Integrating Device and BCI2000 with a Cloud Interface

Abstract

Emerging brain-computer interface (BCI) systems may aim to develop invasive implantable systems to restore functionality in people with paralytic disabili ties and to deliver adaptive brain stimulation (ABS) to treat severe neurological disorders. A key characteristic of next-generation implantable systems will be their ca pability to record extended periods of local field poten tial (LFP) data. Timely transfer of the recorded LFPs to the clinical team is crucial for monitoring the im planted system’s reliability, safety and to dynamically enhance BCI and ABS applications in response to chang ing brain states. Our team is developing a comprehen sive therapeutic BCI ecosystem that combines the Cortec BrainInterchange hardware with the BCI2000 software environment. We have designed an architecture that seamlessly integrates recorded neural signals with de vice performance metrics, delivering these insights to the care team through a cloud-based interface. In or der for future centers-of-excellence to be able to deliver care with clinical BCIs, closed-loop algorithms will need be able to be dynamically updated without physically interacting with the patient for each adjustment. Our BCI ecosystem is currently being tested with canine sub jects, and this manuscript describes how device function (impedance measures) and brain data (LFP signals) were measured daily for an 8 week period following implanta tion through the cloud interface. Cloud based data syn chronization for implantable brain technologies is essen tial for dynamic re-calibration of reliable and safe BCI and ABS therapies in the clinical setting.

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Source: Mivalt, F., Van den Boom, M. A., Lampert, F., Kim, J., Lopez, A. D., Engelhardt, W., ... & Miller, K. J. INTEGRATING CORTEC BRAIN INTERCHANGE DEVICE AND BCI2000 WITH A CLOUD INTERFACE.