Low noise multi-channel biopotential wireless data acquisition system for dry electrodes

Abstract

The bioelectrical potentials generated within the human body are the result of electrochemical activity in the excitable cells of the nervous, muscular or glandular tissues. The ionic potentials are measured using biopotential electrodes which convert ionic potentials to electronic potentials. The commonly monitored biopotential signals are Electrocardiogram (ECG), Electroencephalogram (EEG) and Electromyogram (EMG). The electrodes used to monitor biopotential signals are Ag-AgCl and gold, which require skin preparation by means of scrubbing to remove the dead cells and application of electrolytic gel to reduce the skin contact resistance. The gels used in biopotential recordings dry out when used for longer durations and add noise to the signals and also prolonged use of gels cause irritations and rashes to skin. Also noises such as motion artifact and baseline wander are added to the biopotential signals as the electrode floats over the electrolytic gel during monitoring. To overcome these drawbacks, dry electrodes are used, where the electrodes are held against the skin surface to establish contact with the skin without the need for electrolytic fluids or gels. The major drawback associated with the dry electrodes is the high skin-electrode impedance in the low frequency range between 0.1-120 Hz, which makes it difficult to acquire clean and noise free biopotential signals. The paper presents the design and development of biopotential data acquisition and processing system to acquire biopotential signals from dry electrodes. The electrode-skin-electrode- impedance (ESEI) measurements was carried out for the dry electrodes by impedance spectroscopy. The biopotential signals are processed using an instrumentation amplifier with high CMRR and high input impedance achieved by boot strapping the input terminals. The signals are band limited by means of a second order Butterworth band pass filters to eliminate noise. The processed biopotential signals are digitized and transmitted wirelessly to a remote monitoring station.