When measuring signals from the brain, signals from the heart and eyes get mixed in.  These signals must be filtered and sorted using ICA in order to find the signals which the experimenter is interested in. ICA is also able to separate signals from different regions of the brain.

University of Michigan - Ann Arbor

Independent component analysis (ICA) is a statistical and computational technique for revealing hidden factors that underlie sets of random variables, measurements, or signals. ICA defines a generative model for the observed multivariate data, which is typically given as a large database of samples.

Independent Component Analysis

Goodfellow, I., Bengio, Y., & Courville, A. (2016). $\mathit{Deep \ Learning.}$ MIT Press. Retrieved from [www.deeplearningbook.org](https://www.deeplearningbook.org) 

Deep Learning

Measuring Brain Signals Example (ICA)

If we have n diﬀerent microphones placed in diﬀerent locations, ICA can detect the changes in the volume between each speaker as heard by each microphone and separate the signals so that each $h_i$ contains only one person speaking clearly.

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