Identifying 3-D spatiotemporal skin deformation cues evoked in interacting with compliant elastic surfaces
Observing skin deformation over time
August 26, 2020
Bingxu Li, Steven C. Hauser, Gregory J. Gerling
To help us discriminate soft, compliant fruits and tissues, we rely upon tactile cues embedded in the deformation of finger pad skin. Herein, we use a 3-D stereo imaging technique to directly observe patterns in the skin’s deformation. We develop metrics that map 2-D estimates of terminal contact area to 3-D metrics that represent spatial and temporal changes in penetration depth, surface curvature, and force. Human-subjects experiments compare stimulus pairs varying in compliance.
The results indicate that certain metrics more efficiently distinguish compliances earlier, at less displacement. Our observations seek to guide the design and control of haptic actuators.
Data Collection
A custom-built, stereo imaging device is used to obtain 3-D point cloud data for contact of the finger pad with compliant stimuli. The device includes a load cell, a cantilever of a vertically moving indenter, a 3-D printed housing upon which five stimuli can be mounted and rotated in and out of position for vertical indentation, and two cameras for direct stereo visualization with the finger pad beneath. Image processing technique is applied to each frame.
Procedure to obtain 3-D point cloud data representing the deformed surface of the finger pad. A) Left camera image from stereo pair of an example participant’s finger pad beneath a 121 kPa stimulus at 5 mm indentation. B) raw data of the 3-D point cloud, C) selection of the finger pad outline at the surface image plane, and masking of peripheral noise in the image. D) 3-D point cloud of finger pad contact with the stimulus, post-masking.
Ellipse Method
To characterize how the 3-D point cloud changes over the course of an indentation, we developed a method to fit stacked ellipses to discrete, vertically oriented image planes.
Comparison of finger pad deformation between two compliant substrates, each indented to 5 mm depth. A) 3-D point cloud of an example participant’s finger pad indented by the 45 kPa stimulus to a terminal depth of5 mm. Overlaid are 6 ellipses fitted to this point cloud at imaging planes of0.25 mm increments. B) Similarly, 3ellipses are fitted for the case of a stiffer substrate, a 184 kPa stimulus indented to 5 mm.
Developed Metrics
We develop new metrics to quantify the patterns of deformation of the skin’s surface as evoked across a range of stimulus compliances, indentation depths, and time scales. In a series of human subjects experiments, a range of stimulus compliances (45 – 184 kPa) are employed, which vary in pairwise discriminability, with rates from 50-100%. the new metrics are compared in effort to determine which might most significantly aid in the discrimination of particular combinations of compliant substrates, considering both discriminability and compliance absolute magnitude.
Comparison of five spatial biomechanical metrics between five compliant substrates. Each metric is defined in Methods. The metrics are each plotted at points from 1-5 mm into the 5 mm terminal indentation. A) The contact area is represented by the last formed ellipse, at the initial surface contact plane, which is always the largest ellipse. B)The maximum area change is the largest difference in area between two sequential (adjacent) image planes, divided by the distance between the two image planes. C) The penetration depth of the finger pad into the stimulus. D)The average curvature is average of all slope values between adjacent image planes. E) The force as measured at the stimulus. In panel F), the metrics are statistically compared (via t-test, significance shown as filled box if more than one standard deviation) across three pairs of stimuli, which vary in discriminability (see Figure 2). As can be observed, penetration depth and average curvature are distinct at 1 mm into the 5 mm indentation for the184 to 75 kPa comparison. At 2 mm, additional metrics of contact area and force are now distinct. For each stimulus comparisons, even that of 75 to 45 kPa that is difficult to discriminate, penetration depth and average curvature are distinct by 2 mm.
References
Li, B., Hauser, S.C., and Gerling, G.J., Identifying 3-D spatiotemporal skin deformation cues evoked in interacting with compliant elastic surfaces [DOI][PDF]. IEEE Haptics Symposium, 2020.
Hauser, S.C. and Gerling, G.J., Imaging the 3-D deformation of the finger pad when interacting with compliant materials [DOI][PDF]. IEEE Haptics Symposium, 2018.
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