Predicate Devices

Reference Devices

AI/ML (Artificial Intelligence / Machine Learning)

Unknown
The document describes "Automated algorithms" and "automated recognition" of events, which could potentially be implemented using AI/ML, but it does not explicitly state that AI or ML is used. The description of the performance studies and metrics are consistent with evaluating algorithmic performance, but don't specifically point to AI/ML.

Therapeutic

No

Explanation: The device is intended for diagnostic evaluation and analysis of sleep study results, not for providing therapy or treatment.

Diagnostic

Yes

Explanation: The "Intended Use / Indications for Use" section explicitly states that "EnsoSleep is intended for use in the diagnostic evaluation by a physician to assess sleep quality and as an aid for physicians in the diagnosis of sleep disorders and respiratory related sleep disorders." This directly indicates its role as a diagnostic device. While the device description clarifies that it "does not interpret the results, nor does it suggest a diagnosis" and "marks events of interest for review by a physician who is responsible for diagnoses," its utility in aiding actual diagnosis by a physician qualifies it as a diagnostic device.

SaMD (Software as a Medical Device)

Yes

The device description explicitly states "EnsoSleep is a software-only medical device". The components described are all software platforms and interfaces.

IVD (In Vitro Diagnostic)

Based on the provided information, this device is likely an IVD (In Vitro Diagnostic).

Here's why:

Intended Use: The intended use explicitly states that EnsoSleep is for "diagnostic evaluation by a physician to assess sleep quality and as an aid for physicians in the diagnosis of sleep disorders and respiratory related sleep disorders". While it's a software-only device, its purpose is to analyze physiological signals from the patient to provide information that aids in diagnosis.
Analysis of Physiological Signals: The device description and intended use clearly state that EnsoSleep analyzes "previously recorded physiological signals obtained during sleep". These signals are collected from the patient's body (e.g., during a PSG or Home Sleep Test).
Aid in Diagnosis: The core function is to analyze these signals and provide automated scoring and event detection to assist a physician in making a diagnosis. This aligns with the definition of an IVD, which is used to examine specimens derived from the human body to provide information for diagnostic purposes.
Comparison to Predicate/Reference Devices: The performance studies compare EnsoSleep to predicate and reference devices that are also involved in the analysis of physiological data for sleep disorder diagnosis (K162627 EnsoSleep and K112102 Michele Sleep Scoring). These types of devices are typically regulated as IVDs.

While the device is software-only and doesn't directly interact with a biological specimen in the traditional sense (like a blood sample), the analysis of physiological signals derived from the human body for diagnostic purposes falls under the scope of IVD regulation in many jurisdictions. The key is that the information provided by the device is used to aid in the diagnosis of a medical condition.

Therefore, based on the intended use and the nature of the data it analyzes, EnsoSleep fits the criteria of an In Vitro Diagnostic device.

PCCP (Predetermined Change Control Plan) Authorized

N/A

Overview

Intended Use / Indications for Use

EnsoSleep is intended for use in the diagnostic evaluation by a physician to assess sleep quality and as an aid for physicians in the diagnosis of sleep disorders and respiratory related sleep disorders in pediatric as follows:

· Pediatric patients 13 years and older with polysomnography (PSG) tests obtained in a Hospital or Sleep Clinic
· Adult patients with PSGs obtained in a Hospital or Sleep Clinic
· Adult patients with Home Sleep Tests

EnsoSleep is a software-only medical device to be used under the supervision of a clinician to analyze physiological signals and automatically score sleep study results, including the staging of arousals, leg movements, and sleep disordered breathing events including obstructive apneas (OSA), central sleep apneas (CSA), and hypopneas.

All automatically scored events and physiological signals which are retrieved, analyzed, displayed, and summarized are subject to verification by a qualified clinician. Central sleep apneas (CSA) should be manually reviewed and modified as appropriate by a clinician.

All events can be manually marked or edited within records during review.

Photoplethysmography (PPG) total sleep time is not intended for use when electroencephalograph (EEG) data is recorded. PPG total sleep time is not intended to be used as the sole or primary basis for diagnosing any sleep related breathing disorder, prescribing treatment, or determining whether additional diagnostic assessment is warranted.

Product codes

OLZ

Device Description

EnsoSleep is a software-only medical device that analyzes previously recorded physiological signals obtained during sleep. Users of EnsoSleep are consistent with the roles required to run a sleep clinic: sleep physicians, sleep technicians, clinic operations managers, and IT administrators. EnsoSleep can analyze at-home and in-lab sleep studies for both adult and pediatric patients who are at least 13 years old. Automated algorithms are applied to the raw signals in order to derive additional signals and interpret the raw and derived signal information. The software automates recognition of the following: respiratory events, sleep staging events, arousal events, movement events, cardiac events, derived signals, and calculated indices. EnsoSleep does not interpret the results, nor does it suggest a diagnosis. The device only marks events of interest for review by a physician who is responsible for diagnoses. The device does not analyze data that are different from those analyzed by human scorers.

The signals and automated analyses can be visually inspected and edited prior to the results being integrated into a sleep study report.

The software consists of 4 major components:

The Application Platform runs on local clinic workstations and manages the detection, ● upload, and download of study records and scoring to and from the Storage Platform
The Processing Platform accepts raw physiological signals as inputs in order to recognize events, derive signals, and calculate indices
. The Storage Platform facilitates file and database storage in the EnsoSleep cloud through an API
The Dashboard is a web-based user interface to support configuration, clinic management, and sleep study scoring

Input signals used to derive outputs include:

Electroencephalogram (EEG) ●
Electrocardiogram (ECG) ●
Electro-oculogram (EOG) ●
Electromyogram (EMG) ●
Actigraphy
Airflow
Oximetry
Saturation of Peripheral Oxygen (SpO2)
Respiratory Inductance Plethysmogram (RIP)
Polyvinylidene Flouride (PVDF)
Photoplethysmogram (PPG)
Pulse Rate
Snoring Microphone ●
. Esophogeal Manometry

Outputs that are displayed to users include:

Respiratory Events
- o Obstructive Sleep Apneas (OSA)
Central Sleep Apneas (CSA) o
Mixed Sleep Apneas (MSA) O
Hypopneas O
Cheyne-Stokes Respiration O
Periodic Breathing O
Sleep Staging Events ●
- Stage Wake O
- Stage N1 O
- Stage N2 O
- Stage N3 O
- O Stage REM (rapid eye movement)
Arousal Events ●
- O Arousals
Movement Events ●
- o Leg Movements (LM)
- o Periodic Leg Movement Series (PLMS)
Cardiac Events* ●
- o Bradycardia
- o Tachycardia
Respiratory Rate Events
- o Respiratory Rate
Sleep-Wake Events ●
- o Wake
- o Sleep
Apnea-Hypopnea Index (AHI) ●
Sleep Architecture ●
Sleep Efficiency (SE) ●
Arousal Index (ArI) ●
Sleep Latency (SL) .
REM Latency (RL)
Total Sleep Time (TST)
Periodic Leg Movements (PLMS) Index ●

Capnogram data are not displayed to users.

The primary differences between the predicate device and subject device include:

-Target patient population: pediatric patients are included

-Automated scoring of Cheyne-Stokes and Periodic Breathing respiration events and Total Sleep Time

-Browser-based scoring interface to view and edit sleep studies

-Home-sleep studies are supported

The tachycardia and bradycardia outputs are not for use for cardiovascular monitoring or diagnosis, nor does the device detect arrhythmias.

