Perception of force and stiffness in the presence of low-frequency haptic noise

PLoS One. 2017 Jun 2;12(6):e0178605. doi: 10.1371/journal.pone.0178605. eCollection 2017.

Abstract

Objective: This work lays the foundation for future research on quantitative modeling of human stiffness perception. Our goal was to develop a method by which a human's ability to perceive suprathreshold haptic force stimuli and haptic stiffness stimuli can be affected by adding haptic noise.

Methods: Five human participants performed a same-different task with a one-degree-of-freedom force-feedback device. Participants used the right index finger to actively interact with variations of force (∼5 and ∼8 N) and stiffness (∼290 N/m) stimuli that included one of four scaled amounts of haptically rendered noise (None, Low, Medium, High). The haptic noise was zero-mean Gaussian white noise that was low-pass filtered with a 2 Hz cut-off frequency; the resulting low-frequency signal was added to the force rendered while the participant interacted with the force and stiffness stimuli.

Results: We found that the precision with which participants could identify the magnitude of both the force and stiffness stimuli was affected by the magnitude of the low-frequency haptically rendered noise added to the haptic stimulus, as well as the magnitude of the haptic stimulus itself. The Weber fraction strongly correlated with the standard deviation of the low-frequency haptic noise with a Pearson product-moment correlation coefficient of ρ > 0.83. The mean standard deviation of the low-frequency haptic noise in the haptic stimuli ranged from 0.184 N to 1.111 N across the four haptically rendered noise levels, and the corresponding mean Weber fractions spanned between 0.042 and 0.101.

Conclusions: The human ability to perceive both suprathreshold haptic force and stiffness stimuli degrades in the presence of added low-frequency haptic noise. Future work can use the reported methods to investigate how force perception and stiffness perception may relate, with possible applications in haptic watermarking and in the assessment of the functionality of peripheral pathways in individuals with haptic impairments.

MeSH terms

  • Humans
  • Models, Theoretical*
  • Task Performance and Analysis