Welcome to PhysioView¶

About¶

PhysioView (formerly HeartView) is a Python-based signal processing and quality assessment pipeline with an interactive dashboard designed for wearable electrocardiograph (ECG), photoplethysmograph (PPG), and electrodermal activity (EDA) data collected in research settings.

In contrast to other existing tools, PhysioView provides an open-source graphical user interface intended to increase efficiency and accessibility for a wider range of researchers who may not otherwise be able to perform rigorous signal processing and quality checks programmatically.

PhysioView serves as both a diagnostic tool for evaluating data before and after artifact correction, and as a platform for post-processing physiological signals. We aim to help researchers make more informed decisions about data cleaning and processing procedures and the reliabiltiy of their data when wearable biosensor systems are used.

PhysioView works with data collected from the Actiwave Cardio, Empatica E4, and other physiological devices outputting data in comma-separated value (CSV) format.

Features¶

File Reader: Read and transform raw ECG, PPG, EDA, and accelerometer data from Actiwave European Data Format (EDF), archive (ZIP), and CSV files.
Configuration File Exporter: Define and save pipeline parameters in a JSON configuration file that can be loaded for use on the same dataset later.
Signal Filters: Filter out noise from baseline wander, muscle (EMG) activity, and powerline interference from your physiological signals.
Peak Detection: Extract heartbeats from ECG/PPG and skin conductance responses from EDA data.
Visualization Dashboard: View and interact with our signal quality assessment charts and signal plots of physiological time series, including preprocessed signals and their derived features (e.g., IBI, phasic and tonic components).
Signal Quality Metrics: Generate segment-by-segment signal quality metrics.
Automated Beat Correction: Appy a beat correction algorithm [1] to automatically correct artifactual beats.
Manual Beat Editor: Manually edit beat locations in cardiac signals.

Citation¶

If you use this software in your research, please cite the original paper.

@inproceedings{Yamane2024,
  author    = {Yamane, N. and Mishra, V. and Goodwin, M.S.},
  title     = {HeartView: An Extensible, Open-Source, Web-Based Signal Quality Assessment Pipeline for Ambulatory Cardiovascular Data},
  booktitle = {Pervasive Computing Technologies for Healthcare. PH 2023},
  series    = {Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering},
  volume    = {572},
  year      = {2024},
  editor    = {Salvi, D. and Van Gorp, P. and Shah, S.A.},
  publisher = {Springer, Cham},
  doi       = {10.1007/978-3-031-59717-6_8},
}

What’s New in PhysioView 1.0¶

This is the first official release of PhysioView, the renamed and updated continuation of HeartView.

Pipeline Enhancements¶

Introduced batch processing support.
Added postprocessing features, including heart rate variability (HRV) extraction.
Added automated beat correction functionality.
Introduced EDA processing and signal quality assessment support.

Dashboard Improvements¶

Enabled uploading of ZIP archives for batch processing.
Added a dropdown menu to select a subject’s data from a batch.
Enabled Beat Editor access within a modal.
Added rendering of automated and manual beat corrections directly in the dashboard’s signal plot and SQA charts.
Introduced export functionality for postprocessed data.

This release consolidates the improvements from HeartView’s final updates and marks the beginning of PhysioView as its own versioned project. For a full list of changes, see the full changelog.

Installation¶

The PhysioView source code is available from GitHub:

$ git clone https://github.com/cbslneu/physioview.git

See Installation for further info.

Contents¶

About PhysioView

PhysioView Pipeline

PhysioView Dashboard

PhysioView Beat Editor