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[1] Chaikovsky, I. Electrocardiogram scoring beyond the routine analysis: subtle changes matters. Expert review of medical devices, 17(5), 379-282. (2020).
[2] Chaikovsky, I. Syropyatov, I., Budnyk, M., Miasnikov, G., Kazmirchyk, A., & Dykhanovskiv, V. Investigation of the ECG Leads Sensitivity to Myocardial Ischemia by Means of Biophysical Model. IEEE 39th International Conference of Electronics and Nanotechnology (ELNANO)(pp.518-521). (2019).
Heart health automatic analysis
Algorithm designed for automatically analyzing heart health by using ECG and Holter and prevent dangerous heart events for elevated risk groups
CARDIOLYSE has developed an app that accurately determines the position of every cardiac and vital parameter on a scale from a personal baseline to pathology to prevent dangerous heart events for elevated risk groups. It uses an innovative machine-learning algorithm with up to 400 ECG parameters analyzed, allowing to have a reliable chronic cardiovascular disease control and management, together with a timely high-value and insightful medical care support.
Applications and diseases
This tool is useful for the early detection of elevated risk groups for dangerous heart events. It is a core component in the preventive healthcare, enabling non-clinical environment chronic disease complications management and patients’ quality of life improvement. It provides heart risk level, stress level and heart biological age metrics for better lifestyle adjustments.
The tool also allows to assess the visible impact of assigned therapy.
Detectable pathologies
Advantages
We summarize the patients’ results of the heart risk level, stamina, myocardium scores, stress level and heart biological age metrics for better lifestyle adjustments.
Comprehensive report for the doctor. With up to 400 ECG parameters analyzed and patient’s baseline-personalized. An alert is sent if a critical event risk is detected, being a convenient & Independent Health Self-Management.
References
[1] Chaikovsky, I. Electrocardiogram scoring beyond the routine analysis: subtle changes matters. Expert review of medical devices, 17(5), 379-282. (2020).
[2] Chaikovsky, I. Syropyatov, I., Budnyk, M., Miasnikov, G., Kazmirchyk, A., & Dykhanovskiv, V. Investigation of the ECG Leads Sensitivity to Myocardial Ischemia by Means of Biophysical Model. IEEE 39th International Conference of Electronics and Nanotechnology (ELNANO)(pp.518-521). (2019).
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