Onera SleepMap (SLEEPMAP)

K253668

Onera B.V. · cleared 2026-03-08 · product code OLZ · Neurology

FDA 510(k) summary for Onera SleepMap (SLEEPMAP) (K253668)

Constat organizes this clearance into predicate context, validation evidence, reported performance, postmarket signals, and reimbursement links. Each extracted claim stays tied to the public FDA source; missing fields remain explicitly unstated.

Validation studies
2
Cited predicates
2
Performance observations
2
Product code
OLZ
Official FDA 510(k) database record ↗FDA 510(k) source PDF ↗

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“Onera SleepMap is a software-only medical device that analyses previously recorded physiological signals obtained during sleep through a polysomnography sleep test with the Onera STS I device.”
Algorithmdeep learning model (AI-model), Convolutional Neural Network (AI-model), rule-based algorithm
source quote (p.6)
“The Onera SleepMap contains the following algorithms: - Sleep staging algorithm, a deep learning model (Al-model) which classifies sleep stages, based on EEG, EOG and EMG inputs. - Arousals algorithm, a Convolutional Neural Network (Al-model) which predicts arousals, based on sleep stages, EEG, EOG, EMG, ECG and nasal pressure inputs. - Desaturation algorithm, a rule-based algorithm which detects events of minimum 3% or 4% oxygenation drop based on sleep stages and SpO2 signal inputs. - Apnea (obstructive) detection, a rule-based algorithm which detects "90% nasal pressure drops, based on sleep stages and nasal pressure signal inputs. - Hypopneas (obstructive) detection, a rule-based algorithm which detects ">=30% nasal pressure drops based on sleep stages, nasal pressure signal, arousal events, and desaturation event inputs. - Leg Movement algorithm, a rule-based algorithm which detects (repetitive) EMG amplitude increasements, based on sleep stages, EMG signal and respiratory event inputs. - Artifact algorithms, rule-based algorithms which detect artifacts, based on SpO2, EEG, EOG, EMG and heart rate inputs.”
Adaptive (vs locked)No
PCCPNo
Cybersecurity addressedYes
source quote (p.13)
“Authentication controls, authorization controls, cryptographic controls, access controls, integrity controls, intrusion & availability monitoring controls, and database controls.”

Validation studies (2)

Retrospective clinical

n=98 patients · 2 site(s)

endpoints: Positive Agreement (PA); Negative Agreement (NA); Overall Agreement (OA); False Discovery Rate (FDR)

standards: AASM scoring guidelines

Retrospective clinical

n=215 patients · 2 site(s)

endpoints: Absolute error of HR

Reported performance (2 observations)

sensitivity78.9CI 76.8%, 81.0%
source quote (p.15)
“Total 78.9% (76.8%, 81.0%)”
specificity94.7CI 94.2%, 95.2%
source quote (p.15)
“Total 94.7% (94.2%, 95.2%)”

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

0
recalls in product code, 24mo
3
MAUDE reports in code, 12mo
+80%
vs code's own 3-yr baseline
0
drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-08-26.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Neurology panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Related FDA clearances

More AI/ML devices under product code OLZ

These are recent clearances in the same FDA product-code category. Shared classification does not by itself make a device an appropriate predicate.

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Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K253668