A Reconfigurable High-Dynamic Range ∆Σ Front-End with Event-Based Decimation for Bandwidth-Efficient Implantable Neural Interfaces
Year: 2025
Type: conference-paper
Abstract: As the demand for high channel counts and high-resolution recordings of neural activity continues to grow, the increased power and data rate generated impose hard constraints on the telemetry capabilities of wireless implantable neural interfaces. To address this challenge, this work presents a novel system architecture for a reconfigurable readout circuit. It provides per-channel data rate reduction and adaptable bandwidth to match the characteristics and evolution of the neural signals under non-ideal electrode-tissue interactions. The system consists of a 14-bit hybrid continuous-time/discrete-time delta-sigma (CT/DT-∆Σ) analog front-end (AFE) followed by event-based decimation (EBD) which exploits the inherent sparsity in neural signals. The proposed AFE and EBD co-design was simulated using artifact-laden nonhuman primate microwire recordings. Results demonstrate a dynamic range of 76 dB, ensuring artifact robustness, along with up to a two-order-of-magnitude reduction in output data rate and power-area decimation footprint per channel, offering flexibility for high-quality (14 dB NRMSE) and medium-quality (8 dB NRMSE) reconstructions, based on the characteristics of the neural signals recorded at each channel.
Authors: Natalia Martínez, Juan Sapriza, Davide Schiavone, Giovanni Ansaloni, Luke Bashford, Andrew Jackson, David Atienza, Timothy G. Constandinou
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4411726028