Predicate Devices

Reference Devices

AI/ML (Artificial Intelligence / Machine Learning)

Yes
The device description explicitly states that the predefined sequences called Protocols include "artificial intelligence and rule-based models for the scoring of sleep studies".

Therapeutic

No
DeepRESP is an aid in the diagnosis of sleep disorders by analyzing sleep study recordings and providing data for assessment, but it does not directly treat or alleviate a medical condition.

Diagnostic

Yes

Explanation: The "Intended Use / Indications for Use" section explicitly states that DeepRESP is "an aid in the diagnosis of various sleep disorders." Additionally, the "Device Description" states it provides "data for the assessment and diagnosis of sleep-related disorders."

SaMD (Software as a Medical Device)

Yes

The device is explicitly described as a "cloud-based software as a medical device (SaMD)" and its components are listed as software elements (web API, protocols, result storage). There is no mention of accompanying hardware that is part of the device itself.

IVD (In Vitro Diagnostic)

Based on the provided information, DeepRESP is not an In Vitro Diagnostic (IVD) device.

Here's why:

IVD Definition: In Vitro Diagnostics are devices intended for use in the examination of specimens derived from the human body in order to provide information for diagnostic, monitoring, or compatibility purposes. This typically involves analyzing biological samples like blood, urine, tissue, etc.
DeepRESP's Function: DeepRESP analyzes physiological signals recorded during sleep studies (like EEG, respiratory signals, etc.). It does not analyze biological specimens.
Intended Use: The intended use clearly states that DeepRESP is an "aid in the diagnosis of various sleep disorders" by analyzing sleep study recordings. This is distinct from analyzing biological samples for diagnostic information.

Therefore, while DeepRESP is a medical device used in the diagnostic process, it falls under a different regulatory category than In Vitro Diagnostics.

PCCP (Predetermined Change Control Plan) Authorized

No
The letter does not state that the FDA has reviewed and approved or cleared a PCCP for this specific device.

Overview

Intended Use / Indications for Use

DeepRESP is an aid in the diagnosis of various sleep disorders where subjects are often evaluated during the initiation or follow-up of treatment of various sleep disorders. The recordings to be analyzed by DeepRESP can be performed in a hospital, patient home, or an ambulatory setting. It is indicated for use with adults (22 years and above) in a clinical environment by or on the order of a medical professional.

DeepRESP is intended to mark sleep study signals to aid in the identification of events and annotation of traces; automatically calculate measures obtained from recorded signals (e.g., magnitude, time, frequency, and statistical measures of marked events); infer sleep staging with arousals with EEG and in the absence of EEG. All output is subject to verification by a medical professional.

Product codes

OLZ

Device Description

DeepRESP is a cloud-based software as a medical device (SaMD), designed to perform analysis of sleep study recordings, with and without EEG signals, providing data for the assessment and diagnosis of sleep-related disorders. Its algorithmic framework provides the derivation of sleep staging including arousals, scoring of respiratory events and key parameters such as the Apnea-Hypopnea Index (AHI).

DeepRESP is hosted on a serverless stack. It consists of:

A web Application Programming Interface (API) intended to interface with a third-party ● client application, allowing medical professionals to access DeepRESP's analytical capabilities.
Predefined sequences called Protocols that run data analyses, including artificial . intelligence and rule-based models for the scoring of sleep studies, and a parameter calculation service.
A Result storage using an object storage service to temporarily store outputs from the . DeepRESP Protocols.

Mentions image processing

Not Found

Mentions AI, DNN, or ML

Mentions "artificial . intelligence".

Input Imaging Modality

Not Found

Anatomical Site

Not Found

Indicated Patient Age Range

Adults (22 years and above)

Intended User / Care Setting

By or on the order of a medical professional in a clinical environment (can be hospital, patient home, or ambulatory setting). Used in Physician office.

Description of the training set, sample size, data source, and annotation protocol

Not Found. The document only describes the validation/test set.

Description of the test set, sample size, data source, and annotation protocol

The clinical performance of DeepRESP was validated by a retrospective study. It used manually scored sleep recordings, originating from sleep clinics in the United States, performed as part of routine clinical work matching indicated use of the study device and patient population.

