Northeastern Professor Awarded $1.2 Million Grant

The funding supports the development of brain implants designed to monitor neurological disorders.

Updated on Oct. 6, 2026 in Stroke

A close-up of a small silicon sensor chip on a laboratory probe resting on a white workbench in a medical research lab. — Northeastern University professor Aatmesh Shrivastava received a $1.2 million grant from the NIH to develop machine learning chips for brain implants to monitor neurological disorders. AI Illustration. Upload story photo >

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The National Institute of Neurological Disorders and Stroke awarded a $1.2 million grant to Northeastern University professor Aatmesh Shrivastava. He is developing ultra-low-power machine learning chips for brain implants to track neurological conditions.

Why it matters

The device aims to provide continuous brain monitoring to identify patterns that brief standard tests often miss. This technology could improve diagnosis and management for patients with epilepsy, Alzheimer's, and ALS.

The grant supports a project focused on ultra-low-power machine learning, which aims to improve upon the 1924 electroencephalogram technology developed by Hans Berger. The new device tracks electrical signals from beneath the scalp in real time.

The players

Aatmesh Shrivastava

He is a professor at Northeastern University specializing in the development of low-power machine learning chips.

National Institute of Neurological Disorders and Stroke

This is a federal research organization that provides funding for neurological disorder management and brain health studies.

Hans Berger

He was a German psychiatrist who invented the electroencephalogram in 1924 to record electrical activity in the brain.

The details

The implant utilizes machine learning to analyze electrical signals from the brain as they are generated by nerve cells. By monitoring these signals continuously, the system seeks to detect specific patterns associated with various neurological disorders.

Hans Berger developed electroencephalogram technology in 1924.
The grant award was officially announced on October 6, 2026.

The Big Picture

This research follows the century-long evolution of brain monitoring since Hans Berger's 1924 development of the electroencephalogram. It represents a shift from temporary surface-level testing toward permanent, real-time diagnostic implants.

This development could eventually offer patients with conditions like epilepsy or Alzheimer's a more precise, continuous method for tracking their symptoms. It aims to eliminate the limitations of brief diagnostic sessions, potentially leading to more accurate long-term treatment plans.

The takeaway

Advancements in ultra-low-power computing are enabling a new generation of medical devices that can monitor health conditions internally. Patients may eventually see a shift from diagnostic procedures done in a clinic to real-time data collection occurring seamlessly during daily life.