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Real-time finger motion recognition using skin-conformable electronics


Interpreting and tracking finger motion in free space is of use in the development of control interfaces for augmented and virtual reality systems. One approach to create human–machine interfaces capable of accurate finger motion recognition is to use wearable sensors with integrated neuromorphic computing. Here we show that an integrated titanium-oxide-based artificial synapse array and organic motion sensor can be conformably attached to a finger and provide real-time motion recognition. The synaptic device and sensor exhibit well-defined synaptic and light-responsive electrical properties, respectively, as well as flexibility and mechanical robustness. The integrated synapses–sensor enables optical–electrical signal conversion and summation of post-synaptic current. Finger motions for time-resolved digit patterns (0–9) can be learned and recognized with an accuracy of up to 95% at varying strains and up to 100 strain cycles.

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Fig. 1: TOAS device setup, imaging and initial characterization.
Fig. 2: Evaluation of TOAS device.
Fig. 3: Characterization of OPS and principles of OPS–TOAS devices.
Fig. 4: Finger-writing motion recognition and learning capability.

Data availability

The data that support the findings of this study are available from the corresponding authors upon reasonable request.


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This work was supported by the National Research Foundation of Korea (NRF-2022R1A2B5B02001455, NRF-2022M3H4A1A01009526, NRF-2022K2A9A1A01098066, RS-2023-00220077, RS-2023-00213089 and 2022R1I1A1A01073911); the KU-KIST Research Fund, the Korea University Research Grant, the MSIT, Korea, under the ITRC (Information Technology Research Center) support program (grant no. IITP-2023-2020-0-01461) supervised by the Institute for Information & Communications Technology Planning & Evaluation (IITP); and the Technology Innovation Program (grant no. RS-2022-00154781) funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea). We would like to express our gratitude to B.-G. Lee from Gwangju Institute of Science and Technology and S. Gi from Korea Electronics Technology Institute for their valuable contributions in reviewing and providing insightful feedback on circuit designs.

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Authors and Affiliations



G.W. and S.P. conceived the idea for this work. H.C., I.L., J.J., S.P. and G.W. designed the experiments and wrote the manuscript. H.C. fabricated the TOAS sample and conducted the related electrical and mechanical experiments. I.L., H.L. and J.-H.K. fabricated the ultrathin substrate and OPS sample and conducted the related experiments, including acquiring the digit patterns. J.J. conducted the neural network simulations. G.W. and S.P. oversaw the project, revised the manuscript and led the effort to completion.

Corresponding authors

Correspondence to Sungjun Park or Gunuk Wang.

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Nature Electronics thanks Tse Nga Ng and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Notes 1–5, Figs. 1–43, Tables 1 and 2 and references.

Supplementary Video 1

Detachment of the ultrathin TOAS array device from glass support.

Supplementary Video 2

Ultraflexibility of the TOAS array device.

Supplementary Video 3

Transfer of TOAS array device on the elastomer.

Supplementary Video 4

Mechanical endurance test of the ultraflexible TOAS array device.

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Cho, H., Lee, I., Jang, J. et al. Real-time finger motion recognition using skin-conformable electronics. Nat Electron 6, 619–629 (2023).

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