| Autor: |
Liu, Huaiyu, Lin, Yang, Qi, Liang, Lou, Yongwei, Wang, Guoxing, Liu, Yan |
| Zdroj: |
Circuits and Systems I: Regular Papers, IEEE Transactions on; 2023, Vol. 70 Issue: 3 p1214-1227, 14p |
| Abstrakt: |
Concurrent neural signal instrumentation withstanding neural stimulation artifacts is essential for bi-directional neural interfaces to guarantee signal integrity. In this work, different front-end structures and stimulation artifact mitigation techniques are firstly reviewed to benchmark their step response speed. Then, a mixed domain level-crossing scheme is proposed to achieve fast dynamic response with minimized hardware overhead. The benefit of extending the phase detection range of the phase detectors in VCO-based continuous time $\rm \Delta \Sigma $ modulators is investigated with stability and noise consideration. Then a shift-register-based phase counter is proposed to extend the phase detectors’s detection range, thereby increase quantization resolution and stability margin for in-band noise optimization. The proposed VCO-based neural front-end was fabricated in a 180 nm CMOS process. The prototype achieves $6.38~\mu $ Vrms input-referred noise over 0.5 Hz-10 kHz bandwidth. With a linear input range of 120 mVpp, it exhibits a SNDR of 71.6 dB and a DR of 77.0 dB, which could be further extended up to 100 dB in the artifact adaption mode. Measurements verify that the proposed neural front-end can recover from rail-to-rail differential mode or common mode artifacts within 10 $\mu \text{s}$ (minimum $6.25~\mu \text{s}$ ) while the superposed small signal can be recorded uninterruptedly. |
| Databáze: |
Supplemental Index |
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