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OmicsLake - OmicsLake: Versioned, On-Disk Omics Data Management for Bioconductor

A lightweight framework for versioned, on-disk omics data management using DuckDB, Arrow, and Parquet. It provides read/write-style functions, snapshots, and version-aware dataset lineage for tracked or explicitly annotated workflows. Adapters preserve supported Bioconductor containers, including SummarizedExperiment and MultiAssayExperiment, while retaining queryable tabular components.

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infrastructuredataimportdatarepresentation

4.82 score 41 scripts

PhysioCore - Core Data Structures for Physiological Signal Analysis

Provides the PhysioExperiment class, a 'SummarizedExperiment' extension for multi-modal physiological signal data (such as electroencephalography, electromyography, and electrocardiography). Includes core accessors, channel and event management, and basic 'S4' methods. Designed as a lightweight foundation for the Physio ecosystem of analysis packages.

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softwareinfrastructuredatarepresentationtimecourse

4.80 score 21 dependents

OmicsLake - OmicsLake: Versioned, On-Disk Omics Data Management for Bioconductor

A lightweight framework for versioned, on-disk omics data management using DuckDB, Arrow, and Parquet. It provides read/write-style functions, snapshots, and version-aware dataset lineage for tracked or explicitly annotated workflows. Adapters preserve supported Bioconductor containers, including SummarizedExperiment and MultiAssayExperiment, while retaining queryable tabular components.

Last updated

infrastructuredataimportdatarepresentation

4.69 score 41 scripts

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.

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cppopenmp

3.95 score 3 dependents

PhysioEEG - EEG Analysis Functions for PhysioExperiment Objects

Provides comprehensive electroencephalography (EEG) analysis functions for PhysioExperiment objects. Includes preprocessing (filtering, re-referencing, bad channel detection, interpolation, epoching, artifact rejection), independent component analysis (FastICA, Infomax, JADE) with automatic artifact detection, event-related potential (ERP) component detection and measurement (N100, P300, N400, P600, MMN), source localization (eLORETA, sLORETA, LCMV beamformer), EEG microstate analysis (K-means, AAHC), sleep staging (AASM criteria, spindle/K-complex/slow-wave detection), brain-computer interface features (CSP, SSVEP, motor imagery), clinical EEG analysis (spike detection, QEEG, asymmetry indices), time-frequency analysis (Morlet wavelet, STFT, multitaper, ERSP, ITC), connectivity analysis (coherence, PLV, wPLI, Granger causality), visualization (signal traces, ERP waveforms, topographic maps, spectrograms, connectivity plots, hypnograms, source maps), and simulated data generators for testing and demonstration.

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3.65 score

PhysioIO - Input and Output Functions for 'PhysioExperiment' Objects

Provides input and output capabilities for 'SummarizedExperiment'-derived physiological signal containers. Supported formats include 'EDF' and 'EDF+', 'BDF', 'GDF', 'BrainVision', 'HDF5', 'BIDS', comma-separated values, and 'MATLAB' files, together with 'DuckDB' database integration. Out-of-memory processing of large datasets is available through delayed 'HDF5' arrays.

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softwareinfrastructuredataimportdatarepresentation

3.65 score 1 dependents

PhysioMoCap - Motion Capture and Biomechanics Analysis for PhysioExperiment Objects

Provides motion capture, pose estimation, and biomechanical simulation analysis for PhysioExperiment objects. Includes I/O for C3D, Venus3D, GaitRec, OpenPose, DeepLabCut, MediaPipe, BVH, ASF/AMC, OpenSim, and generic CSV formats. Provides marker tracking (Hungarian algorithm), signal filtering, numerical differentiation, resampling, center of mass calculation, gait parameters, clinical statistics (ICC, SEM, MDC, Bland-Altman), movement phase segmentation, dynamic time warping, movement normalization, functional PCA, force-plate kinetics (GRF filtering, COP, loading rate, impulse), planar inverse dynamics (joint moments/power), EMG integration (rectification, RMS envelope, MVC normalization), gait/running/jump task schemas, OpenSim workflow integration, and biomechanics-specific visualization.

