (mean: 26 years)

participated in the experiments. They were all right-handed. They

had no known abnormalities of the skin or peripheral sensory or

vascular systems. None of the participants had any significant

experience in tactile pattern recognition. All subjects signed an

informed consent form that was approved by the MIT Committee

On the Use of Humans as Experimental Subjects.

2.2 Apparatus

The motors used in these experiments were C2 tactors

(Engineering Acoustics, Inc.) which are voice coil motors 30-mm

in diameter, 8-mm deep with a mass of 17 g. The diameter of the

moving element is 7 mm which is centered in a hole 9-mm in

diameter which provides a stationary surround with a 1-mm gap.

The moving element protrudes 0.5 mm above the surface of the

surround and so makes firm contact with the skin and the

surround serves to dampen the surface waves from the vibrating

contactor. The C2 tactor has a resonant frequency of 250 Hz. An

acrylic fixture was machined to hold the C2 tactor which was then

mounted on the bench (for the finger experiments) or on a stand

with a movable platform that could be lowered onto the forearm

and held in place. The tactors were controlled using a multi-

channel, portable controller unit (ATC3.0, Engineering Acoustics,

Inc.) A MATLAB (MathWorks, Inc) code was developed to send

the subjects’ responses to the controller using the DLL libraries of

the controller.

2.3 Tactile Patterns

The tactile patterns were designed by varying three stimulus dimensions (frequency, amplitude and pulse duration) each of which had two values to give a total of eight patterns as illustrated in Fig. 1. Frequency was set at 50 or 200 Hz, and controller gain was set at 1 or 2. As the amplitude of the signal produced by the C2 tactor varies with frequency, the amplitude of vibration was measured using a precision optical reflective sensor (HEDS-1500, Agilent Technologies). The peak-to-peak amplitude of tactons 1 and 5 was 53 µm, for tactons 3 and 7 it was 82 µm, for tactons 2 and 6 it was 110 µm and for tactons 4 and 8 it was 164 µm.

Each tacton consisted of five short signals each 500 ms long which gave a total duration of 2.5 s. Each 500 ms signal was pulsed on for either 450 ms or 250 ms. Fig. 1 provides a schematic illustration of the eight patterns that participants used to indicate their responses. The waveforms depicted were not intended to be accurate in terms of the actual frequencies, amplitudes and duration of the stimuli delivered but served to emphasize the differences among the tactile patterns. Tactons numbered 1-4 had a pulse duration of 450 ms and those numbered 5-8 had a pulse duration of 250 ms. In Fig. 1, tactons 1, 2, 5 and 6 had a gain of 1, and those numbered 3, 4, 7, and 8 had a gain of 2. However, as indicated above these gain values resulted in different amplitudes when the frequency of the signal changed. The frequency of tactons 1, 3, 5 and 7 was 50 Hz, whereas tactons numbered 2, 4, 6 and 8 had a frequency of 200 Hz. The number of patterns chosen was based on earlier research with eight tactons that were presented at different locations on the body. In those studies the percent correct scores ranged from 30% to 90% [2]. Pilot studies were also conducted to determine which stimulus values yielded tactons that were readily discriminated when presented in pair-wise comparisons.

Figure 1. Visual depiction of eight patterns (tactons) which varied

with respect to frequency, amplitude and pulse duration.

2.4 Procedure

Participants placed their left index finger on the C2 tactor or the

C2 tactor was lowered onto the volar surface of the left forearm

100 mm from the crease in the wrist. In both conditions, light

contact was maintained between the tactor and the skin. The

experimental protocol and dimensions used to create the tactile

patterns were explained to participants. Headphones that

presented white noise were worn throughout the experiment so

that auditory cues from the motors could not be used to facilitate

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identifying the patterns. A visual depiction of each stimulus was

presented on the computer screen in front of the subject (see Fig.

1); in the familiarization period the subject selected each stimulus

using a computer mouse and the stimulus was then presented to

the finger (or forearm) while participants looked at the visual

display. After this, there was a series of practice trials in which

tactons were presented and participants had to indicate which

pattern they felt. Feedback was provided after each response.

After the practice session the experiment began. Each stimulus

was presented eight times at each location, giving a total of 128

trials. After each stimulus was presented, participants indicated

their responses by selecting the number associated with the visual

pattern on the screen. There was no time limit imposed on

participants and on most trials participants made their responses

within a couple of seconds. A rest break was provided when

requested. No feedback regarding the correctness of the response

was provided during the main experiment. The order of stimulus

presentation was randomized across participants.

