Publications by Cong Ding | EPFL Graph Search

A 49.8-mm 2 IR-UWB Transmitter With Co-Designed Power Amplifier and Antenna for Neural Implants With Extended Transmission Range

Anja Skrivervik, Mahsa Shoaran, Mingxiang Gao, Cong Ding

This work presents an implantable impulse-radio ultrawideband transmitter (IR-UWB TX) optimized for high-density neural recording. To address the tradeoffs between data rate, transmission range, implant size, and power consumption, we propose a novel co-de ...

Institute of Electrical and Electronics Engineers (IEEE)2025

Neurostimulation and Wireless Data Transmission Circuits for Implantable High-Density Neural Interfaces

Cong Ding

Over the past years, implantable closed-loop neural interfaces have received increasing attention for their potential to enhance the understanding of the brain, treat neurological disorders, and provide unprecedented opportunities for individuals with para ...

EPFL2024

A 0.14-nJ/b 200-Mb/s 2.7-3.5-GHz Quasi-Balanced FSK Transceiver With PLL-Based Modulation and Sideband Energy Detection

Cong Ding, Bowen Wang

This paper describes a balanced frequency shift keying (FSK) modulation, namely quasi-balanced FSK (QB-FSK), for energy-efficient high-data-rate communication. Not suffering from data-pattern dependency, the proposed modulation method enables frequency mod ...

2024

A 3 mm2, Energy-Efficient, Multi-Data-Rate, FDMA Transmitter with On-Chip Antenna for Next-Generation Neural Implants

Anja Skrivervik, Mahsa Shoaran, Mingxiang Gao, Cong Ding

This paper presents a versatile energy-efficient wireless transmitter (TX) for neural implants with high/ultrahigh channel counts. The TX supports a wide range of data transmission rates, from 50Mb/s to 1.2 Gb/s, through a novel dual-modulation approach. O ...

IEEE2024

A 49.8mm2 Fully Integrated, 1.5m Transmission-Range, High-Data-Rate IR-UWB Transmitter for Brain Implants

Anja Skrivervik, Mahsa Shoaran, Mingxiang Gao, Cong Ding

Implantable neural interfaces hold great potential to restore function in individuals impaired by paralysis, limb amputations, or various neurological conditions. The need for precise mapping of neuronal activity across various brain regions and enhancing ...

IEEE2024

A 16-Channel Low-Power Neural Connectivity Extraction and Phase-Locked Deep Brain Stimulation SoC

Mahsa Shoaran, Uisub Shin, Cong Ding

Growing evidence suggests that phase-locked deep brain stimulation (DBS) can effectively regulate abnormal brain connectivity in neurological and psychiatric disorders. This letter therefore presents a low-power SoC with both neural connectivity extraction ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

NeuralTree: A 256-Channel 0.227-mu J/Class Versatile Neural Activity Classification and Closed-Loop Neuromodulation SoC

Stéphanie Lacour, Mahsa Shoaran, Uisub Shin, Cong Ding, Alix Esther Anne Trouillet, Emilie Cornelia Maria Revol, Bingzhao Zhu

Closed-loop neural interfaces with on-chip machine learning can detect and suppress disease symptoms in neurological disorders or restore lost functions in paralyzed patients. While high-density neural recording can provide rich neural activity information ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

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

Mahsa Shoaran, Uisub Shin, Cong Ding, Laxmeesha Somappa

Measuring neural oscillatory synchrony facilitates our understanding of complex brain networks and the underlying pathological states. Altering the cross-regional synchrony-as a measure of brain network connectivity-via phase-locked deep brain stimulation ...

IEEE2022