Complex social information can be felt through a virtual touch
Distancing amid the COVID-19 pandemic has made both physical and social connections a touch more difficult to maintain. For Stanford University graduate student Millie Salvato, being apart from her girlfriend on the opposite coast has proved challenging.
“It’s a unique work that looks at how our social touch is delivered and then ... how to reproduce it,” says Gregory Gerling, a touch researcher at the University of Virginia who was not involved in the study. After collecting 661 touch movements—squeezes, strokes, shakes, pokes, and the like—Salvato and her colleagues mapped the location and pressure of each. Next, they used a machine-learning algorithm to select the movements that were most reliably part of each response. Finally, they programmed a wearable sleeve to simulate these movements using eight embedded disks that vibrate when electronically signaled.
Even with no training, 30 new study participants correctly matched the simulated touches to the six scenarios 45 percent of the time—about 2.7 times more than by chance. For comparison, a previous study from Gerling’s laboratory found participants could match scenarios for touches from real human hands 57 percent of the time.
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