Digitally-Assisted Analog Front-end for Biomedical Sensors

Biomedical sensors are used to measure a myriad of biopotential signals including electroencephalogram (EEG), electrocardiogram (EKG), electromyogram (EMG), and neural field potential (NFP) signals [1], [2], [3]. Most of the useful information in these signals resides in the frequency range of 0.5 Hz to 1 kHz, allowing ultralow power circuits to be used when processing them. This is critical for systems that are implanted, since energy is extremely scarce, and the lifetime of the device must be on the order of 10 years. Unfortunately, these signals are often as small as 10 μVs, and their low frequency location make them vulnerable to aggressors such as DC offset, powerline noise, and flicker noise. DC offset can result from charge accumulation at the interface between the metal electrodes and the skin, and also from amplifier offsets caused by random mismatches. While chopper stabilization has proved effective at mitigating the effects of amplifier DC offset and flicker noise, electrode DC offset cannot be removed through chopping and must be high-pass filtered at the front end of the system to prevent saturation [1], [2], [3]. Powerline noise, typically at 50 or 60 Hz, is mostly a common-mode signal that requires adequate common-mode rejection. However, if there are mismatches or inductive loops in the electrodes, these aggressors can become differential-mode signals, corrupting the desired signal, and potentially saturating the system. In closed-loop deep brain stimulation systems, another aggressor arises from stimulation artifacts [4]. In that case, the NFPs can be much smaller than stimulation artifacts placing stringent requirements on the dynamic range of the system and potentially leading to signal corruption.