Types of Anomalies

Several anomalies may compromise the quality of EEG data collected using dry sensors. Identifying and addressing these anomalies is imperative for accurate interpretation.

  1. Poor Contact

Incomplete contact between sensor and scalp, leading to low signal amplitude and high impedance.

  • Flat or noisy signals compared to nearby electrodes.

  • Visible air gaps between the sensor and the scalp.

  1. Movement

Scalp or hair movement due to participant activity, muscle engagement, or perspiration.

  • High-frequency noise bursts.

  • Erratic fluctuations in signal amplitude.

  1. Electrical Interference

External electrical noise from sources like power lines, computers, or electronic devices.

  • Consistent 50/60Hz hum in the signal.

  • Spikes or bursts of noise unrelated to brain activity.

  1. Hardware Malfunction

Hardware failure or sensor damage.

  • Complete absence of signal from a specific channel.

  • Erratic or distorted signals differing from other channels.

Additional Checks:

  1. Identify parallel vertical lines on Fp1 and Fp2 channels. These could possibly indicate eye blinking. These range between 1 to 2 seconds. Most of the signal quality in other sensors remains intact.

  1. Ensure consistency in graphs between corresponding sensors on the left and right hemisphere. Eg: Here F3 and F4 channels show varying signals, indicating improper connection of F4 channel on the scalp.

PreviousSetting up the device on the app

Last updated