Object stiffness recognition using haptic feedback delivered through transcutaneous proximal nerve stimulation.

OBJECTIVE: Haptic feedback is crucial when we manipulate objects. Information pertaining to an object's stiffness in particular can help facilitate fine motor control. In this study, we seek to determine whether objects of different stiffness levels can be recognized using haptic feedback provided by transcutaneous electrical stimulation of peripheral nerves. APPROACH: Using a stimulation electrode grid placed along the medial side of the upper arm, the median and ulnar nerve bundles were targeted to evoke haptic sensation on the palmar side of the hand. Stimulation current amplitude was modulated in real-time with the fingertip force recorded from a sensorized prosthetic hand. In order to evaluate which stimulation pattern was more critical, object stiffness was encoded either by the rate of change of the stimulus amplitude or the level of peak stimulus amplitude, as the prosthesis grasped the objects. MAIN
RESULTS: Both encoding methods allowed the subjects to differentiate objects of different stiffness levels with  >90% accuracy. No significant difference was observed between the two encoding methods, which indicated that both the rate of change of the stimulation amplitude and the peak stimulation amplitude could effectively provide stiffness information of the objects. SIGNIFICANCE: The outcomes suggest that it is possible to elicit haptic sensations describing various object stiffness levels using transcutaneous nerve stimulation. The haptic feedback associated with object stiffness can facilitate object manipulation/interactions. It may also improve user experience during human-machine interactions, when object stiffness information is incorporated.