3 RESULTS

The data were analyzed initially in terms of the percentage of

correct responses for each tacton as a function of the body site

tested. There was considerable variability across participants with

individual mean scores averaged across all tactons ranging from

28% to 78% correct. There was no clear pattern of an enhanced

ability to identify patterns when presented on the finger as had

been predicted on the basis of its superior tactile acuity. Of the

eight participants tested, four obtained higher scores on the finger

and four on the forearm. The correlation between the participants’

scores on the finger and forearm was not significant (r=0.27,

p>0.05).

The group mean results are illustrated in Fig. 2 where it can be seen that there is marked variability for both the finger and forearm in terms of the accuracy with which the various tactons could be identified. The overall group mean identification rates were 55% correct for the finger and 58% correct for the forearm and for the individual tactons the mean scores ranged from 30% to 83% correct. A repeated-measures two-way ANOVA with tacton and site as factors revealed that there was a significant difference in scores for the various tactons (F(7,49)=5.01, p=0.007) and that the interaction between tacton and site was also significant (F(7,49)=4.29, p=0.017). There was no effect of body site.

Figure 2. Group mean percent correct scores for each tacton

presented on the finger (white bars) and forearm (black bars).

Standard deviations are shown.

The interaction effect reflects the finding that the ability to identify tactons varied at the two sites. For the finger, tacton 4 was identified most consistently (70% of the trials), whereas tactons 2

(80%) and 6 (83%) were identified most often on the forearm. The latter two tactons had similar amplitudes and frequencies and varied with respect to pulse duration. For both the finger and forearm tacton 7 was the most difficult to identify (50 Hz, gain of 2, 250 ms pulse duration), and as the confusion matrices reveal (Tables 1 and 2) it was very consistently misidentified as tacton 5 which was similar in all dimensions except amplitude.

When identification is considered with respect to the three dimensions used to create tactons (frequency, amplitude, pulse duration), it is clear that identification was easiest for tactons created with the higher frequency of 200 Hz and greater amplitudes. The mean identification score for the higher frequency tactons was 68% (range: 63.5-70%) as compared to 44% (range: 32.5-53%) for the lower frequency tactons. Similarly the tactons with higher amplitudes (110 and 164 µm) were easier to identify (68% correct) than those with lower amplitudes (53 and 82 µm) (46% correct). The identification of the tactons when grouped according to the three dimensions is shown in Fig. 3, with the data collapsed across the sites tested.

Figure 3. Group mean percent correct scores for tactons grouped

by stimulus dimension. The white bars are the lower stimulus

magnitudes (50 Hz, amplitude of 53 and 82 µm, and 250 ms) and

the black bars are the larger magnitudes (200 Hz, amplitudes of

110 and 164 µm, and 450 ms) for each dimension.

Table 1. Confusion matrix for the finger with scores out of the total

of the 64 trials presented for each tacton. The highlighted diagonal

represents correct responses.

Subjects’ responses

Tacton 1 2 3 4 5 6 7 8

1 38 8 12 0 4 1 1 0

2 0 30 1 26 0 4 0 3

3 17 6 32 0 7 1 1 0

4 0 11 0 45 0 2 0 6

5 4 3 6 0 36 8 7 0

6 0 9 1 3 0 36 2 13

7 4 3 2 0 25 6 24 0

8 0 3 0 8 0 13 1 39

The confusion matrices of the participants’ responses (Tables 1 and 2) indicate which tactons were most frequently confused and provide cues as to the dimensions of tactile patterns participants attended to and which properties may have been difficult to encode. The pattern of errors is generally similar for the two sites tested and the errors are typically symmetric; that is if tacton 2 was most often misidentified as tacton 4, then tacton 4 was most often misidentified as tacton 2. The errors depicted in the Tables suggest that the dimension most difficult for subjects to encode was amplitude. When this defined the difference between two

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tactons, for example tactons 6 and 8, errors predominantly involved selecting the tacton with the same frequency and pulse duration as the stimulus presented but different amplitude.

Table 2. Confusion matrix for the forearm with scores out of the

total of the 64 trials presented for each tacton. The highlighted

diagonal represents correct responses.