Two separate studies were conducted:

Type I-II recordings (with EEG): A total of 2,224 Type I recordings were used. The recording collection consisted of 46% Females, had individuals in all age groups (22-35, 36-45, 46-55, 56-65, 65+), and all BMI groups (

Regulation Number and Section

§ 882.1400 Electroencephalograph.

(a)
Identification. An electroencephalograph is a device used to measure and record the electrical activity of the patient's brain obtained by placing two or more electrodes on the head.(b)
Classification. Class II (performance standards).

Summary

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March 14, 2025

Image /page/0/Picture/1 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, with the letters "FDA" in a blue square. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.

Nox Medical ehf % Hrishikesh Gadagkar Senior Principal Ram+ 2790 Mosside Blvd #800 Monroeville, Pennsylvania 15146

Re: K241960

Trade/Device Name: DeepRESP Regulation Number: 21 CFR 882.1400 Regulation Name: Electroencephalograph Regulatory Class: Class II Product Code: OLZ Dated: July 3, 2024 Received: July 3, 2024

Dear Hrishikesh Gadagkar:

We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food. Drug. and Cosmetic Act (that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.

If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.

Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device"

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(https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).

Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30. Design controls; 21 CFR 820.90. Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the OS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).

Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.

All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rue"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advicecomprehensive-regulatory-assistance/unique-device-identification-system-udi-system.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.

For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

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Sincerely,

Patrick Antkowiak -S

for Jay Gupta Assistant Director DHT5A: Division of Neurosurgical, Neurointerventional, and Neurodiagnostic Devices OHT5: Office of Neurological and Physical Medicine Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

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Indications for Use

510(k) Number (if known) K241960

Device Name DeepRESP

Indications for Use (Describe)

DeepRESP is an aid in the diagnosis of various sleep disorders where subjects are often evaluated during the initiation or follow-up of treatment of various sleep disorders. The recordings to be analyzed by DeepRESP can be performed in a hospital, patient home, or an ambulatory setting. It is indicated for use with adults (22 years and above) in a clinical environment by or on the order of a medical professional.

DeepRESP is intended to mark sleep study signals to aid in the identification of events and annotation of traces; automatically calculate measures obtained from recorded signals (e.g., magnitude, time, frequency, and statistical measures of marked events); infer sleep staging with arousals with EEG and in the absence of EEG. All output is subject to verification by a medical professional.

Type of Use (Select one or both, as applicable)
-------------------------------------------------

X Prescription Use (Part 21 CFR 801 Subpart D)

Over-The-Counter Use (21 CFR 801 Subpart C)

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510(k) Summary DeepRESP – 510(k) Traditional

DATE PREPARED

March 13, 2025

MANUFACTURER AND 510(k) OWNER

Nox Medical ehf Katrinartuni 2, IS - 105 Reykjavik, Iceland Telephone: +354 570 7170 Official Contact: Kolbrun E Ottosdottir, Chief Compliance Officer

REPRESENTATIVE/CONSULTANT

Hrishikesh Gadagkar, Sr. Principal RQM+ 2790 Mosside Blvd #800, Monroeville, PA Telephone: +1 (410) 245-0501 Email: hgadagkar@rqmplus.com

DEVICE INFORMATION

Proprietary Name/Trade Name:	DeepRESP
Common Name:	Electroencephalograph, Automatic Event Detection Software
for Polysomnograph with Electroencephalograph
Regulation Number:	882.1400
Class:	II
Product Code:	OLZ
Premarket Review:	Division of Neurosurgical, Neurointerventional and Neurodiagnostic
Devices (DHT5A), Office of Neurological and Physical Medicine
Devices (OHT5)
Review Panel:	Neurology

PREDICATE DEVICE IDENTIFICATION

The DeepRESP is substantially equivalent to the following predicate:

| 510(k)
Number | Predicate Device Name / Manufacturer | Primary
Predicate | Additional
Predicate |
|------------------|--------------------------------------|----------------------|-------------------------|
| K192469 | Nox Sleep System / Nox Medical | x | |
| K202142 | Sleepware G3 / Respironics Inc | | x |

DEVICE DESCRIPTION

DeepRESP is a cloud-based software as a medical device (SaMD), designed to perform analysis of sleep study recordings, with and without EEG signals, providing data for the assessment and diagnosis of sleep-related disorders. Its algorithmic framework provides the derivation of sleep staging including arousals, scoring of respiratory events and key parameters such as the Apnea-Hypopnea Index (AHI).

