06 Mar EnsoData Raises $1.5M to Develop A.I.-powered Sleep Analysis Tools
Xconomy Wisconsin — An estimated 29.4 million adults in the U.S. suffer from sleep apnea, a major contributor to the “epidemic” of Americans not getting enough sleep, according to the Centers for Disease Control and Prevention.
Sleep apnea—interruptions in breathing that can be caused by obstructions such as the tonsils—is a progressive disorder that can be life-threatening. But before doctors choose a treatment for a patient who doesn’t sleep well, they must figure out whether the patient suffers from sleep apnea or a different disorder. The process of diagnosis, however, tends to be time- and labor-intensive, says Chris Fernandez, co-founder and CEO of EnsoData. The Madison, WI-based startup is developing software that uses machine learning algorithms to help clinicians score sleep data from studies performed in laboratories and at patients’ homes.
“Today, more than 85 percent of sleep clinics rely on a manual scoring process. It can take one hour or more” for a clinician (usually a polysomnographic technologist) to analyze eight or nine hours of sleep data this way, Fernandez says. By contrast, staff at the 50-plus sleep clinics currently using EnsoData’s software can diagnose sleep disorders and other conditions in as little as five minutes, he says.
Investors think EnsoData is on to something. The startup recently announced it raised a $1.5 million funding round, bringing its total seed-stage funding to more than $2 million, Fernandez says.
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