Package: PhysioPreprocess 0.4.1

Yusuke Matsui

PhysioPreprocess: Preprocessing Functions for PhysioExperiment Objects

Provides preprocessing functions for physiological signal data stored in 'SummarizedExperiment'-derived objects, including digital filters ('Butterworth' and notch), resampling, re-referencing, artifact detection, independent component analysis ('ICA') based artifact removal, and composable preprocessing pipelines.

Authors:Yusuke Matsui [aut, cre]

PhysioPreprocess_0.4.1.tar.gz
PhysioPreprocess_0.4.1.zip(r-4.7-x86_64)PhysioPreprocess_0.4.1.zip(r-4.7-arm64)PhysioPreprocess_0.4.1.zip(r-4.6-x86_64)PhysioPreprocess_0.4.1.zip(r-4.6-arm64)PhysioPreprocess_0.4.1.zip(r-4.5-x86_64)
PhysioPreprocess_0.4.1.tgz(r-4.6-x86_64)PhysioPreprocess_0.4.1.tgz(r-4.6-arm64)PhysioPreprocess_0.4.1.tgz(r-4.5-arm64)PhysioPreprocess_0.4.0.tgz(r-4.5-x86_64)
PhysioPreprocess_0.4.1.tar.gz(r-4.7-arm64)PhysioPreprocess_0.4.1.tar.gz(r-4.7-x86_64)PhysioPreprocess_0.4.1.tar.gz(r-4.6-arm64)PhysioPreprocess_0.4.1.tar.gz(r-4.6-x86_64)
PhysioPreprocess_0.4.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
PhysioPreprocess/json (API)

# Install 'PhysioPreprocess' in R:
install.packages('PhysioPreprocess', repos = c('https://x-biosignal.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/x-biosignal/physiopreprocess/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

cppopenmp

3.95 score 3 packages 40 exports 25 dependencies

Last updated from:a00b57e66f. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK224
linux-devel-x86_64OK247
source / vignettesOK208
linux-release-arm64OK188
linux-release-x86_64OK236
macos-release-arm64OK184
macos-release-x86_64OK372
macos-oldrel-arm64OK204
macos-oldrel-x86_64OK499
windows-devel-arm64OK284
windows-devel-x86_64OK266
windows-release-arm64OK297
windows-release-x86_64OK209
windows-oldrel-x86_64OK195
wasm-releaseOK120

Exports:applyPipelineasrCalibrateasrProcessassaySamplingRatesbaselineCorrectbutterworthFilterclassifyICAComponentscleanDatacleanLinecleanRawdatacreatePipelinedecimatedetectArtifactsdetectBadChannelsdetrendSignaldetrendSignalsfilterSignalsfirFiltergetCurrentReferenceicaDecomposeicaRemoveinterpolateinterpolateBadChannelsisAverageReferencedlfilterlfilterInitnotchFilterrejectBadEpochsremoveBaselineremoveICAComponentsrereferenceresamplerunICAsetAssaySamplingRatesosDesignsosfiltsosfiltfiltsosfiltInitStreamFilterzapLine

Dependencies:abindBiobaseBiocGenericscliDelayedArraydigestgenericsGenomicRangesIRangeslatticelifecycleMASSMatrixMatrixGenericsmatrixStatsPhysioExperimentRcpprlangS4ArraysS4VectorsSeqinfosignalSparseArraySummarizedExperimentXVector

ICA-Based Artifact Removal
Introduction | Setup | Creating Example Data | Workflow 1: Built-In ICA | Step 1: Decompose into Independent Components | Step 2: Identify Artifact Components | Step 3: Remove Artifact Components | Workflow 2: fastICA Package | Step 1: Run ICA | Step 2: Remove Components | Detecting Bad Channels | Interpolating Bad Channels | Recommended Preprocessing Order | Choosing the Number of Components | Summary | References
Rendered fromica-artifact-removal.Rmdusingknitr::rmarkdown

Last update: 2026-10-03
Started: 2026-10-03

Signal Preprocessing Guide
Introduction | Setup | Creating Example Data | Filtering | Moving Average Filter | Butterworth Filter | FIR Filter | Notch Filter | Resampling | Arbitrary Resampling | Integer-Factor Decimation | Integer-Factor Interpolation | Re-Referencing | Average Reference | Single Channel Reference | Linked Reference | Checking the Reference | Detrending | Linear and Mean Detrending | Alternative Detrending | Baseline Removal | Preprocessing Pipelines | Creating a Pipeline | Applying a Pipeline | Summary | References
Rendered frompreprocessing-guide.Rmdusingknitr::rmarkdown

Last update: 2026-10-03
Started: 2026-10-03

Readme and manuals

Help Manual

Help pageTopics
Apply preprocessing pipelineapplyPipeline
Calibrate Artifact Subspace Reconstruction (ASR)asrCalibrate
Apply Artifact Subspace Reconstruction (ASR)asrProcess
Per-assay sampling rates (moved to PhysioCore)assaySamplingRates
Baseline correctionbaselineCorrect
Butterworth filterbutterworthFilter
Classify ICA components as brain or artifactclassifyICAComponents
Clean data using an artifact removal pipelinecleanData
Remove line noise with CleanLinecleanLine
Automated raw-data cleaning (EEGLAB clean_rawdata-style)cleanRawdata
Preprocessing Pipeline for PhysioExperimentcreatePipeline
Decimate signaldecimate
Detect artifacts in continuous datadetectArtifacts
Detect bad channelsdetectBadChannels
Detrend signaldetrendSignal
Signal Detrending Functions for PhysioExperimentdetrendSignals
Causal and stateful IIR filtering primitivesfilters-causal
Moving average filterfilterSignals
FIR filterfirFilter
Get current referencegetCurrentReference
ICA and Artifact Removal for PhysioExperimenticaDecompose
Remove ICA componentsicaRemove
Interpolate signalinterpolate
Interpolate bad channelsinterpolateBadChannels
Check if data is average referencedisAverageReferenced
One-pass causal IIR filtering (Direct Form II Transposed)lfilter
Steady-state initial conditions for a one-pass IIR filterlfilterInit
Notch filter (power line noise removal)notchFilter
Print pipeline summaryprint.PhysioPipeline
Reject bad epochsrejectBadEpochs
Remove baselineremoveBaseline
Remove ICA componentsremoveICAComponents
Re-referencing Operations for EEG Datarereference
Resampling operations for PhysioExperimentresample
ICA-Based Artifact Removal for PhysioExperimentrunICA
Set a per-assay sampling rate (moved to PhysioCore)setAssaySamplingRate
Design a Butterworth filter in second-order-sections (SOS) formsosDesign
One-pass causal SOS filtering with optional carried statesosfilt
Zero-phase SOS filtering with state-initialised edge handlingsosfiltfilt
Steady-state initial conditions for a cascaded SOS filtersosfiltInit
Stateful streaming filter objectStreamFilter
Remove line noise with ZapLinezapLine