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Image /page/5/Picture/0 description: The image shows the text "nox medical" in a sans-serif font. The text is dark blue and appears to be a logo or brand name. The words are lowercase and evenly spaced.

510(k) Summarv DeepRESP – 510(k) Traditional

DeepRESP is hosted on a serverless stack. It consists of:

A web Application Programming Interface (API) intended to interface with a third-party ● client application, allowing medical professionals to access DeepRESP's analytical capabilities.
Predefined sequences called Protocols that run data analyses, including artificial . intelligence and rule-based models for the scoring of sleep studies, and a parameter calculation service.
A Result storage using an object storage service to temporarily store outputs from the . DeepRESP Protocols.

Image /page/5/Figure/6 description: The image is a dataflow diagram titled "Figure 1 - DeepRESP dataflow". The diagram shows the flow of data between different components, including the EMR Repository, Client application, DeepRESP API, DeepRESP Protocols, and DeepRESP Result storage. The EMR Repository and Client application are connected by a two-way arrow, indicating that data can flow in both directions. The Client application is connected to the DeepRESP API, which is connected to the DeepRESP Protocols, which is connected to the DeepRESP Result storage.

INDICATIONS FOR USE DeepRESP is an aid in the diagnosis of various sleep disorders where subjects are often evaluated during the initiation or follow-up of treatment of various sleep disorders. The recordings to be analyzed by DeepRESP can be performed in a hospital, patient home, or an ambulatory setting. It is indicated for use with adults (22 years and above) in a clinical environment by or on the order of a medical professional.

DeepRESP is intended to mark sleep study signals to aid in the identification of events and annotation of traces; automatically calculate measures obtained from recorded signals (e.g., magnitude, time, frequency, and statistical measures of marked events); infer sleep staging with arousals with EEG and in the absence of EEG. All output is subject to verification by a medical professional.

COMPARISON OF TECHNOLOGICAL CHARACTERISTICS

Nox Medical believes that the DeepRESP is substantially equivalent to the primary predicate device based on the information summarized here:

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510(k) Summary DeepRESP – 510(k) Traditional

Trade/Device Name	Subject Device:	Primary Predicate Device:	Additional Predicate Device:
	DeepRESP	Nox Sleep System	Sleepware G3
Manufacturer	Nox Medical	Nox Medical	Respironics, Inc.
510(k) Number	K241960	K192469	K202142
Regulation Number	21 CFR 882.1400	21 CFR 882.1400	21 CFR 882.1400
Regulation Name	Electroencephalograph	Electroencephalograph	Electroencephalograph
Regulatory Class	Class II	Class II	Class II
Product Code(s)	OLZ	Primary: OLZ
Subsequent: KZM	OLZ
Intended Use	DeepRESP is a cloud-based artificial intelligence-
enabled software application used for analysis
(automatic scoring), retrieval, and summarization
of data recorded with sleep monitoring devices.
The device uses an algorithm to categorize sleep-
related events that help aid in the diagnosis of
sleep-related disorders. The results of the analyzed
data are then transferred to another software for
manual scoring, display and reporting	The Nox Sleep System is used as an aid in the
diagnosis of different sleep disorders and for the
assessment of sleep.
The Nox Sleep System is used to measure, record,
display, organize, analyze, summarize, and retrieve
physiological parameters during sleep and wake.The
Nox Sleep System allows the user to decide on the
complexity of the study by varying the number and
types of physiological signals measured.
The Nox Sleep System allows for generation of
user/pre-defined reports based on subject´s data.
The user of the Nox Sleep System are medical
professionals who have received training in the areas
of hospital/clinical procedures, physiological
monitoring of human subjects, or sleep disorder
investigation.
The intended environments are hospitals, institutions,
sleep centers, sleep clinics, or other test
environments, including the patient's home.	Sleepware G3 is a software application used for
analysis (automatic and manual scoring), display,
retrieval, summarization, report generation, and
networking of data received from monitoring devices
used to categorize sleep related events that help aid
in the diagnosis of sleep-related disorders.
The optional Somnolyzer software application is
intended to mark sleep study signals in order to aid
in the identification of events and annotation of
traces; automatically calculate measures obtained
from recorded signals (e.g., magnitude, time,
frequency, and statistical measures of marked
events); and infer sleep staging in the absence of
EEG. All output subject to verification by a qualified
user.
Indications for Use	DeepRESP is an aid in the diagnosis of various
sleep disorders where subjects are often evaluated
during the initiation or follow-up of treatment of
various sleep disorders. The recordings to be	The Nox Sleep System is used as an aid in the
diagnosis of different sleep disorders and for the
assessment of sleep.
The Nox Sleep System is used to measure, record,	Sleepware G3 is a software application used for
analysis (automatic and manual scoring), display,
retrieval, summarization, report generation, and
networking of data received from monitoring devices
	analyzed by DeepRESP can be performed in a
hospital, patient home, or an ambulatory
setting. It is indicated for use with adults (22
years and above) in a clinical environment by or on
the order of a medical professional.

DeepRESP is intended to mark sleep study signals
to aid in the identification of events and annotation
of traces; automatically calculate measures
obtained from recorded signals (e.g., magnitude,
time, frequency, and statistical measures of
marked events); infer sleep staging with arousals
with EEG and in the absence of EEG. All output is
subject to verification by a medical professional. | display, organize, analyze, summarize, and retrieve
physiological parameters during sleep and wake.

The Nox Sleep System allows the user to decide on
the complexity of the study by varying the number
and types of physiological signals measured.

The Nox Sleep System allows for generation of
user/pre-defined reports based on subject 's data.

The user of the Nox Sleep System are medical
professionals who have received training in the areas
of hospital/clinical procedures, physiological
monitoring of human subjects, or sleep disorder
investigation.

The intended environments are hospitals, institutions,
sleep centers, sleep clinics, or other test
environments, including the patient's home. | used to categorize sleep related events that help aid
in the diagnosis of sleep-related disorders. It is
indicated for use with adults (18 and older) and
infant patients (one year old or less) in a clinical
environment by or on the order of a physician.

Page 3 of 10

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510(k) Summarv DeepRESP – 510(k) Traditional

SUMMARY OF NON-CLINICAL TESTING

Software verification and validation testing were performed per IEC 62304:2006/A1:2015 Medical device software – Software life cycle processes, IEC 82304-1:2017 Health Software – general requirements for product safety and the FDA quidance General Principles of Software Validation to demonstrate safety and performance based on current industry standards and that we met the intended use and user needs. Relative documentation was prepared as recommended in FDA's Guidance for Industry and FDA Staff, Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices.

SUMMARY OF CLINICAL TESTING

The clinical performance of DeepRESP was validated by a retrospective study. It used manually scored sleep recordings, originating from sleep clinics in the United States, performed as part of routine clinical work matching indicated use of the study device and patient population.

The performance of DeepRESP with regards to scoring of sleep recordings with electroencephalography (EEG) (i.e. Type I and II), and sleep recordings without EEG (i.e. Type III) was validated. Two separate studies were conducted, one to validate DeepRESP with scoring of Type I-II recordings and a second one with scoring of Type III recordings. The studies were done by evaluating the agreement in scoring and clinical indices resulting from the automatic scoring by DeepRESP compared to manual scoring. The performance of DeepRESP was compared to the agreement of the automatic scoring of the predicate device to manual scoring. The same collection of sleep recordings and same manual scoring were used when comparing the automatic scoring of DeepRESP and the predicate device. The study method was a retrospective data study comparing paired differences.

In both studies DeepRESPs performance with regards to sleep state estimation and respiratory event scoring was validated against the Nox Sleep System (K192469). For evaluation for performance of arousal scoring, Sleepware G3 (K202142) was used as a comparator.

For validating scoring performance for Type I recordings, a total of 2,224 Type I recordings were used. For validating scoring performance for Type III recordings, a total of 3,488 sleep recordings were used, including 2,213 Type I recordings and 1,275 Type II recordings. The Type I and II recordings were processed as Type III recordings by utilizing only the subset of signals from them that are common to Type III recordings.

The recording collection used for validation of Type I scoring consisted of 46% Females, had individuals in all age groups (22-35, 36-45, 46-55, 56-65, 65+), and all BMI groups (