In-Sensor Touch Analysis for Intent Recognition

doi:10.1002/adfm.202411331

In-Sensor Touch Analysis for Intent Recognition

2024-09-02

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DOI：10.1002/adfm.202411331

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Tactile intent recognition systems, which are highly desired to satisfy human's needs and humanized services, shall be accurately understanding and identifying human's intent. They generally utilize time-driven sensor arrays to achieve high spatiotemporal resolution, however, which encounter inevitable challenges of low scalability, huge data volumes, and complex processing. Here, an event-driven intent recognition touch sensor (IR touch sensor) with in-sensor computing capability is presented. The merit of event-driven and in-sensor computing enables the IR touch sensor to achieve ultrahigh resolution and obtain complete intent information with intrinsic concise data. It achieves critical signal extraction of action trajectories with a rapid response time of 0.4 ms and excellent durability of >10 000 cycles, bringing an important breakthrough of tactile intent recognition. Versatile applications prove the integrated functions of the IR touch sensor for great interactive potential in all-weather environments regardless of shading, dynamics, darkness, and noise. Unconscious and even hidden action features can be perfectly extracted with the ultrahigh recognition accuracy of 98.4% for intent recognition. The further auxiliary diagnostic test demonstrates the practicability of the IR touch sensor in telemedicine palpation and therapy. This groundbreaking integration of sensing, data reduction, and ultrahigh-accuracy recognition will propel the leapfrog development for conscious machine intelligence.

Keywords:

bionic structure

human-machine interactions

in-sensor computing

intent recognitions

touch sensors

In-Sensor Touch Analysis for Intent Recognition

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