A pilot study: Introduction of time-domain segment to intensity-based perception model of high-frequency vibration

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Abstract

The intensity of a high-frequency vibration is the primary cue to convey vibrotactile information perceived by the Pacinian system. However, the conventional intensity-based spectral power model is not sufficient to interpret a relatively slow time-variant pattern of vibration such as amplitude-modulated (AM) vibrations. This paper introduced a time-domain segment to the intensity-based model such that a long-term vibration pattern is divided into multiple short-term sinusoidal vibrations that maintain the same energy. We expected that such short-term segmentation could deliver the similar perception if the energy of each segment of the reproduced vibration is the same as the original waveform even though the time-segmented reproduced waveform has a step-wise envelope shape. We conducted a pilot psychophysical experiment in which the participants discriminated between the original AM vibrations and the time-segmented vibrations by changing the segment size from 1/6 to 1/2 of the AM period. The experiment is conducted under different combinations of the carrier frequencies (300 Hz and 600 Hz) and envelope frequencies (15 Hz, 30 Hz, and 45 Hz) frequencies. The results showed that the participants had low discrimination ratios (the mean values are less than 0.6) at the segment size from 1/6 to 1/3 of the AM period and the participants could discriminate easily between the flat sinusoidal vibration and the original AM vibration (the mean discrimination ratios are larger than 0.90) even if the energies of the two vibrations were maintained. The results suggest that the time-segmented intensity-based model could reproduce perceptually-similar vibrations for AM vibrations at the segment size from 1/6 to 1/3 of the AM period.

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Cao, N., Nagano, H., Konyo, M., Okamoto, S., & Tadokoro, S. (2018). A pilot study: Introduction of time-domain segment to intensity-based perception model of high-frequency vibration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10893 LNCS, pp. 321–332). Springer Verlag. https://doi.org/10.1007/978-3-319-93445-7_28

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