Multimodal cardiovascular and physiological signal research
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
Guided workflows map common questions to data requirements, analysis steps, and documentation — pick the scenario closest to your study.
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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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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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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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
Everything available in the Cardiology workspace today — pipelines, explorers, exports, and provenance.