Software that identifies sleep states from deep brain signals


A University of Colorado research team has developed software which can interpret brain patterns in order to determine whether the patient is awake or asleep that can be used with closed-loop DBS. The technology uses artificial neural networks to determine a patient’s sleep state. It was trained from PD patients with implanted DBS electrodes in the subthalamic nucleus. This software could change or shut off DBS implants in order to encourage a more restful, lengthy and restorative sleep and save battery power.


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For Information, Contact:
Maxine Faass
University of Colorado
Joel Zylberberg
Elijah Christensen
Aviva Abosch
John Thompson
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