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3.54 score

PhysioAnalysis - Analysis and Visualization for PhysioExperiment Objects

Provides analysis and visualization functions for physiological signal data stored in 'PhysioExperiment' objects, which extend the Bioconductor 'SummarizedExperiment' container. Methods include the fast Fourier transform ('FFT'), time-frequency decomposition, epoching, functional connectivity (coherence and phase-based measures), graph and network metrics, statistical parametric mapping, and cluster-based permutation testing. Visualization utilities cover scalp topographic maps ('topoplots'), multichannel signal displays, and network graphs. Compiled routines are provided through 'Rcpp' and 'RcppArmadillo'.

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openblascppopenmp

3.48 score 1 dependents

PhysioCrossModal - Cross-Modal Coupling Analysis for PhysioExperiment Objects

Provides cross-modal coupling, connectivity, and synchrony analysis between physiological signals of different modalities (EEG, EMG, ECG, EDA, MoCap, fNIRS, etc.). Introduces a MultiPhysioExperiment container class for holding multiple PhysioExperiment objects at different sampling rates with temporal alignment. Includes spectral coherence, phase synchrony (PLV, PLI, wPLI), directed coupling (Granger causality), and time-domain coupling (cross-correlation) methods.

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3.18 score

PhysioDevices - Wearable and Lab-System Device Ingestion for PhysioExperiment Objects

Readers that ingest consumer-wearable and wired laboratory device exports into PhysioExperiment / MultiRatePhysioExperiment objects. Wearables: Empatica E4 CSV sessions and EmbracePlus Avro containers (multi-rate ACC / BVP / EDA / TEMP / HR / IBI streams), Shimmer GSR3+ Consensys exports (GSR, PPG, accelerometer), and Polar heart-rate / R-R interval exports. Lab systems: BIOPAC AcqKnowledge '.acq' files (per-channel rates and markers), Delsys Trigno EMG + IMU exports (multi-rate streams with per-sensor metadata), and Xsens MVNX motion-capture XML (segment kinematics, joint angles, centre of mass). Each import records a provenance entry and the correct per-signal sampling rates.

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3.18 score

PhysioECG - ECG Analysis Functions for PhysioExperiment Objects

Provides electrocardiography (ECG) analysis functions for PhysioExperiment objects. Includes R-peak detection (adaptive Pan-Tompkins), RR interval computation, HRV time-domain metrics (SDNN, RMSSD, pNN50), HRV frequency-domain analysis (VLF, LF, HF power), nonlinear HRV (Poincare, Sample Entropy, DFA), ECG morphology analysis (QRS boundaries, QT/QTc intervals), and signal quality assessment with ectopic beat correction.

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3.00 score

PhysioEMG - EMG Analysis Functions for PhysioExperiment Objects

Provides electromyography (EMG) analysis functions for PhysioExperiment objects. Includes envelope extraction (RMS, Hilbert), muscle activation onset detection (Hodges-Bui, Teager-Kaiser), fatigue analysis (median frequency shift), and muscle synergy decomposition (NMF, PCA, ICA).

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3.00 score

PhysioEDA - Electrodermal Activity Analysis for PhysioExperiment Objects

Provides electrodermal activity (EDA / skin conductance) analysis functions for PhysioExperiment objects. Includes preprocessing (filtering, downsampling), artifact detection and correction, tonic/phasic decomposition (highpass, median, CDA, cvxEDA), SCR peak detection, feature extraction, data transformations, signal quality assessment, visualization, and event-related SCR analysis.

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3.00 score

PhysioExperiment - Unified Analysis of Physiological Signals (Meta-Package)

A meta-package for the Physio ecosystem: attaching it loads and re-exports the public API of the core packages (PhysioCore data model, PhysioIO file/database I/O, PhysioPreprocess signal preprocessing, and PhysioAnalysis time-frequency/connectivity/network/statistics/visualization), so existing code that used the former monolithic 'PhysioExperiment' package keeps working. It also provides the GUI/REST launchers. Domain packages (EEG, ECG, EMG, EDA, MoCap, cross-modal, MSK-Net, OpenSim, clinical) are installed separately from the same ecosystem.

