Ability to recognize and identify the location of vibration stimulation on the fingers

Liu, Yang; Yu, Yanan; Yang, Jiajia; Inai, Yoshinobu; Wu, Jinglong

doi:10.1109/icma.2014.6885939

Cited by 2 publications

(2 citation statements)

References 19 publications

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“…Slowly adapting (SA) fibers (Merkel and Ruffini mechanoreceptors) respond dominantly to sustained stimuli with main frequencies up to 100 Hz [ 25 ], while rapidly adapting (RA) fibers (Meissner and Pacinian mechanoreceptors) are involved in the representation of vibrations and tickle, with activation frequencies reaching 200–300 Hz for Pacinian receptors [ 23 ]. The maximum spatial sensitivity is achieved on the index phalanx, where the location of the presented tactile stimulation is precisely encoded [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications

Sorgini

Massari

D’Abbraccio

et al. 2018

Sensors

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We present a tactile telepresence system for real-time transmission of information about object stiffness to the human fingertips. Experimental tests were performed across two laboratories (Italy and Ireland). In the Italian laboratory, a mechatronic sensing platform indented different rubber samples. Information about rubber stiffness was converted into on-off events using a neuronal spiking model and sent to a vibrotactile glove in the Irish laboratory. Participants discriminated the variation of the stiffness of stimuli according to a two-alternative forced choice protocol. Stiffness discrimination was based on the variation of the temporal pattern of spikes generated during the indentation of the rubber samples. The results suggest that vibrotactile stimulation can effectively simulate surface stiffness when using neuronal spiking models to trigger vibrations in the haptic interface. Specifically, fractional variations of stiffness down to 0.67 were significantly discriminated with the developed neuromorphic haptic interface. This is a performance comparable, though slightly worse, to the threshold obtained in a benchmark experiment evaluating the same set of stimuli naturally with the own hand. Our paper presents a bioinspired method for delivering sensory feedback about object properties to human skin based on contingency–mimetic neuronal models, and can be useful for the design of high performance haptic devices.

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Section: Introductionmentioning

confidence: 99%

Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications

Sorgini

Massari

D’Abbraccio

et al. 2018

Sensors

View full text Add to dashboard Cite

show abstract

“…In particular, human hands' skin is able to perceive a relatively wide range of frequencies when stimulated with a vibrotactile stimulus, with a maximum frequency centered at about 300 Hertz for Pacinian receptors [26][27][28][29]. The maximum spatial sensitivity is achieved on the index phalanx, where the location of a presented vibrotactile stimulation is precisely encoded [30].…”

Section: Introductionmentioning

confidence: 99%

Gesture-Based Control of a Robot Arm with Neuromorphic Haptic Feedback

Sorgini¹,

Farulla²,

Lukić³

et al. 2018

Preprint

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Research on bidirectional human-machine interfaces will enable the smooth interaction with robotic platforms in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. We complement the gesture-based control by means of a tactile-feedback strategy grounding on a spiking artificial neuron model. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user’s hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pick-and-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the effectiveness of a neuronal spiking model for encoding hand displacement and exerted forces in order to promote a fluid embodiment of the haptic interface and control strategy. The main contribution of this paper is in presenting a robotic arm under gesture-based remote control with multisensory telepresence, demonstrating for the first time that a spiking haptic interface can be used to effectively deliver on the skin surface a sequence of stimuli emulating the neural code of the mechanoreceptors beneath.

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Ability to recognize and identify the location of vibration stimulation on the fingers

Cited by 2 publications

References 19 publications

Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications

Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications

Gesture-Based Control of a Robot Arm with Neuromorphic Haptic Feedback

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