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Neuromorphic hardware for somatosensory neuroprostheses

Author

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  • Elisa Donati

    (University of Zurich and ETH Zurich)

  • Giacomo Valle

    (University of Chicago)

Abstract

In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies.

Suggested Citation

  • Elisa Donati & Giacomo Valle, 2024. "Neuromorphic hardware for somatosensory neuroprostheses," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-44723-3
    DOI: 10.1038/s41467-024-44723-3
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    References listed on IDEAS

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    2. Shize Lu & Xinqing Xiao, 2024. "Neuromorphic Computing for Smart Agriculture," Agriculture, MDPI, vol. 14(11), pages 1-26, November.
    3. Haisheng Xia & Yuchong Zhang & Nona Rajabi & Farzaneh Taleb & Qunting Yang & Danica Kragic & Zhijun Li, 2024. "Shaping high-performance wearable robots for human motor and sensory reconstruction and enhancement," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

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