All research areas

Multimodal cardiovascular and physiological signal research

Cardiology

The Cardiology area is a web workspace for multimodal cardiovascular and physiological signal research. Upload ECG, RR intervals, blood pressure, PPG, and respiration recordings; run validated preprocessing and metrics pipelines; link data to subjects; compare cohorts; and generate AI-assisted interpretations grounded in computed metrics.

Use cases

Start from a research scenario

Guided workflows map common questions to data requirements, analysis steps, and documentation — pick the scenario closest to your study.

All Cardiology use cases

Holter HRV analysis

Research question: What are the time-domain, frequency-domain, and nonlinear HRV characteristics of this recording, and is the signal quality sufficient for reliable metrics?

Analyze a single ECG or Holter recording — preprocess the waveform, compute HRV metrics, inspect signal quality in the waveform explorer, and generate analytical interpretation.

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Wearable RR cohort

Research question: How do HRV metrics differ across participants, treatment arms, or diagnostic groups when only RR interval data is available?

Process RR interval exports from wearables or Holter summary files across a cohort, batch HRV computation, and compare metrics between groups.

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Multimodal autonomic profiling

Research question: How do heart rate variability, blood pressure dynamics, and respiration interact for this participant? What do baroreflex sensitivity and respiratory sinus arrhythmia reveal about autonomic regulation?

Combine ECG, blood pressure, and respiration recordings for a single subject — compute cross-modal coupling metrics and generate mechanistic AI interpretation.

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Cohort endpoints

Research question: Do HRV, blood pressure, or other cardiovascular metrics differ significantly between groups, and do signal-derived indices associate with clinical outcomes in this cohort?

Compare physiological metrics across treatment groups, identify outliers, and explore research-only signal-derived risk stratification tied to outcomes metadata.

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Capabilities

Platform features

Everything available in the Cardiology workspace today — pipelines, explorers, exports, and provenance.

  • Experiment containers for cardiovascular signal studies
  • ECG upload in WFDB, CSV, and EDF waveform formats
  • ECG preprocessing with R-peak detection, RR intervals, and signal quality index
  • Time-domain, frequency-domain, and nonlinear HRV metrics
  • Full ECG analysis pipeline chaining preprocess and HRV in one run
  • RR-only CSV upload for Holter and wearable exports
  • Arrhythmia burden metrics: irregularity percentage, pause burden, and beat flags
  • PPG preprocessing with pulse peak detection and inter-beat intervals
  • Pulse rate variability (PRV) computed from PPG preprocess runs
  • Blood pressure variability, dipping classification, and MAP statistics
  • Respiration rate, breath timing, and quality summaries
  • Respiratory sinus arrhythmia (RSA) cross-modal coupling from ECG and respiration
  • Baroreflex sensitivity from HRV and blood pressure sequence analysis
  • Subject import and cohort metadata linking across recordings
  • Cohort comparison with group means, standard deviations, and statistical tests
  • Batch HRV jobs across multiple datasets in one request
  • Research-only signal-derived risk stratification from cohort outcomes metadata
  • Interactive waveform explorer for QC and visual context
  • AI interpretation with descriptive and mechanistic modes citing recorded metrics
  • Methods report generation from experiment bundles
  • Async job panel with run status, parameters, and artifact links