Subjects’ responses

Tacton 1 2 3 4 5 6 7 8

1 30 0 12 0 17 0 5 0

2 0 51 0 6 0 4 0 3

3 19 0 19 1 13 0 12 0

4 0 12 0 45 0 1 0 6

5 15 0 2 0 31 1 15 0

6 0 5 0 0 0 53 0 6

7 6 0 9 0 22 2 25 0

8 0 0 0 4 0 12 0 48

The confusion matrices from each participant were used to calculate the information transfer (IT). From the confusion matrix the information transfer associated with the two sites tested was calculated. IT values determine how many “bits” of information subjects can distinguish from the set of stimuli presented and indicate the maximum number of tactons that can be identified without error. For each stimulus-response pair (Si,Rj) the IT was calculated by:

, (1)

where P(Si/Rj) is the proportion of correct responses, Rj for Si, and

P(Si) is the probability of stimulus Si [19]. The average IT value

for each location was calculated using the equation:

, (2)

where P(Si,Rj) is the probability of response Rj given Si, and P(Rj)

is the probability of Rj. The maximum IT is called the Information

in Stimulus (IS) which is the total number of bits contained in the

stimuli or the IT value for 100% accuracy, and can be calculated

more simply using the equation:

IS

(3)

The IS, or maximum IT, for this set of stimuli is 3 bits, meaning

that there are 3 total possible bits of information to be transferred from the eight stimuli that have to be identified. The calculation 2IT gives the maximum number of tactons that can be correctly identified, although it is not generally an integer [19]. The IT values ranged from 1.30 to 2.33 across participants and for the group the mean values were 1.67 and 1.76 bits for the finger and forearm respectively. This is interpreted as indicating that for this set of eight tactons 3.18 and 3.39 patterns can be correctly identified.

4 DISCUSSION

The results from this experiment indicate that in the absence of

spatial cues, tactons were relatively difficult for participants to

identify, with an overall mean recognition rate of 57% correct and

an IT of 1.72 bits. There were, however, significant differences in

the identification rates among the tactons, which provide cues as

to which stimulus dimensions participants found easiest to

encode. Tactons created using higher frequencies (200 Hz) were

easier to identify than those with lower frequencies (50 Hz), and

when tactons were misidentified the errors usually involved

choosing a tacton with the same frequency and pulse duration but

different amplitude. The better performance with higher frequency

tactons presumably reflects the greater sensitivity of both glabrous

and hairy skin to frequencies between 200-300 Hz [5][23]. It has

been shown that there is no difference between the fingertip and

the forearm in terms of the ability to discriminate the frequency of

vibrotactile stimuli [24], which is consistent with the present

findings showing similar performance at both sites tested. Other studies using a similar number of tactons (nine) presented

at a single location, as in the present experiment, have generally reported higher identification rates with means ranging from 70% to 80% correct [8][25]. In these latter experiments two stimulus parameters were varied: waveform and frequency [25], and waveform and rhythm [8], with three levels of each stimulus. The difference between the present experiment and these other studies on tacton identification suggests that having two dimensions with three values per dimension (32=9) results in improved identification as compared to three dimensions with two values per dimension (23=8). The specific dimensions selected to create tactons must also be considered in this comparison, in that studies that have used spatial cues as a stimulus dimension to create tactons have generally reported much higher rates of tacton identification (90%) [2]. In the latter study only two stimulus dimensions, intensity and spatial location, were used to create tactile patterns.

The dimensions of perceptual stimuli are often defined as being integral or separable [26], and this distinction is important to tacton design. Dimensions that are integral are those that form phenomenologically unitary stimuli that are difficult to analyze into distinct components and combine according to a Euclidean metric. In contrast, separable dimensions are more easily analyzable and from a perceptual perspective can be processed individually. Discrimination and classification tasks are often used to determine which dimensions are integral and separable; dimensional redundancy improves performance with integral dimensions but has little effect on performance with dimensions that are separable. In the context of vibrotactile information processing, frequency and amplitude have been shown to be integral dimensions, as reflected in the decrease in choice reaction times for classifying stimuli when frequency and amplitude are correlated and the increase in reaction times when they are orthogonal [27]. Similarly, when amplitude is modulated redundantly with frequency, discrimination of time-varying vibrotactile stimuli improves [28]. In contrast, vibrotactile frequency and duration have been shown to be separable dimensions of tactile stimuli [29]. In the present experiment, the perceived frequency of tactons with the same frequency but varying amplitude (e.g. tactons 1 and 3 or 2 and 4) may have changed for some subjects due to the influence of vibration amplitude on perceived frequency. An increase (decrease) in vibration amplitude at a constant frequency can result in an increase (decrease) in perceived frequency, although the robustness of this phenomenon varies considerably across subjects [30]. These interactions may have influenced performance in the present experiment, but the two frequencies selected to create

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tactons (50 and 200 Hz) were very different and their perception primarily mediated by separate mechanoreceptor populations [5].

