Corundum Neuroscience has awarded a research grant to Tel Aviv University in Israel to develop a machine learning (ML)-based method to non-invasively detect abnormal brain activity deep in the brain during sleep.
The study uses machine learning and AI to classify subtle signals detected when paroxysmal discharges occur using high-density electroencephalography (hd-EEG) sleep data collected from older adults with cognitive impairment and dementia.
The aim of this research is to generate disease-specific biomarkers for various neurodegenerative diseases.
“Currently, there are no objective tools with the sensitivity required to non-invasively detect and quantify the features of brain activity that we are investigating,” said lead researcher Professor Neal.
“Our goal is to combine research into brain activity during sleep with machine learning to lay the foundation for measuring abnormal brain activity during sleep in dementia patients, and ultimately to validate biomarkers for various neurological diseases.”
In this study, we will test our detection tool on HD-EEG sleep data from early and late stages of dementia and compare it to healthy controls. Furthermore, the project will also investigate to what extent it is possible to identify narcolepsy discharges at different stages of neurodegeneration.
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In the short term, Corundum hopes that this research will help identify early-stage dementia patients who could benefit from anti-epileptic treatment. In the long term, this research paves the way for improved diagnosis, prognosis, drug titration, and risk stratification of epilepsy, dementia, and various neurological and psychiatric diseases.
Research into sleep diagnosis and monitoring has increased in recent years. In January, Netherlands-based Onera Health raised €30 million ($32.7 million) in Series C funding to accelerate approval of its second-generation at-home sleep disorder diagnosis and polysomnography (PSG) system in Europe and the US.
In October 2023, Sleepiz received Class II 510(k) clearance from the U.S. Food and Drug Administration (FDA) for its Sleepiz One+ bedside device, which uses radar technology to non-contact monitor a patient's breathing patterns, respiration rate and heart rate while they sleep.
