Shigeki Arata
Nagoya University(JP)
Publications by Year
Research Areas
Neuroscience and Neural Engineering, Electrochemical sensors and biosensors, Analog and Mixed-Signal Circuit Design, Fuel Cells and Related Materials, Advanced Sensor and Energy Harvesting Materials
Most-Cited Works
- → A 6.1-nA Fully Integrated CMOS Supply Modulated OOK Transmitter in 55-nm DDC CMOS for Glasses-Free, Self-Powered, and Fuel-Cell-Embedded Continuous Glucose Monitoring Contact Lens(2018)42 cited
- → Wafer-scale development and experimental verification of 0.36 mm2228 mV open-circuit-voltage solid-state CMOS-compatible glucose fuel cell(2018)25 cited
- → A 385μm × 385μm 0.165 V 0.27 nW Fully-Integrated Supply-Modulated OOK CMOS TX in 65nm CMOS for Glasses-Free, Self-Powered, and Fuel-Cell-Embedded Continuous Glucose Monitoring Contact Lens(2018)25 cited
- → AI-Based Edge-Intelligent Hypoglycemia Prediction System Using Alternate Learning and Inference Method for Blood Glucose Level Data with Low-periodicity(2019)17 cited
- → Design of a Self-Controlled Dual-Oscillator-Based Supply Voltage Monitor for Biofuel-Cell-Combined Biosensing Systems in 65-nm CMOS and 55-nm DDC CMOS(2019)16 cited
- → A Solar-Cell-Assisted, 99.66% Biofuel Cell Area Reduced, Biofuel-Cell-Powered Wireless Biosensing System in 65-nm CMOS for Continuous Glucose Monitoring Contact Lenses(2019)12 cited
- → A 385×385µm<sup>2</sup> 0.165V 0.27nW Fully-Integrated Supply-Modulated OOK Transmitter in 65nm CMOS for Glasses-Free, Self-Powered, and Fuel-Cell-Embedded Continuous Glucose Monitoring Contact Lens(2019)12 cited
- → A Blood Glucose Level Prediction System Using Machine Learning Based on Recurrent Neural Network for Hypoglycemia Prevention(2018)11 cited
- → A 65-nm CMOS 1.4-nW Self-Controlled Dual-Oscillator-Based Supply Voltage Monitor for Biofuel-Cell-Combined Biosensing Systems(2019)11 cited
- → A 2.1-nW Burst-Pulse-Counting Supply Voltage Monitor for Biofuel-Cell-Combined Biosensing Systems in 180-nm CMOS(2019)10 cited