Function

Annotates stream with user-defined metadata

Example:

eeg$.pipe(addinfo({ samplingRate: 256, channelNames: ["Af7", "Fp1", "Fp2", "Af8"] })

Example:

eeg$.pipe(addSignalQuality())

Returns the average alpha power from a stream of PSDs

Example:

eeg$.pipe(epoch({ duration: 256, interval: 100, samplingRate: 256 }), fft({ bins: 256 }), alphaPower())

Takes a stream of PSDs and returns a sream of arrays, containing the average power in each channel

Example:

eeg$.pipe(epoch({ duration: 256, interval: 100, samplingRate: 256 }), fft({ bins: 256 }), sliceFFT(10, 20), averagePower())

Applies a bandpass filter to EEG Data. Can be applied to both raw or epoched data

Example:

eeg$
.pipe(bandpassFilter({ cutoffFrequencies: [2, 50], nbChannels: 4 }))

Returns the average beta power from a stream of PSDs

Example:

eeg$.pipe(epoch({ duration: 256, interval: 100, samplingRate: 256 }), fft({ bins: 256 }), betaPower())

Takes a stream of Samples and applies a Fast Fourier Transform to return a stream of PSDs (Power Spectral Density). Note: this operator works by buffering the stream of samples into buffers that are as long as the supplied number of bins. Because it doesn't allow as much flexibility in terms of how often data is emitted we recommend using a combination of the epoch and fft operators instead.

Example:

eeg$.pipe(bufferFFT({ bins: 1024 }))

Takes an array or RxJS buffer of EEG Samples and returns an Epoch.

Example:

eeg$.pipe(bufferTime(1000), bufferToEpoch({ samplingRate: 256 }))

Returns the average delta power from a stream of PSDs

Example:

eeg$.pipe(epoch({ duration: 256, interval: 100, samplingRate: 256 }), fft({ bins: 256 }), deltaPower())

Converts a stream of individual Samples of EEG data into a stream of Epochs of a given duration emitted at specified interval. This operator functions similarly to a circular buffer internally and allows overlapping Epochs of data to be emitted (e.g. emitting the last one second of data every 100ms).

Example:

eeg$.pipe(epoch({ duration: 1024, interval: 100, samplingRate: 256 }))

Applies a Fast Fourier Transform to a stream of Epochs of EEG data and returns a stream of PSDs (Power Spectral Density). Frequency resolution will be samplingRate / bins. If input Epoch duration is not equal to bins, data will be zero-padded or sliced so that is the same length as bins.

Example:

eeg$.pipe(epoch({ duration: 256, interval: 100, samplingRate: 256 }), fft({ bins: 256 }))

Returns the average gamma power from a stream of PSDs

Example:

eeg$.pipe(epoch({ duration: 256, interval: 100, samplingRate: 256 }), fft({ bins: 256 }), gammaPower())

Get a 2D data array organized by channel from an array of Samples. Credit to Ken from Seattle's elegant transposition http://www.codesuck.com/2012/02/transpose-javascript-array-in-one-line.html

Applies a highpass filter to EEG Data. Can be applied to both raw or epoched data

Example:

eeg$
.pipe(highpassFilter({ cutoffFrequency: 2, nbChannels: 4 }))

Applies a lowpass filter to EEG Data. Can be applied to both raw or epoched data

Example:

eeg$
.pipe(lowpassFilter({ cutoffFrequency: 50, nbChannels: 4 }))

A collection of useful statistics functions Adapted from Daniel Hug's gist: https://gist.github.com/Daniel-Hug/7273430

Applies a notch filter to EEG Data. Can be applied to both raw or epoched data. Has the ability to filter out harmonics of line noise (e.g. 120Hz, 180Hz), though this is only needed for high-frequency devices with >= 1000hz sampling rate

Example:

eeg$
.pipe(notchFilter({ cutoffFrequency: 60, nbChannels: 10, samplingRate: 1000, filterHarmonics: true }))

Takes a stream of PSDs and returns the average power for each of the classic EEG bands (alpha, beta, theta, etc.). Classic EEG bands can be overridden by providing a custom bands object (e.g. { lowAlpha: [7.5, 10], highAlpha: [10, 12.5] })

Example:

eeg$.pipe(epoch({ duration: 256, interval: 100, samplingRate: 256 }), fft({ bins: 256 }), powerByBand())

Slices a stream of PSDs to a specific frequency range defined by a minimum and maximum frequency in Hz

Example:

eeg$.pipe(epoch({ duration: 256, interval: 100, samplingRate: 256 }), fft({ bins: 256 }), sliceFFT([2, 30]))

Returns the average theta power from a stream of PSDs

Example:

eeg$.pipe(epoch({ duration: 256, interval: 100, samplingRate: 256 }), fft({ bins: 256 }), thetaPower())

Converts a stream of EEG data (either eegObjects or Epochs) from volts to microvolts

Example:

eeg&.pipe(toMicrovolts)

ZeroPads inputs for FFTs of non base 2