A Neural-ADC-Compatible Fully-Dynamic Lossless Adaptive Resolution Compression Technique for Energy-Constrained Bio-Signal Recording

This paper presents a lossless adaptive-resolution compression technique intended for energy-constrained implantable neural interface microsystems. The proposed method seamlessly integrates with the widely-adopted ADC-direct front-end architectures with minimal overhead and no need for architectural modification, making it universally-compatible. It maintains an always-Nyquist sampling rate and employs a single-bit quantizer to overcome the limitations of previously-reported adaptive sampling and adaptive resolution methods (e.g., missing short-time events, nonlinearity, power/area overdesign). It also features continuous DC variation calculation and adjustable hysteresis bands. The method is optimized and validated through MATLAB simulations, followed by synthesis and implementation in a standard 130nm CMOS process, resulting in an active area of 0.0529 mm
²
and total power consumption of 1.9µW @ 128kHz. Post-layout verification was conducted using prerecorded EEG and ECG datasets, demonstrating a minimum compression ratio of 83.75% of the theoretical maximum (i.e., $\frac{{{N_H}}}{{{N_L}}}$), highlighting its effectiveness for implantable neural recording devices.