A DSP Architecture for Distortion-Free Evoked Compound Action Potential Recovery in Neural Response Telemetry System

This paper presents a digital signal processing (DSP) architecture for real-time and distortion-free recovery of electrically-evoked compound action potentials (ECAPs) from stimulus artifacts and periodic noises in bidirectional neural response telemetry (NRT) system. In this DSP architecture, a low computation-cost bidirectional-filtered coherent averaging (BFCA) method is proposed for programmable linear-phase filtering of ECAPs, which can be easily combined with the alternating-polarity (AP) stimulation method to reject stimulus artifacts overlapped with ECAP responses. Design techniques including the configurable folded infinite-impulse response (IIR) filter and division-free averaging are also presented for efficient hardware implementation. Implemented in 180-nm CMOS process, the proposed DSP architecture consumes 10.03-mm² area and 2.35-mW post-layout simulated power. The efficacy of the DSP architecture in recovering ECAPs from recorded neural data contaminated by overlapped stimulus artifacts and periodic noises is validated in in-vivo electrical nerve stimulations. Experiment results show that compared with the previous coherent averaging technique, the proposed DSP architecture improves the signal-to-noise ratio (SNR) of ECAP responses by 11 dB and achieves a 3.1% waveform distortion that is 17.1× lower.