Abstract
We demonstrate a wearable flexible electrostatic transducer (FET) matrix that conforms to the skin and can be used to generate complex haptic signals. The transducers consist of a pair of flexible electrodes that are attracted based on electrostatic force. We designed and built a 2 by 2 matrix of transducers from a pair of flexible films, with the design optimized for indentation into the skin. A transducer with a 10 mm by 10 mm footprint and a height of 2 mm effectively generated perceptible stimulus on the skin when operated at 150 V–250 V. Three psychophysical experiments were carried out to evaluate the properties of the new device as a wearable haptic display. Experiment 1 showed that the matrix of transducers was able to linearly boost perceived intensity when compared to a single transducer. Experiment 2 indicated that it was possible to indistinguishably replicate multi-frequency signals delivered to one transducer using multiple transducers that each operated at one of the frequencies. In Experiment 3, four movement-based stimulation patterns were designed using tactile illusion, and the identification rates were significantly above chance level. Our findings demonstrate that the compact, flexible, and scalable transducer array is well suited as a new type of actuator for wearable haptics research and applications.
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Acknowledgements
The authors are grateful for the financial support of the National Science Foundation award (ECCS1509369), the National Institute of Health (NIH) Director’s Transformative Research Award (R01HL137157), the Thayer School of Engineering PhD Innovation Program, and Facebook, Inc. under the SARA program. H. Z. Tan was partly supported by a Google Faculty Research Award 2019 and Grant No. 1954842-IIS from the National Science Foundation.
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Trase, I., Tan, H.Z., Chen, Z., Zhang, J.X.J. (2021). Wearable Haptic Array of Flexible Electrostatic Transducers. In: Yamamoto, S., Mori, H. (eds) Human Interface and the Management of Information. Information Presentation and Visualization. HCII 2021. Lecture Notes in Computer Science(), vol 12765. Springer, Cham. https://doi.org/10.1007/978-3-030-78321-1_28
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