TU / e is working on chip for EEG wearable which patients can use at home

Mar

1

2016

Researchers at Eindhoven University of Technology are working on an EEG-efficient chip, which epilepsie- and Parkinson’s patients can use at home to record brain activity. The chip must be applied in a portable system that can analyze EEG signals.

A document of the researchers show that the plan to use the ARM Cortex-M0 processor design. The Cortex M0 will be integrated as a general-purpose CPU in a so-called Brainwave processor. The M0 is the smallest CPU design from ARM and must be adapted to the EEG system. The processor is a 28nm FD-SOI produced CMOS process from STMicroelectronics. The resulting chip would be four times more energy efficient than current EEG monitoring systems according to the researchers.

The aim of the project called Brainwave, is to develop a portable system that allows patients to make continuous EEG scans and so seven days a week, 24 hours outside the hospital can record brain activity. Acute symptoms such as seizures, would thus be faster, and intervention may come into play, for example medication.

Also, the system would be able to recognize freezing episodes associated with Parkinson’s patients. Here, patients feel as if their feet are addressing the ground and no step can take more. This can result in a trap. The Brainwave could raise the alarm in the event of such an episode.

Recognizing patterns in EEG signals that indicate for example, a seizure, according to the researchers involved. Specialized personnel must often look at the long-term EEG, which makes the study duration and patients need before traveling to a hospital or specialized center. Cee-chip development, the researchers could analyze the signals themselves and therefore can be used for long-term EEG monitoring in intensive care units of hospitals.

The proposed Brainwave device must have an accuracy of over ninety percent with an error deviation of less than one percent in defining seizures and freezing episodes. The research is funded by Technology Foundation STW.

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