In the present experiment, it was surprising to find that the ability to identify tactons was not influenced by the site on which they were presented. The greater density of mechanoreceptors and associated superior tactile acuity of the finger as compared to the forearm [23][31] was not reflected in higher identification scores for these supra-threshold stimuli. It is clear that the particular stimulus dimensions selected to create tactons were equally difficult for both sites to resolve, but as evident in Fig. 2 and the statistical analyses, some tactons (e.g. tactons 2 and 6) were easier to identify when presented to the forearm as compared to the hand. A similar finding was reported by Summers et al. [28] who compared discrimination of time-varying tactile stimuli presented on the index finger and the wrist. Their results indicated that gap detection and the perception of frequency differences was similar at the wrist and fingertip, but that the perception of amplitude differences was in fact superior at the wrist. The latter finding may be due to the more rapid increase in the subjective intensity of vibrotactile amplitude at less sensitive sites such as the forearm as compared to the fingers [32]. These results collectively suggest that the forearm can be used to display vibrotactile information and that it may prove to be particularly effective in situations where the hands are required for other activities or the communication needs to be private and unobtrusive.

The left fingertip and forearm were used in these experiments so that the right, preferred, hand controlled the computer mouse that participants used to enter their responses. The question naturally arises as to whether any of the results reported reflect differences in the sensitivity of the left and right sides of the body. It has generally been found that hand superiorities in cutaneous sensitivity are rarely observed and that there are no significant differences between the left and right hands in terms of pressure or vibrotactile thresholds [33][34]. It would therefore be expected that performance would be similar if the tactons were presented to the right hand and arm.

The information transmission capabilities of the set of tactons were also evaluated in this experiment in terms of the static IT achieved. Previous studies have shown that IT varies depending on the dimensionality of the tactile stimuli and for the hand on the number of fingers involved in sensing the stimuli [21][22]. For vibrotactile stimuli delivered to a finger, IT has been measured at 1-2 bits for each stimulus dimension (e.g. frequency, intensity and contactor area) and about 4-5 bits for all dimensions. The estimates in the present experiment of 1-2 bits for stimuli varying along three dimensions are considerably smaller than these estimates, although in some of the earlier studies subjects were trained to reach a performance criterion prior to testing [22]. The present IT values are more similar to those reported by Summers et al. [28] who estimated an IT of 0.6 bits for one dimensional stimuli (frequency modulation) delivered to the wrist and finger and 1.05 and 0.8 bits for two-dimensional stimuli (frequency modulation plus amplitude modulation) presented on the wrist and finger respectively.

5 CONCLUSIONS

The development of effective vibrotactile communication systems

involves identifying how the various stimulus parameters that

define the input to the skin can be combined optimally to create a

lexicon of tactons. There is a challenge in creating such systems

when the input cannot be spatially distributed across the skin such

as when interacting with a screen on a mobile device with a single

digit. The results from the present experiment indicate that when

presented to a single location such as the fingertip or forearm,

tactons created using stimulus frequency, amplitude and pulse

duration are relatively difficult to identify after a short period of

training. However, certain stimulus dimensions, such as higher

vibrotactile frequencies and amplitudes, appear to be the relatively

easy to encode. Other studies that have reported higher rates of

identification at a single site created their tactons by varying two

stimulus dimensions, which suggests that increasing the

dimensionality of the stimulus may not necessarily lead to better

identification. In the present experiment, the tactons that were

accurately identified and the confusion matrices of subjects’

responses provided valuable cues as to which stimulus parameters

should be evaluated in future work. Higher rates of tacton

identification may result from concurrent variation of integral

dimensions of vibrotactile stimuli such as their amplitude and

frequency and orthogonal variations in the temporal profile of the

input. Varying the duration of the tactons should also improve

identification. Studies of vibrotactile pattern perception reveal the importance

of understanding how the properties of the somatosensory system influence the processing of information at different sites on the body. Features such as skin anisotropies and spatial-temporal interactions, must be considered in designing and evaluating tactons. Tactile stimuli presented at one site and in one orientation may not be encoded in a similar manner at another site due to variations in mechanoreceptor density. Finally, the superior tactile acuity at some locations (e.g. the hand) does not necessarily confer an advantage in identifying tactile stimuli, as revealed in the present experiment. Acknowledgements This research was supported by a grant from the National Science

Foundation under Grant No. IIS-1016998.

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