EEG is one of the most common noninvasive methods for brain activity analysis. The technology has been used since the beginning of the 20th century. However, sensing technology has only recently developed to a point where a small cost-effective, wireless set of dry sensors can be mounted on the skull and produce a reliable reading.
The technological challenge lies in developing robust interpretation of brain EEG signals from one or few electrodes during routine brain activity without relying on any external stimuli.
Our experience in time series analysis enables us to apply advanced signal processing, machine learning and robust statistics to detect minute changes in the EEG signal, and obtain a rich set of psychophysical features from a single electrode. The same technology is also used in the analysis of seismic data for early detection of earthquakes in the analysis of financial time series data.
Applications include detection and monitoring of: Attention Deficit, Depression, Schizophrenia, Post Traumatic Syndrome and more.