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We are engaged in development of neurotechnology for monitoring and modulating brain activity. There are several projects which are at different stages of completion.


The present approach for brain injury monitoring employs multiple invasive brain probes with each probe measuring a different quantity. We have developed the NeuroProbe Solution, a simple, portable, single source brain monitoring solution for the management of severe traumatic brain injury. This composite solution consists of the NeuroProbe, NeuroLink, and NeuroMonitor devices. We developed the NeuroProbe, a brain monitoring solution based on a single probe that integrates multiple physiologic sensors on a single intracranial probe. Additionally, we created a single interface device called the NeuroLink to acquire scalp EEG and digitize and transmit the multi-modal data acquired by the NeuroProbe and NeuroLink. A display unit called the NeuroMonitor is used to analyze and display the acquired multimodal data in a synchronized real-time manner. This innovative solution allows integration of the data from multiple physiological parameters through a standard tablet creating a simple single end-to-end solution from sensors to multimodal data display in an otherwise fragmented and complex domain thus broadening its application. The NeuroProbe Solution has many advantages over current solutions including improved safety, better data and a lower cost and is thus expected to lead to improved monitoring of patients with brain injury.


In ongoing work, we are building next generation sensors for neurochemistry. This includes electrical methods based on the use of silicon nanowires and optical methods. A novel combination of electrical with optical methods provides the state-of-the are technology to study brain biochemistry.

Brain Machine Interface

In collaboration with Drs Rajit Manohar (electrical engineering) and Abhishek Bhattacharjee (computer science) we are building a flexible ultralow-power processing architecture for implantable brain machine interfaces (BCIs). The focus of this work is on the development of the architecture, hardware solutions and an open language for real-time processing of multimodal brain signals from tens of sensors. Such a device would be amenable for monitoring different nodes of a brain network to monitor the rise of aberrance within the network, for example at seizure onset, and to control it.