Simulating the recording parameters in electrophysiological recording

Christian Medical College, Vellore

The priciples involved in:

unipolar recording versus bipolar recording
near-field versus far-field recording
widely spaced electrodes versus closely spaced (bipolar needle) electrodes
propagating potential versus static depolarization (as in post-synaptic potentials)

can be studied using the following simulation. Vary the different controls and observe the unipolar and bipolar potentials when an excitation occurs (using the "excite" button). Click here to start the simulation: Basic recording arrangement

The above simulation can be extended to include an external noise source, namely, powerline noise at 50Hz. See how the noise is affected by electrode spacing as well as the Common Mode Rejection Ratio (CMRR) of the preamplifier. Click here to start the simulation: Noise in the recording arrangement

The use of a notch filter to reduce the 50Hz noise, can be studied using the next program. Note that the use of the filter reduces the noise but, can also distort the signal. Moreover, unless the filter notch exactly matches the powerline noise frequency, it will be of little use. Click here to start the simulation: Notch filtering to reduce noise

Averaging to reduce noise in evoked potentials

The following simulation shows how ensemble averaging can be used to reduce noisy evoked potentials. The upper trace shows repeated raw traces of evoked responses. The lower trace shows the accumulated average. Use the reset button to start averaging afresh. If the evoked response changes (try changing the stimulus PW or PA to achieve this), then the latency and amplitude can changed. Observe that the ensemble average is slow in tracking such changes. Compare this with weighted ensemble averaging. Click here to start the simulation: Averaging Evoked Potentials

Frequency filtering in electrophysiology

Use the following simulation to study the use of Low Pass, High Pass and Notch filters to separate electrophysiological signals, and obtain only the signal of interest. Click here to start the simulation: Filtering

For details of the mathematics behind some of the above simulations see:
Suresh R. Devasahayam, Signals and Systems in Biomedical Engineering: Signal Processing and Physiological Systems Modeling. Kluwer Academic/ Plenum Publishers, New York, June 2000.

Suresh Devasahayam