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Biomimetic hairy affective-touch sensory AI interface.

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  • 1Interdisciplinary Research Center, School of Electronic Science and Engineering, Southeast University, Nanjing, China.

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|March 19, 2026
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Summary
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Researchers developed a biomimetic hairy sensor to detect affective touch, enabling artificial intelligence (AI) to recognize emotions from physical contact. This tactile sensing technology advances human-AI emotional interaction.

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Area of Science:

  • Biomimetic engineering
  • Neuroscience
  • Artificial Intelligence

Background:

  • Artificial intelligence (AI) lacks the ability to perceive tactile emotions, limiting its understanding of human social behaviors conveyed through physical touch.
  • Current AI systems struggle to interpret the nuances of affective touch, hindering natural human-AI interaction.
  • Developing tactile sensing capabilities is crucial for AI to decode social cues embedded in physical contact.

Purpose of the Study:

  • To create a biomimetic hairy sensing interface capable of capturing the spatiotemporal and intrinsic features of affective touch.
  • To enable accurate emotion recognition in AI by replicating biological tactile sensing mechanisms.
  • To establish a bioelectronic analog for affective touch transduction.

Main Methods:

  • Development of a biomimetic hairy sensing interface with a bistage hairy structure and homogeneous nanomesh manufacturing.
  • Utilizing isoline theory for high force detection sensitivity and spatial precision.
  • Direct induction of neuromimetic electric pulse signals without a spike coding circuit.
  • Integration with a hybrid neural network (convolutional neural network and contextual large language model).

Main Results:

  • The hairy interface achieved high force detection sensitivity (0.67 N⁻¹) and spatial precision (1.61 mm localization accuracy over 100 cm²).
  • The interface successfully replicated the behavior of biological C-LTMRs (slowly adapting, Merkel nerve receptors).
  • Real-time emotion recognition was achieved with 82.37% accuracy using the hybrid neural network, analyzing individualized touch patterns.

Conclusions:

  • The developed neuromorphic tactile framework successfully enables emotion recognition from affective touch.
  • This bioelectronic analog of affective touch transduction advances the development of AI systems capable of understanding human physical contact.
  • The technology facilitates closed-loop human-AI emotional interaction, paving the way for humanoid robots with natural affective communication abilities.