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softwaretimecoursepreprocessing

2.70 score

PhysioNetPhysiology - Network Physiology and Time-Delay-Stability Organ-Interaction Networks

Tools for Network Physiology: the study of dynamic interactions among diverse physiological systems (brain, heart, respiration, muscle). Implements Time Delay Stability (TDS) analysis to identify stable dynamic couplings between signals, builds organ-interaction networks whose links are significance-tested against phase-randomised surrogates, and quantifies how those networks reconfigure across physiological states (e.g. sleep stages). Designed to operate on the multimodal PhysioExperiment data model, but the core engine works on plain multivariate time series. Methods follow Bashan et al. (2012) <doi:10.1038/ncomms1705> and Bartsch et al. (2015) <doi:10.1371/journal.pone.0142143>.

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cpp

2.70 score

PhysioClinical - Clinical Outcome Measures and Responder Analysis

Validated clinical outcome-measure scoring (FMA, Berg, ARAT, TUG, 6MWT, Barthel, Katz, Lawton-Brody IADL, ...), MDC/MCID responder classification, ICF tagging, interval (Rasch) analysis of ordinal ADL/IADL instruments, and normative deviation scoring for the x-biosignal rehabilitation ecosystem.

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2.70 score

PhysioAppKit - Domain-Neutral Single-Case Engine for Physiological Application Layers

A small, domain-neutral engine for single-case (N-of-1) analysis shared by physiological application layers (rehabilitation, sport, psychophysiology, and others). Provides the Nonoverlap of All Pairs (NAP) effect size, a threshold-and-band single-case analysis, a phase plot, an honest hypothesis-to-evidence verdict combiner, and a dependency-free Rasch model for turning ordinal ratings into an interval scale. Application layers supply their domain slots (ontology, threshold, goal, reasoning, report) and call this engine; the engine knows nothing about any specific domain.

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2.18 score 1 dependents

PhysioStream - Governed Real-Time Streams for Physiological Data

Provides validated stream metadata, source and sink contracts, a bounded single-producer/single-consumer ring buffer, deterministic in-process loopback streams, capability-gated Lab Streaming Layer inlets and outlets, marker-event capture, governed Extensible Data Format read/write, and conversion of buffered physiological samples to PhysioExperiment objects, with explicit robust clock-offset, drift, jitter, multi-stream synchronization, transactional causal processing pipelines, explicit backpressure, monotonic latency measurement, and governed loopback, MQTT, and TTL stimulation-command outlets with arm, dead-man, maximum, duplicate-ID, and refractory interlocks, plus causal EMG-onset, EEG-ERD, and phase-target detectors bound to commit-before-stimulation closed-loop session control and provenance, with a bounded live biofeedback scope and marker-anchored video-time synchronization.

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cpp

2.18 score 1 dependents

PhysioRecipes - Reproducible Analysis Case Studies for the PhysioExperiment Ecosystem

A version-controlled database of self-contained, reproducible analysis case studies on public physiological data, built on the PhysioExperiment ecosystem. Each case states a proposition, answers a question on a public dataset and completes through to figures and a conclusion, with every reported number traced to an artifact and the whole op-DAG replayable byte-identically. The package ships the verified run bundles and a small API to browse the case metadata, open a case's bundle, and check the invariants that every case must satisfy.

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1.70 score

PhysioWearable - Free-Living Wearable Accelerometry for the Physio Ecosystem

Free-living physical-activity analysis of raw tri-axial accelerometer data, following the GGIR methodology. Computes the Euclidean-Norm-Minus-One (ENMO) acceleration metric with epoch aggregation, gravity-based auto-calibration (van Hees et al. 2014), non-wear detection, step detection, physical-activity intensity classification and bout detection, and a free-living physical-behaviour summary (intensity gradient and MX metrics, activity fragmentation, diurnal profile and guideline attainment) linked to the ICF Activities and Participation performance qualifier. Ingests raw accelerometer exports (GENEActiv / ActiGraph / Axivity CSV) into PhysioExperiment objects.

