Research & IP

80+ peer-reviewed articles and a growing portfolio of granted and pending patents.

NeuralTree: A 256-Channel 453μW-Power Closed-Loop Neuromodulation System-on-Chip with Embedded Machine Learning for Seizure and Tremor Control and Finger Movement Decoding

NeuralTree: A 256-Channel 453μW-Power Closed-Loop Neuromodulation System-on-Chip with Embedded Machine Learning for Seizure and Tremor Control and Finger Movement Decoding

A 256-Channel 0.227µJ/Class Versatile Brain Activity Classification and Closed-Loop Stimulation SoC with 0.004mm2-1.51 µW/Channel Mixed-Signal Front-End

2022 SSCS-Brain Joint Society Best Paper Award

A 256-Channel 0.227µJ/Class Versatile Brain Activity Classification and Closed-Loop Stimulation SoC with 0.004mm2-1.51 µW/Channel Mixed-Signal Front-End

An Ultra-Low-Power Extreme Gradient-Boosted Classifier for Implantable Medical Devices

An Ultra-Low-Power Extreme Gradient-Boosted Classifier for Implantable Medical Devices

REST: An Ultra-Fast Graph Neural Network Framework with Residual State Update for Memory-Efficient Seizure Detection in Clinical Devices

REST: An Ultra-Fast Graph Neural Network Framework with Residual State Update for Memory-Efficient Seizure Detection in Clinical Devices

MiBMI: The First Fully-Integrated Miniaturized Brain–Machine Interface Chipset Enabling Low-Latency Brain-to-Text Conversion

MiBMI: The First Fully-Integrated Miniaturized Brain–Machine Interface Chipset Enabling Low-Latency Brain-to-Text Conversion

A 512-Channel, 31-Class, 2.46-mm2 Neural Recording and Decoding System with Sub-900µW Power Consumption for Handwritten Character Decoding

A 512-Channel, 31-Class, 2.46-mm2 Neural Recording and Decoding System with Sub-900µW Power Consumption for Handwritten Character Decoding

A Mixed-Signal Compressive Sensing System for High-Density ECoG Recording with 10.5µW and 250 × 250 µm² per Channel

A Mixed-Signal Compressive Sensing System for High-Density ECoG Recording with 10.5µW and 250 × 250 µm² per Channel

A 49.8-mm² IR-UWB Transmitter With Sub-27pJ/b/m Energy Efficiency and 500Mb/s Data Rate for Neural Implants With Extended, Meter-Range Transmission

A 49.8-mm² IR-UWB Transmitter With Sub-27pJ/b/m Energy Efficiency and 500Mb/s Data Rate for Neural Implants With Extended, Meter-Range Transmission

A 3mm2, Energy-Efficient, FDMA Transmitter with On-Chip Antenna for Next-Generation High-Channel-Count Neural Implants Supporting 50Mb/s to 1.2Gb/s at 1.49−7.26mW

A 3mm2, Energy-Efficient, FDMA Transmitter with On-Chip Antenna for Next-Generation High-Channel-Count Neural Implants Supporting 50Mb/s to 1.2Gb/s at 1.49−7.26mW

A 16-Channel 60µW Neural Synchrony Processor for Multi-Mode Phase-Locked Neurostimulation in Psychiatric Disorders

A 16-Channel 60µW Neural Synchrony Processor for Multi-Mode Phase-Locked Neurostimulation in Psychiatric Disorders

ResOT: An Energy-Aware and Memory-Efficient Oblique Decision Tree for On-Chip Neural Signal Classification in Epilepsy, Parkinson's Disease, and BCI

ResOT: An Energy-Aware and Memory-Efficient Oblique Decision Tree for On-Chip Neural Signal Classification in Epilepsy, Parkinson's Disease, and BCI

A 16-channel 1.1mm2 implantable seizure control SoC with sub-μW/channel consumption and closed-loop stimulation in 0.18µm CMOS

A 16-channel 1.1mm2 implantable seizure control SoC with sub-μW/channel consumption and closed-loop stimulation in 0.18µm CMOS

Improved detection of Parkinsonian resting tremor with feature engineering and Kalman filtering

Improved detection of Parkinsonian resting tremor with feature engineering and Kalman filtering

A Miniaturized 1.5m-Range IR-UWB Transmitter with Co-Designed PA–Antenna Interface for Wireless Implantable Neural Interfaces

A Miniaturized 1.5m-Range IR-UWB Transmitter with Co-Designed PA–Antenna Interface for Wireless Implantable Neural Interfaces

A 32-Channel 196-μW Logarithmic SoC for Brain Network Connectivity Extraction and Adaptive Psychiatric Symptom Classification

A 32-Channel 196-μW Logarithmic SoC for Brain Network Connectivity Extraction and Adaptive Psychiatric Symptom Classification