Bio-potential detection is important for bio-medical diagnostics and research. Bio-potentials are generally weak (µV) with high offsets (100mV level). Low noise processing is critical to extract the signal. In this paper, we report the design of a single-chip CMOS bio-potential detector. The design uses chopping to suppress the low-frequency noise in CMOS amplifiers. The strong offset is removed by a high gain feedback loop with a low pass filter with 1Hz cut-off frequency. A high-gain front stage is designed to further suppress the noise. The nonlinearity in the high-gain front stage can be compensated by calibration. A chopping-pulse free switched-capacitor low-pass filter follows for variable gain amplification and noise bandwidth limiting. The circuit is designed in a 0.35µm CMOS process for 50µV–10mV bio-potentials with offset up to 100mV. HSPICE simulations verify that the designed detector achieve the gain of 400 and 4000. The selectable bandwidth is 1kHz for EEG/ECG/EMG or 5kHz for extra-cellular recording. The design does not require external capacitors. The in-band noise is lower than 58nV/Hz0.5. The power consumption of the detector is less than 160µW. The die area is 0.3mm×0.7mm.
[1]
D. Schmitt-Landsiedel,et al.
A 128 /spl times/ 128 CMOS bio-sensor array for extracellular recording of neural activity
,
2003,
2003 IEEE International Solid-State Circuits Conference, 2003. Digest of Technical Papers. ISSCC..
[2]
Maysam Ghovanloo,et al.
A Low-Noise Preamplifier with Adjustable Gain and Bandwidth for Biopotential Recording Applications
,
2007,
2007 IEEE International Symposium on Circuits and Systems.
[3]
David A. Johns,et al.
Analog Integrated Circuit Design
,
1996
.
[4]
B. Eversmann,et al.
A 128 × 128 CMOS bio-sensor array for extracellular recording of neural activity
,
2003
.
[5]
Refet Firat Yazicioglu,et al.
A 60 $\mu$W 60 nV/$\surd$Hz Readout Front-End for Portable Biopotential Acquisition Systems
,
2007,
IEEE Journal of Solid-State Circuits.
[6]
S. Hafizovic,et al.
CMOS microelectrode array for bidirectional interaction with neuronal networks
,
2006,
IEEE Journal of Solid-State Circuits.