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1.70 score

PhysioHDEMG - High-Density Surface EMG Motor-Unit Decomposition for the Physio Ecosystem

Decomposition of high-density surface electromyography (HD-sEMG) electrode-grid recordings into constituent motor-unit discharge patterns by convolutive blind source separation (extension, whitening and a fixed-point contrast maximisation with convolution-kernel-compensation refinement), following Holobar & Zazula (2007) and Negro et al. (2016). Provides motor-unit pulse trains, firing statistics (discharge rate, recruitment / derecruitment, pulse-to-noise ratio and silhouette quality), spatial motor-unit action-potential maps over the electrode grid, and a ground-truth HD-sEMG simulator for validation.

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1.70 score

PhysioTwin - Digital-Twin Simulation and Data Assimilation for Physiological and Movement Systems

A digital-twin engine that couples mechanistic simulation of movement and physiology with realistic sensor emulation and data assimilation, so a subject-specific model can be personalised from real measurements and then used for in-silico experiments. It ships a parameterised limb model (forward dynamics) and mechanistic physiological and network generators -- a Jansen-Rit neural-mass EEG column with an optional 1/f aperiodic background, a McSharry limit-cycle electrocardiogram, a Windkessel arterial blood-pressure model with a closed-loop baroreflex, a respiration waveform and respiratory-sinus-arrhythmia heart-rate-variability generator, and Kuramoto coupled-oscillator and Matsuoka central-pattern-generator rhythms. A forward sensor-emulation layer turns clean signals into realistic recordings (inertial-measurement-unit, optical-marker occlusion, surface-electromyography electrode and electrocardiogram lead), with richer chains for multi-channel electromyography crosstalk and amplifier characteristics, multi-lead electrocardiogram and analogue-to-digital conversion. A data-assimilation layer personalises the twin to recorded data with a family of state-space estimators (unscented, extended, particle and ensemble Kalman filters), likelihood-free Bayesian calibration (rejection and sequential Monte-Carlo approximate Bayesian computation), Markov-chain Monte- Carlo, a Gaussian-process surrogate and GP-accelerated (Bayesian-optimisation) calibration -- including personalising the closed-loop cardiovascular- respiratory twin to measured heart-rate and blood-pressure variability -- as well as particle Markov-chain Monte-Carlo and particle Gibbs (with ancestor sampling) for whole-waveform Bayesian fitting -- including a whole-record fit of the closed-loop cardiovascular model that identifies the baroreflex and respiratory gains a summary fit cannot, with either a resonant Mayer-oscillator or a broadband first-order-autoregressive low-frequency component for records without a distinct Mayer peak -- and Fisher-information optimal experimental design for choosing the most informative experimental condition. Applications include single- and population-level in-silico intervention (perturb parameters and predict the change, with effect size, responder rate and statistical power), multi-modal coupling, and labelled synthetic training-data generation with sensor domain randomisation, all backed by a simulation validity-and-verification harness (identifiability, global sensitivity and validation against real recordings). A clinical decision loop ties these together as research tooling: a personalised twin is certified by a validation gate (goodness of fit and parameter identifiability) before it may advise, candidate interventions are scored with their predictive uncertainty and ranked on multiple criteria, mechanistic predictions are reconciled with external evidence rather than overriding it, and a follow-up measurement is checked against the predicted interval. A closed-loop cardiovascular-respiratory model couples a delayed baroreflex with respiration to produce emergent Mayer waves and respiratory sinus arrhythmia, and an optional bridge holds the twin's predictions to account against a real single-case (SCED/MCID/ICF) clinical evaluation.

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1.70 score

PoseFixeR - Anomaly Detection and Correction for OpenPose Gait Analysis

Detects and corrects the anatomical, biomechanical, physical, and detection-confidence anomalies that arise in two-dimensional video-based gait analysis with OpenPose, then imputes and smooths the corrected keypoint trajectories. Implements the method of Sugiyama, Uno and Matsui (2023) <doi:10.1371/journal.pcbi.1009989>.

