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Vibrotactile Phantom Sensation Rendering with Complex Waveform Signals

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Abstract
Since realistic feedback in Human-Computer Interaction field provides users with a greater sense of immersion and satisfaction, realism has been the main criteria for haptic researchers to implement user-preferred systems.
Despite its benefits, haptic feedback has innate limitation in providing spatially correct information that is usually considered mandatory for realistic information rendering in VR or multi-modal feedback systems.
The phantom sensation, which is an illusory tactile effect occurring in the middle of multiple stimulated sties, has contributed to spatial information delivery using sinusoidal signals.
Those sinusoidal signals could successfully provided the intended location information, however, lacked their realism for their simple design space which is not capable of describing realistic vibrations.
We proposed textured phantom sensation (TPS) as a technique that delivers temporally consistent texture information at the desired location using the phantom sensation.
We selected the index and middle fingertips as the stimulating sites with a controlled distance of 5cm and tested TPS in both stationary and dynamic scenarios.
Our first attempt to assess TPS with fixed motion profile was failed due to following reasons: lack of training and high task difficulty.
Also, the temporally consistent vibrations did not reveal the texture differences, which degrades the realism of the signal, so we designed a reinforced experiments using the texture vibrations from motions without normalization.
We chose 3 and 5 distinctive textures for each experiment among 100 textures from a literature to generate consistent texture vibration for our experiments.
So far, our studies showed the possibility of giving the texture and location informations with high accuracy.
Author(s)
Minwook Lee
Issued Date
2024
Type
Thesis
URI
https://scholar.gist.ac.kr/handle/local/19886
Alternative Author(s)
이민욱
Department
대학원 AI대학원
Advisor
Park, Gunhyuk
Degree
Master
Appears in Collections:
Department of AI Convergence > 3. Theses(Master)
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