Tactile Augmentation of Material Classification via Imperceptible On-Skin Triboelectricity Collection.

ABSTRACT: Harnessing intrinsic triboelectric signals from human skin holds promise for enhancing tactile perception. However, collecting these signals without disrupting normal skin functions and convoluting motion artifacts remains challenging. Additionally, person-to-person signal variance complicates data processing. In this study, it is demonstrated that triboelectric signals generated from touch can be imperceptibly collected and processed using a machine learning model to achieve tactile augmentation. When one hand contacts and rubs against a target object, charge transfer occurs between the skin and the object's surface. By placing a substrate-less microfiber electrode on the finger of the other hand, a body-coupled triboelectric circuit is formed to collect these signals, which contain mater

SUBMITTER: Huang J 

PROVIDER: S-EPMC12376505 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature