Madison, Wisconsin-based EnsoData has received FDA clearance for its sleep analysis software called EnsoSleep, which uses machine learning to analyze sleep quality and aide in diagnosis of sleep or respiratory-related sleep disorders.
EnsoSleep, which began as a research effort between founders Chris Fernandez and Sam Rusk while they were students at the University of Wisconsin Madison, is intended to reduce the time it takes to analyze a sleep study by interfacing with polysomnography systems and intelligently automating, analyzing and generating a report of sleep data. The software integrates with existing lab workflows to detect sleep staging, sleep-disordered breathing, apneas, leg movements and more. EnsoSleep’s cloud-based system is also equipped to handle terabytes of incoming health data, and can export reports and summaries to electronic health records.
“FDA clearance of the EnsoSleep technology represents an historic milestone for our company and sleep clinicians who want to realize the huge time savings that are possible with automated analysis of sleep study results,” Fernandez said in a statement. “It took months of detailed testing and validation of our product by everyone on the EnsoData team, along with our early clinical partners.”
The software was validated in clinical studies using signals from standard PSG systems, and the algorithmically calculated scoring system is based on current American Academy of Sleep Medicine (AASM) guidelines.
EnsoData is a graduate of Y Combinator and Gener8or’s gBeta accelerators, and raised $550,000 last year to develop the software. Now that the company has secured FDA clearance, they plan to leverage algorithmic and big data technologies to help sleep centers and health systems operate sleep studies more efficiently at lower costs.
“We're confident this will be the first of many EnsoData products receiving FDA clearance to power company growth into the future,” Fernandez said.