The realization and rendering of artificial thermal tactile perception hold great potential for advancing wearable technologies and human–machine interaction, with broad applications in medical rehabilitation, virtual reality (VR), augmented reality (AR), and intelligent manufacturing. Although wearable thermoelectric devices (WTEDs) offer a promising platform, their limited cooling capacity and inefficient heat dissipation remain critical barriers to achieving effective thermal tactile functionality. In this study, we developed a novel two–stage wearable thermoelectric device (TSWTED) integrated with a nickel foam–enhanced hydrogel heat sink. Independent control of the two thermoelectric devices (TEDs) enabled flexible current combinations to meet different cooling requirements. An analytical model of the skin–TSWTED system was also established , and the device structure was optimized with the minimum cooling temperature as the design objective. Experimental results showed that, with the nickel foam–enhanced hydrogel heat sink, the TSWTED achieved minimum steady-state and dynamic cooling temperatures of 281.06 K and 271.74 K, respectively, which were on average about 10 K lower than those obtained without this heat sink. In wearable experiments, the minimum skin surface temperature reached 289.2 K, below which painful sensations may occur, thus effectively addressing the heat dissipation limitations on the hot side of the TSWTED. Further thermal feedback tests with representative materials confirmed that the TSWTED can effectively reproduce thermal tactile sensations on human skin. Overall, the proposed TSWTED provides an efficient experimental platform and a controllable temperature–regulation method for artificial thermal tactile feedback research in VR and AR applications.
Building similarity graph...
Analyzing shared references across papers
Loading...
Yuanzhi Liu
Zhijia Cai
Dandan Pang
Case Studies in Thermal Engineering
Nanyang Technological University
Western Sydney University
Ningbo University
Building similarity graph...
Analyzing shared references across papers
Loading...
Liu et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69a7602cc6e9836116a2ca78 — DOI: https://doi.org/10.1016/j.csite.2026.107803