From Ludwig’s Kymograph to Modern Physiology
The word kymograph comes from the Greek kyma (“wave”) and graphō (“to write”). Invented by the physiologist Carl Ludwig in 1847, the kymograph transformed fleeting physiological signals into a permanent record, allowing clinicians and scientists to observe the body’s hidden dynamics for the first time.
At KymoMetrics, we carry that vision forward. Where Ludwig captured the waveform, we decode it. By combining physiology, advanced mathematics, artificial intelligence, and machine learning, we unlock the wealth of information contained within physiological data, transforming complex measurements into meaningful insights that inform and empower clinical decision making.
We believe that data alone has little value; its true power lies in the knowledge it creates and the decisions it enables. Our vision is to make physiological information more accessible, interpretable, and actionable, ensuring that every healthcare decision is guided by a deeper understanding of the patient’s unique physiology.
This philosophy underpins everything we develop
Our advanced hemodynamic assessment technologies analyse cardiovascular waveforms and apply sophisticated physiological models to derive clinically meaningful parameters that support the management of heart failure, cardiogenic shock, and mechanical circulatory support.
Our statistical analysis and data analytics platform — Inference-Stats — enables clinicians and researchers to transform complex datasets into robust evidence, making advanced analytical methods more accessible and intuitive.
For clinicians, our proprietary hemodynamic engine re-interprets existing clinical measurements to reveal insights and new perspectives in patients with circulatory shock.
Equally important is our commitment to communicating information effectively. We re-present complex NICOR data in clear, intuitive formats that support understanding by both clinicians and patients, fostering informed conversations and shared decision making.
Our mission
Our mission extends beyond measuring physiology or analysing data. Our aim is to transform data into information, information into understanding, and understanding into better decisions — to turn hidden data into understanding.