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1.70 score

PhysioRehab - ICF-Native Single-Case Clinical-Reasoning Tools for Rehabilitation

Re-centres physiological measurement around the way rehabilitation reasons about the individual: International Classification of Functioning (ICF) semantics, individualised goal-referenced outcomes (Goal Attainment Scaling), single-case change detection that fuses quantitative signals with qualitative ICF qualifiers, a hypothesis-to-evidence reasoning scaffold that keeps the clinician in the loop, and an auto-drafted, ICF-structured progress note. Adapters ingest real signals from the ecosystem (markerless gait from 'PhysioMoCap', muscle fatigue from 'PhysioEMG'); the ICF layer resolves against 'PhysioAnnotationHub'; single-case statistics come from 'PhysioAppKit'. The worked instance is stroke hemiplegic gait; the framework is condition-agnostic. A research tool with synthetic examples, not a medical device: outputs are clinician-in-the-loop measurement, documentation and reasoning support, never diagnosis.

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1.70 score

synergyMixR - Mixture-Based Muscle Synergy Analysis

Provides tools for analyzing muscle synergy using various statistical methods including MPCA and MFA. Enables researchers to identify distinct subgroups within populations that exhibit different muscle synergy patterns, rather than forcing all subjects into a single global model.

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openblascppopenmp

1.70 score

PhysioReport - Clinical Report Generation for the x-biosignal Ecosystem

Parameterized, bilingual (Japanese/English), colorblind-safe clinical reports (gait, HRV, EMG) with normative overlays and MDC/MCID-annotated change for the x-biosignal physiological signal ecosystem.

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1.70 score

PhysioPipe - Reproducible 'targets' Pipelines for Physiological Signal Analysis

A collection of reusable 'targets' target factories for the Physio ecosystem: drop-in pipelines for the standard single-modality analyses (ECG heart-rate variability, EEG band power, EMG amplitude/fatigue, EDA skin conductance) plus multi-record cohort branching and Quarto reporting. Each factory returns a list of targets so a whole reproducible '_targets.R' is a couple of lines, with incremental re-runs and byte-level provenance.

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1.70 score

PhysioLake - Versioned, Lineage-Tracked Data Management for the Physio Ecosystem

Integrates the PhysioExperiment ecosystem with 'OmicsLake', a versioned, on-disk data-management engine built on 'DuckDB', 'Apache Arrow' and 'Parquet' with automatic dataset-level lineage tracking. Rather than reimplementing a data lake, PhysioLake inherits the domain-agnostic OmicsLake core (storage backend, snapshots and time-travel, cross-dataset lineage, query layer) and registers physiology-specific adapters and utilities: 'PhysioExperiment' objects are stored and retrieved with full fidelity, preserving the sampling-rate slot and the W3C-PROV provenance held in object metadata. This connects the ecosystem's per-object (micro) provenance with the lake's cross-dataset (macro) lineage.

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1.70 score

PhysioClinStats - Clinical Inference Engine for Physiological Signal Studies

Statistical inference for rehabilitation studies: mixed-effects / MMRM longitudinal models, single-case (N-of-1) designs, estimands with multiple imputation, and per-estimate uncertainty. Heavy modelling backends are optional (guarded) Suggests.

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1.70 score

PhysioGaitNorm - Normative Gait Reference Database for the Physio Ecosystem

Normative gait reference data for the Physio ecosystem: mean and standard-deviation kinematic waveform bands over the gait cycle (51- and 101-point) for the nine Gait Deviation Index / Gait Profile Score kinematic variables, together with a normative feature reference set for constructing the Gait Deviation Index. Provides dataset loaders, a catalogue, and a documented provenance and version manifest. The bundled "adult_reference" set is derived from real motion-capture data - the 24 young healthy adults (age 21-37) of the public WBDS dataset (Fukuchi, Fukuchi & Duarte 2018, CC-BY), overground comfortable-speed walking, time-normalised to the gait cycle; the per-subject waveforms also form the normative feature population for the Gait Deviation Index. Sagittal angles use the Z-axis convention; frontal/transverse axes were resolved by matching published normative shape (Perry & Burnfield; Winter). See the provenance manifest and citations. Consumed by gait-index calculations (Schwartz & Rozumalski 2008 GDI; Baker et al. 2009 GPS/GVS/MAP).

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1.70 score

PhysioAnnotationHub - Anatomical and Clinical Knowledge Graph for Physiological Data

Centralized annotation hub providing anatomical ontology, muscle/bone metadata, nerve innervation, clinical codes (ICD-10, ICF), and knowledge graph queries for the physio-ecosystem.

