An Artificial Tactile Neuron Enabling Spiking Representation of Stiffness and Disease Diagnosis

Junseok Lee; Seonjeong Kim; Seongjin Park; Jaesang Lee; Wonseop Hwang; Seong Won Cho; Kyuho Lee; Sun Mi Kim; Tae‐Yeon Seong; Cheolmin Park; Suyoun Lee; Hyunjung Yi

doi:10.1002/adma.202201608

journal article·2022-06Open access

An Artificial Tactile Neuron Enabling Spiking Representation of Stiffness and Disease Diagnosis

Junseok Lee, Seonjeong Kim, Seongjin Park, Jaesang Lee, Wonseop Hwang, Seong Won Cho, Kyuho Lee, Sun Mi Kim, Tae‐Yeon Seong, Cheolmin Park, Suyoun Lee, Hyunjung Yi

Advanced Materials· Volume 34· Issue 24

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Source abstract

Abstract

Abstract Mechanical properties of biological systems provide useful information about the biochemical status of cells and tissues. Here, an artificial tactile neuron enabling spiking representation of stiffness and spiking neural network (SNN)‐based learning for disease diagnosis is reported. An artificial spiking tactile neuron based on an ovonic threshold switch serving as an artificial soma and a piezoresistive sensor as an artificial mechanoreceptor is developed and shown to encode the elastic stiffness of pressed materials into spike frequency evolution patterns. SNN‐based learning of ultrasound elastography images abstracted by spike frequency evolution rate enables the classification of malignancy status of breast tumors with a recognition accuracy up to 95.8%. The stiffness‐encoding artificial tactile neuron and learning of spiking‐represented stiffness patterns hold a great promise for the identification and classification of tumors for disease diagnosis and robot‐assisted surgery with low power consumption, low latency, and yet high accuracy.

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Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Advanced Memory and Neural Computing · Neural dynamics and brain function

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Post‐Silicon Semiconductor Institute Korea Institute of Science and Technology Seoul 02792 Republic of Korea

YU‐KIST Yonsei University Seoul 03722 Republic of Korea

Department of Materials Science and Engineering Yonsei University Seoul 03722 Republic of Korea

Center for Neuromorphic Engineering Korea Institute of Science and Technology Seoul 02792 Republic of Korea

Department of Materials Science and Engineering Korea University Seoul 02841 Republic of Korea

Department of Materials Science and Engineering Seoul National University Seoul 08826 Republic of Korea

Department of Radiology Seoul National University Bundang Hospital Seoul National University College of Medicine Seongnam 13620 Republic of Korea

Division of Nano & Information Technology Korea University of Science and Technology Daejeon 34316 Republic of Korea

Funding

National Research Foundation of Korea

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