User perceptions and evaluations of short vibrotactile feedback

Dabic, Stéphanie; Navarro, Jordan; Tissot, Jean-Marc; Versace, Rémy

doi:10.1080/20445911.2013.768997

Cited by 11 publications

(9 citation statements)

References 20 publications

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“…We chose the sinewave as the waveform since Dabic et al [23] revealed that there was no role in the waveform for perceived differences of vibrotactile feedback on touchscreens.…”

Section: B Parametersmentioning

confidence: 99%

“…We considered the frequency and the duration in the later main study. Dabic et al [23] have demonstrated the frequency is the most salient parameter for the perceived differences, and the duration also impacts vibrotactile signals perception when vibrotactile feedbacks are short. So, we only considered other unclear parameters in this section.…”

Section: B Parametersmentioning

confidence: 99%

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Perceived Depth and Roughness of Virtual Buttons With Touchscreens

Wei

et al. 2022

IEEE Trans. Haptics

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With the rapidly increasing penetration of touchscreens in various application sectors, more sophisticated and configurable haptic effects can be rendered on touchscreens (e.g., buttons). In this paper, we presented a design process to instantiate a wide range of vibrotactile stimuli for rendering various virtual buttons on touchscreens. We study the perceived depth and roughness of rendered virtual buttons. There are two stages: the design of the drive signals and the main study. We generated and screened drive signals to render vibrotactile stimuli for virtual buttons through varying envelope shapes, superposition methods, compound waveform composition (CWC) types, durations, and frequencies. The results show that the perceived depth of virtual buttons can be very deep, and the perceived roughness can be very rough around the resonant frequency. Perceived depth and roughness decrease when the frequency increases or decreases from the resonant frequency. A longer duration of vibrotactile stimuli and adding pulse numbers could increase the perceived depth and roughness. Perceived depth and roughness have a similar trend with varying frequencies at a fixed duration.

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“…We chose the sinewave as the waveform since Dabic et al [23] revealed that there was no role in the waveform for perceived differences of vibrotactile feedback on touchscreens.…”

Section: B Parametersmentioning

confidence: 99%

Section: B Parametersmentioning

confidence: 99%

Perceived Depth and Roughness of Virtual Buttons With Touchscreens

Wei

et al. 2022

IEEE Trans. Haptics

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“…For every pair thus generated, the subjects evaluated the perceptual dissimilarity between the two signals on a 1 to 7 Likert scale, where 1 was equivalent to the signals are very similar and 7 to the signals are very different. An extensive description of the experiment is available in [11].…”

Section: A Dissimilarity Judgment Experimentsmentioning

confidence: 99%

“…With the above data, an 18 × 18 perceptual dissimilarity matrix D P , was generated [11]. The value of each element D P (i, j ) corresponds to the perceptual distance between signals i and j .…”

Section: A Dissimilarity Judgment Experimentsmentioning

confidence: 99%

A Fuzzy Rule-Based Model of Vibrotactile Perception via an Automobile Haptic Screen

Duţu

Mauris

Bolon

et al. 2015

IEEE Trans. Instrum. Meas.

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International audienceWith the increased popularity of touch-sensitive surfaces, much attention has been drawn to their security-related issues, as they currently rely only on the visual sense for feedback. To improve operability, vibrotactile signals may be delivered to the finger on screen interaction. The way vibrotactile signals affect human perception is examined via three measured variables, related to their energy, velocity, and spectral complexity, and which are analytically defined in this paper. It is shown that these variables accurately account for the psychophysical properties of the tactile sense. Based on this, a psychophysical fuzzy rule-based model of vibrotactile perception is introduced to forecast the comfort values of the vibrational signals provided by an automobile haptic screen. Using an efficient rule-based generation method, a Mamdani fuzzy inference system is proposed; it achieves a mean error rate of 14% for the train set and 17% for the test set, while correctly classifying most of the signals within a reasonable tolerance, related to human evaluation imprecision. The system also produces a comprehensible linguistic rule structure, which allows behavioral patterns to be detected

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“…This approach has been an exceedingly effective tool in comprehending the perceptual structure of many types of haptic stimulus, e.g., texture [16,38,40], vibration [17,18,25,44,47,57], and material [58]. In particular, the sensations of button press were analyzed using perceptual spaces for 10 real and 14 force-feedback buttons [32], 23 physical buttons [36], and 18 touchscreen virtual buttons [10]. We report a perceptual space for physical and vibration-augmented buttons and their extrinsic perceptual properties using a set of adjectives.…”

Section: Perceptual Space and Dimensionsmentioning

confidence: 99%

Augmenting Physical Buttons with Vibrotactile Feedback for Programmable Feels

Park

Yoon

et al. 2020

Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology

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Physical buttons provide clear haptic feedback when pressed and released, but their responses are unvarying. Physical buttons can be powered by force actuators to produce unlimited click sensations, but the cost is substantial. An alternative can be augmenting physical buttons with simple and inexpensive vibration actuators. When pushed, an augmented button generates a vibration overlayed on the button's original kinesthetic response, under the general framework of haptic augmented reality. We explore the design space of augmented buttons while changing vibration frequency, amplitude, duration, and envelope. We then visualize the perceptual structure of augmented buttons by estimating a perceptual space for 7 physical buttons and 40 augmented buttons. Their sensations are also assessed against adjectives, and results are mapped into the perceptual space to identify meaningful perceptual dimensions. Our results contribute to understanding the benefts and limitations of programmable vibration-augmented physical buttons with emphasis on their feels.

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User perceptions and evaluations of short vibrotactile feedback

Cited by 11 publications

References 20 publications

Perceived Depth and Roughness of Virtual Buttons With Touchscreens

Perceived Depth and Roughness of Virtual Buttons With Touchscreens

A Fuzzy Rule-Based Model of Vibrotactile Perception via an Automobile Haptic Screen

Augmenting Physical Buttons with Vibrotactile Feedback for Programmable Feels

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