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1.70 score

PhysioMSKNet - Musculoskeletal Network Analysis for Physiological Data

Network science analysis of the human musculoskeletal system. Implements hypergraph representations of muscle-bone connections, physical simulation via damped harmonic oscillators, perturbation-based impact scoring, community detection, and clinical outcome prediction. Based on Murphy et al. (2018) <doi:10.1371/journal.pbio.2002811>.

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1.70 score

PhysioHeadModels - Realistic EEG Head Models and Forward Solvers for the Physio Ecosystem

Provides EEG forward-model building blocks for the Physio ecosystem: an analytic multi-concentric-sphere leadfield, a boundary element method (BEM) solver with the double-layer operator for custom head meshes, cortical source-space helpers with surface normals, and on-demand fetchers for large published head models (the New York Head and FreeSurfer fsaverage) that are downloaded to a per-user cache rather than shipped.

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1.70 score

PhysioNeurophys - TMS and Peripheral Motor Neurophysiology Analysis

Provides transcranial magnetic stimulation (TMS) and peripheral motor-neurophysiology analysis for PhysioExperiment objects. Includes motor-evoked-potential amplitude and latency, Boltzmann recruitment curves, H-reflex recruitment and Hmax/Mmax metrics, F-wave persistence and latency, paired-pulse inhibition and facilitation, cortical silent-period timing, TMS-EEG pulse removal, source-informed SSP-SIR and SOUND cleaning, TMS-evoked-potential summaries, the PREP2 upper-limb stroke-prognosis algorithm, and a governed TMS pulse and intensity metadata schema.

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1.70 score

PhysioTrial - Randomization, Allocation Concealment and Blinding for Clinical Trials

Provides reproducible trial-design infrastructure for simple, permuted-block, stratified-block, and Pocock-Simon minimization randomization. Sealed allocation sequences, deterministic audit fingerprints, treatment-code management, append-only unblinding logs, CONSORT/SPIRIT operations, adverse-event summaries, explicit analysis populations, missing-data hooks, and endpoint-analysis wrappers support auditable clinical-trial workflows. Deterministic CDISC SDTM-shaped and ADaM-shaped exports provide linked tabulation and analysis datasets without claiming external regulatory conformance.

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1.70 score

PhysioNIRS - Governed Near-Infrared Spectroscopy Data and SNIRF Input/Output

Provides strict input, output, measurement identity, probe geometry, optical-density, modified Beer-Lambert, motion-correction, and short-separation nuisance, signal-quality, channel-pruning, and live neurofeedback contracts for continuous-wave functional near-infrared spectroscopy data stored in 'PhysioExperiment' objects. Shared Near Infrared Spectroscopy Format ('SNIRF') files are read and written through structured 'HDF5' APIs while preserving time bases, measurement order, probe coordinates, metadata tags, stimulus tables, and processing provenance.

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1.70 score

PhysioML - Leakage-Aware Machine Learning for Physiological Time Series

Provides leakage-aware, reproducible feature transforms and reference deep-learning workflows for physiological time series stored in PhysioExperiment objects. Canonical catch22 characteristics are computed through the official R backend, while ROCKET and MiniRocket transforms use guarded optional Python backends. Guarded optional torch and luz backends provide case-aware datasets, compact neural architectures, training, and prediction. Explicit contracts preserve case, channel, feature, normalization, backend, and model provenance without claiming clinical validation. Named transfer-learning policies, leakage-safe CORAL alignment, and immutable hash-verified foundation-model caches provide bounded reuse across domains.

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1.70 score

PhysioCompliance - Evidence, Privacy, and Lifecycle Controls for Physiological Records

Provides deterministic, tamper-evident audit trails, externally authenticated electronic signatures, explicit de-identification policies, project-owned lifecycle and risk-document templates, normalized requirement-risk-control-test traceability, objective-evidence verification, and read-only ecosystem engineering-readiness checks for PhysioExperiment records and packages. Reports expose structural, linkage, record-state, signature, privacy, traceability, and package-readiness findings without repairing stored evidence. These technical controls and documentation aids do not determine device status, assign risk acceptability, authorize release, or establish conformity with a regulatory framework or standard.

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1.70 score
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