ABSTRACT
BACKGROUND: The peripheral nervous system is involved in a multitude of physiological functions. Recording neural signals provides information that can be used by diagnostic bioelectronic medicine devices, closed-loop neuromodulation therapies and other neuroprosthetic applications. The ability to accurately record these signals is challenging, due to the presence of various biological and instrument-related interference sources. NEW METHOD: We developed a common-mode interference rejection algorithm based on an impedance matching approach for bipolar cuff electrodes. Two unipolar channels were recorded from the two electrode contacts of a bipolar cuff. The impedance mismatch was estimated and used to correct one of the two channels. RESULTS: When applied to electrocardiographic (ECG) artifacts collected from three mice using CorTec electrodes, the algorithm reduced the interference to noise ratio (INR) over simple subtraction by 12â¯dB on average. The algorithm also reduced the INR of stimulation artifacts in recordings from three rats collected using flexible electrodes by an additional 2.4â¯dB. In the same experiments evoked electromyographic (EMG) interference was suppressed by 1.3â¯dB. COMPARISON WITH EXISTING METHODS: Simple subtraction is the common approach for reducing common-mode interference in bipolar recordings, however impedance mismatches that exist or emerge compromise its efficiency. CONCLUSIONS: The algorithm significantly reduced the common-mode interference from ECG artifacts, stimulation artifacts, and evoked EMG interference, while retaining neural signals, in two animal models and two recording setups. This approach can be used in a variety of different neurophysiological setups to remove common-mode interference from a variety of sources.
