Vaclav Kremen, Ph.D., M.S., has a background in electrical engineering, biomedical engineering, machine learning and artificial intelligence. During his scientific and engineering career, he has developed tools and methods for data mining and signal analysis in the domain of multiscale, multimodal physiological data such as polysomnography, multilead electrocardiogram (ECG) and neurophysiology.
The methods and tools developed by Dr. Kremen enable scientific discoveries in both clinical and theoretical fields of the natural sciences. Dr. Kremen has written tools for mining of big data in areas of neuroscience, neurology and cardiology. Dr. Kremen's recent research is focused in neurology, neuroscience, deep brain stimulation and closed-loop implantable systems to advance care of patients with neurological disorders such as epilepsy.
- Dr. Kremen's early research focused on automated analysis of multiscale intracardiac electrophysiology to differentiate fractionated atrial electrograms and substrate of atrial fibrillation and to navigate ablation of atrial fibrillation.
- Dr. Kremen developed methods for advanced analysis of multilead ECG and tools for analysis of the cardiovascular system. He also developed a device for noninvasive assessment of cardiovascular parameters.
- Dr. Kremen's latest research focuses on several neuroscience projects to understand the basic mechanisms of seizures and human cognition and to translate that understanding into novel therapies for the treatment of epilepsy and impaired memory.
- Dr. Kremen has been developing fully automated systems for an automated behavioral stage classification using intracranial electrophysiology data to assess and guide therapies of patients with neurological disorders.
- In collaboration with Gregory A. Worrell, M.D., Ph.D., Dr. Kremen is working on the development and application of a next generation epilepsy device. This neural stimulator provides automated closed-loop electrical stimulation to treat epilepsy.
Significance to patient care
Dr. Kremen has been developing and improving tools that advance the care of patients with cardiac and neurological diseases. He has been developing a next-generation epilepsy management system that integrates local hand-held and cloud-computing resources and that is wirelessly coupled to an implanted device with embedded payloads (sensors, intracranial EEG telemetry, electrical stimulation, classifiers and control policy implementation).
The system can provide a seamless interface between patients and physicians, and real-time intracranial ECG can be used to classify brain state (wake, sleep, pre-seizure and seizure), implement control policies for electrical stimulation and track patient health. This system creates a flexible platform and enables tracking and management of epileptic neural networks to help patients better manage the epilepsy.
- Guest editor, Sensors, 2019-present
- Awarded grant postdoctoral research project GACR #P103/11/P106, 'Integration of Digital Signal Processing and Artificial Intelligence Methods for Intracardiac Signal Complexity Evaluation,' Czech Science Foundation, Czech Republic, 2011-2013
- Member: Czech Society for Biomedical Engineering and Medical Informatics; Czech Medical Association of J.E. Purkyne; International Society for Telemedicine and eHealth; International Federation for Medical and Biological Engineering; International Medical Informatics Association; and European Federation for Medical Informatics
- Reviewer: IEEE Transactions on Biomedical Engineering; Computer Methods and Programs in Biomedicine; Computers in Biology and Medicine; Physiological Measurement; Biomedical Engineering/Biomediczinische Technik; eNeuro, Epilepsia Open; Journal of Neural Engineering; and Journal of Electrocardiology