Nathan Intrator, CEO, Neurosteer.
Professor (on leave) of Computer Science and Neuroscience at Tel Aviv University, Israel.
An international scholar in neural computation, machine learning and pattern recognition with more than 120 scientific publications.
He studies the signal processing capabilities of sonar animals and develops signal processing methods for BCI, most notably for extensive information extraction from 2 EEG electrodes. Intrator invented a novel emotional and cognitive activity interpretation system, with previously unattainable detail, enabling disruptive brain monitoring and neurofeedback for IoT.
His applied research led to several patents and applications and the founding of three companies in biomedical signal analysis, sonar imagery and homeland security.
He is the past CEO of Karmel Sonix, a publicly traded medical device company, where he led the company to obtaining FDA and CE clearance for an asthma monitoring medical device.
A miniature neurological bed-side monitor
Lack of real-time brain monitoring affects assessment quality and prevents personalized and timely treatment of neurological disorders. Combining advanced signal processing and machine learning, Neurosteer captures brain activity with a minimal sensor, interprets brain dynamics, and detects in real time various neurological states including emotional and cognitive load, sleep stages and abnormal (epileptic) activity. Clinical decision-making in a wide range of neurological disorders can be dramatically improved.
EVEN MORE SEMINARS
James Barber The Royal London Hospital
Post-Traumatic Disorders of Consciousness: Prognostication, Communication & Reconnection
Dr Derek Jones Anatomical Concepts (UK) Ltd & Fixxl Ltd
Embodied Cognition – A role in rehabilitation
Edoardo Sabatini and Edoardo Dal Pra EB Neuro
Multimedia Authoring & Management using your Eyes & Mind
Tina Soulis Neuroscience Trials Australia
Strategies in CNS Drug and Device Development: The Australian Advantage
Dr Jeremy Isaacs St George's University Hospitals NHS FT
Diagnosis of young onset dementia