Mount Sinai team creates AI algorithm to detect sleep disorder

Rem Sleep Behavior Disorder, or RBD, is a condition that causes abnormal movements or briefed twitching DURING SLEEP, and Occasional Episodes of Dram Elementment.

The challenge

RBD affects more than one million Americans and is almost allays an early sign of parkinson’s or dementia, often preceding other symptoms by 10-15 years. That means it presents an unprecedented options for developing therapies Against Parkinson’s Disease or Dementia and Ultimately Identifying theoses who would be born.

However, rbd has been very different to dignose.

“A simple screening question on where or not people act out their dreams is poorly sensitive because many people with rbd rabd rarely have full-blown dress Small twitches that they or their partners are not aware of, “Explained Mount Sinai Clinician Dr. Emmanuel during.

DURING is Associate Professor of Neurology at the ICHN School of Medicine, Where he Sees Patients at the Mount Sinai Integrative Sleep Center and Specializes In movements, SLEEP NESOREPERS, As VOLLALSES Pulmonary Medicine and Critical Care.

Mount Sinai Health System is one of the largest academic medical systems in the new york metro area, with 48,000 Employees Working Across Eight Hospitals, More Than 400 Outpatint Practices, More OutPatient Practices, More Outs Clinical Labs, A School of Nursing, and a Leading School of Medicine and Graduate Education.

“A Simple Screening Question also is Poorly Specific Secause More Common Conditions – Like Sleep Apnea or a Form of Restless Legs Movements during Sleep -Can Cause Symptoms of Dream-Enactment Mimicking RBD, “during Continued.” RBD Questionnaires Lack Accuracy. “

The Gold Standard Test For Diagnising RBD is an in-Lab Sleep Test in a Sleep Center, also know as a polysomnogram, which measures muscle activity (Increased in rbd) Durring means Sleep Using MUSING MUSING MUSING MUSTEP Using Electromyography.

But rbd has been very different to diagnose using this in-Lab Sleep Test Security IT’s Very Difential to Interpret and Subject to Artifacts, to the point that thought SLEPETS CAN DISAGREE ONED Diagnosis.

“Notable, Although a video camera records any movements during sleep, the current standard for interpreting the test does not take any of that in the into account, no automated tool currently extra Data, “during noted.

“In Fact, In Most Sleep Centers, The Video Data is Discarded after the Sleep Test and Only the rest of the data collected – EEG, Breathing Signals, EKG, etc. – will be stored.”

Furthermore, He Said, Unless A Person Undergoing A Sleep Test is specifically suspended to have rbd by their sleep specialist – based on a history of dream enactment – the diagnosis being in 99% of cases, the test is conducted to evaluate for sleep apnea, which does not require assessing muscle activity, “He added.

This leads to missing “Incidental cases” of rbd, which occur in at least 1% of the adult population, according to study. To address this need, the Mount Sinai Research Team Developed A Method For Automating The Diagnosis of RBD by Analyzing Video Recordings of Sleep during in-Lab Sleep Tests.

Proposal

The team developed an algorithm to automatically the frequency and pattern of body movements detected DURING REM (RAPID EYE Movement) SLEEP and Determine Whiphera, BASED ONATEASEs, BASED ON MOVEDED RBD or not.

This has been done only by one group in Austria, but their study used a particular research-grade 3-d camera, which required being done added to the standard Sleep Test Hardware.

“No Study Before Ors Had Tested Video Data Routinely Collected With The 2-D-Infrared camera used in all clinical sleep labs around the world,” DURING SAID.

Meeting the challenge

“We assembled a large dataset – larger than done in the Prior Study – Comprising 81 Sleep Study Recordings of Patients with RBD (‘Cases’) and 91 with RBD (‘Controls’), Including 63 Whit A Range of Other Sleep Disorders and 28 Healthy Sleepers, “during explained.

An Optical Flow Computer Vision Algorithm Automatically Detected Movements during Rem Sleep, from which features of rate (frequency), ratio (proportion of time in rem sleep showing movements), magnitude and velocity of movements of MOLOCITY OF Immobility (a measure of the distribution pattern of movements in rem Sleep) Were Extracted, He Continued. From that five features, a machine-less classifier was trained to differential rbd from Other Sleep Conditions and Normal Sleep.

“We also weightened in testing the accusing classifier to detect rbd in patients who actually have rbd, but who, on the review of their slap test, was not reported to MOVE, BASED NOT MOVE, BASED NOT MOVE Review of Video Footages by a Sleep Expert, “DURING Recalled. “A Total of 11 Such Patients with RBD But No Visible-The-Human-Eye Movements was identified, and 71 patients with rbd with visible movements.”

Results

The mount sinai team found, as they expected, that people with rbd exhibited an increase number of movements in rem -sleep, particularly brief movements short Known as Myoclonus. AccuraCies for Detecting RBD Ranged from 84.9% (with only two features) to 87.2%.

Combining all five features but only analyzing short (Less than a 2-second Duration) movements achieved the highest accuracy at 91.9%.

Of the 11 patients with rbd without noticeable movements during the sleep test, Seven Were correctly identified, or detected as having rbd, based on the mount sinai algorithm.

Advice for other

“This is the first study showing that a simple algorithm analyzing video recording 91.9%, “during noted. “This work improves prior frameworks by using a 2-d camera that is routinely used in sleep laboratories, and improoving performance by adding on features.

“This Approach could be implemented in Clinical Sleep Laboratories to Facilitate and improve the diagnosis of rbd,” He Concluded. “Coupled with automated detection of rem sleep, it should also be tested in the home environment, using conventional infrared cameras to detect and monitor rbd.”

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Email him: bsiwicki@himss.org
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