Human–Machine Haptic Interface Design Using Stochastic Resonance Methods

Repperger, D.W.; Phillips, Carol A; Berlin, J.; Neidhard-Doll, Amy T.; Haas, Michael

doi:10.1109/tsmca.2005.850608

Cited by 21 publications

(9 citation statements)

References 40 publications

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“…In humans, Repperger et al showed that target tracking task can be improved by adding lateral noise in chair (where subjects sat during the task) [17]. These studies show that wobbling helps to enhance visual perception.…”

Section: Does Cross Modal Noise Help In Ttc Judgments?mentioning

confidence: 99%

“…Correspondingly, Simonotto et al observed SR in images by adding pixel noise [19]. Furthermore, Repperger et al showed SR in human-machine haptic interface by adding noise to the chair and joystick to improve target tracking [17].…”

Section: Introductionmentioning

confidence: 99%

“…In several experiments, researchers demonstrated SR to enhance detectability in different animals (crayfish [14], paddlefish [15] as well as humans [16,17]). For instance, Zeng et al observed SR effect on human hearing [16].…”

Section: Introductionmentioning

confidence: 99%

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Stochastic Resonance in Time-to-Contact Judgments

et al. 2015

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Communicated by Stanislav M. SoskinStochastic resonance (SR) is a counterintuitive phenomenon in which additive noise enhances performance of a nonlinear system. Previous studies demonstrated SR effect on human tactile sensitivity by adding noise of same modality and cross modality. Similarly, enhancement of human hearing through additive noise has been studied. In this study, we investigate the effect of noise in visual perception, specifically time-to-contact (TTC) judgments. This study explores four research questions: (1) Does noise help in TTC judgments? (2) How does noise affect speed and accuracy of TTC judgments? (3) Does cross modal noise help in TTC judgments? (4) How does cross modal noise affect speed and accuracy of TTC judgments? Through simulation, we show that noise in optical cue can enhance weak signals. We also demonstrate that noise can improve speed of TTC judgments at the expense of accuracy. Similarly, we demonstrate SR by adding noise of cross modality. These findings provide plausible hypotheses regarding how much noise should be added to enhance TTC judgments.

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Section: Does Cross Modal Noise Help In Ttc Judgments?mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Stochastic Resonance in Time-to-Contact Judgments

et al. 2015

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“…Specially, because response time of tactile feedback is the shortest in sensory detections, it is able to help improve user's performance and fast action [11,12]. In addition, force information that is a part of tactile feedback is able to enhance user's performance in general inputting devices' tasks [13].…”

Section: Literature Reviewmentioning

confidence: 99%

The Effects of Multimodal Feedback and Gender on Task Performance of Stylus Pen Users

Park

Kim

Pobil

2012

International Journal of Advanced Robotic Systems

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As various interactive input devices for computers have become available, the role of multimodal feedbacks generated by the devices has gained an increasing emphasis in recent years, with debates surrounding the relative efficiency of different feedback types of input devices. To address this and related issues, the present study conducted a 4 (types of feedback: visual vs. tactile vs. auditory vs. combined feedback) x 2 (gender: male vs. female) within-subject experiment to examine the effects of the type of feedbacks and gender on the efficiency and accuracy of a multimodal stylus pen. Results from the experiment showed that, regardless of the feedback type, males clicked the stylus faster than females while making more errors. A similar pattern was discovered when used the pen for dragging; males completed the dragging task faster than females while producing more errors. Interactions between the feedback type and gender as well as implications and limitations of the present study are discussed.

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“…In practical application, SR has been utilized in signal processing, for example to degrade the noisy of noise image and to enhance the detectability of weak signals [17].Daniel W. Repperger extended SR concepts to the design of the haptic interface and improved the training tracking performance [18]. In this paper, it is supposed to utilize the SR in tactile sensation to improve the realistic of haptic texture, and explore on how to improve the performance of haptic texture system through tuning the parameters of noise signal.…”

Section: Introductionmentioning

confidence: 99%

Research on improving the haptic texture display using stochastic noise

2009

2009 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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Stochastic resonance has been found to be a common mechanism in a variety of physical and biological systems including signal transduction in human audition and vision. It was supposed that adding stochastic noise signal to the texture force model could enhance the realistic of haptic texture display. Based on this assumption, the prior texture force model based on image processing was improved by adding the white Gaussian noise, and the haptic texture display interface was constructed based on DELTA haptic device. The texture perception experiments were carried out. The experiments showed that people can achieve more remarkable texture perception when adding an appropriate noise signal to the original texture force, and subjects can obviously distinguish the texture images with the haptic texture display interface.

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Human–Machine Haptic Interface Design Using Stochastic Resonance Methods

Cited by 21 publications

References 40 publications

Stochastic Resonance in Time-to-Contact Judgments

Stochastic Resonance in Time-to-Contact Judgments

The Effects of Multimodal Feedback and Gender on Task Performance of Stylus Pen Users

Research on improving the haptic texture display using stochastic noise

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