Mentions image processing

Not Found

Mentions AI, DNN, or ML

Not Found

Input Imaging Modality

Not Found

Anatomical Site

Not Found

Indicated Patient Age Range

Pediatric patients 13 years and older
Adult patients

Intended User / Care Setting

Physician / Hospital or Sleep Clinic

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

Not Found

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

To construct the final study sample from the archived collection population, a randomized sampling with proportionate allocation across each sleep apnea disease severity quantile (normative, mild, moderate, and severe sleep apnea) was used to construct a valid Adult Sample of N=100 adult subjects (AHI mean: 22.4 [95% Cl: 18.6%, 26.1%], std: 18.8, median: 17.2, min: 0, max: 109.2, rule: 1.a.) and Pediatric Sample of N=47 pediatric subjects (AHI mean: 11.4 [95% CI: 7.6%, 15.6%], std: 13.6, median: 7.0, min: 0, max: 60.3, rule: 1.a.) from the first laboratory N=1984 archived collection of retrospective diagnostic clinical PSG data, and a valid Respiratory Rate Sample of N=100 adult subjects (AHI mean: 13.2 [95% Cl: 9.7%, 16.5%], std: 17.1, median: 6.6, min: 0, max: 82.9, rule: 1.b.) from the second laboratory N=1079 archived collection of retrospective diagnostic clinical PSG data.

Following the finalization of each N=100 subject Adult, N=47 Pediatric, and N=100 Respiratory Rate study sample respectively, six (6) clinical testing laboratories were evaluated for independent manual scoring, three (3) laboratories were selected, and the clinical test setting was established for constructing a valid 2/3 Majority Scoring consensus reference, using N=9 total registered scoring technologists (RPSGTs) with 5 to 20+ years clinical experience by verification of meeting all defined study scoring-acquisition, scoring-blind, and rater-quality certification controls. Manual scoring for sleep stage, hypopnea events, obstructive sleep apnea (OSA) events, central sleep apnea (CSA) events, arousal events, limb movement events, respiratory effort related arousal (RERA) events, cheyne-stokes (CS) respiration events, and periodic breathing (PB) events were prospectively collected from three (3) independent, registered sleep technologists (RPSGT) for the N=100 Adult and N=47 Pediatric subjects, and manual scoring for sleep stage and respiratory rate events for the N=100 Respiratory Rate subjects, selected as the study population sample, by randomized, double-blinded assignment of each subject to three (3) additional, prospective scorers from the panel of N=9 total independent registered sleep technologists. The designated comparative reference was constructed using 2/3 Majority Scoring to evaluate the subject EnsoSleep device performance versus the predicate EnsoSleep device (K162627) performance for all event types and experimental endpoints evaluated, and the reference device Michele Sleep Scoring device (K112102) performance for hypopnea and central sleep apnea event types specifically.

Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)

Study Type: Clinical Validation Testing (cross-sectional experimental design)

Sample Size:

N=100 Adult subjects
N=47 Pediatric subjects
N=100 Respiratory Rate (RR) adult subjects

Standalone Performance: Not explicitly stated as standalone performance, but the device's performance was evaluated against a 2/3 Majority Scoring consensus reference.

Key Results:
The substantial equivalence of the subject EnsoSleep device to the predicate device was evaluated across four experimental endpoints:

Sleep Scoring Performance: The subject device's sleep scoring performance (PA, NA, OA) for sleep stages (Wake, N1, N2, N3, REM, Total) was observed to meet or exceed the predicate device's performance. For some events, there were statistically significant increases in agreement with 2/3 Majority Scoring.
- Adult Sample (N=100, 84,408 PSG epochs):
  - Wake: PA 93.5% (93.1%, 93.8%), NA 97.2% (97.1%, 97.4%), OA 96.1% (96.0%, 96.3%)
  - N1: PA 37.0% (35.6%, 38.5%), NA 98.3% (98.2%, 98.4%), OA 95.0% (94.8%, 95.1%)
  - N2: PA 88.3% (87.9%, 88.6%), NA 89.3% (89.0%, 89.6%), OA 88.8% (88.6%, 89.0%)
  - N3: PA 80.0% (79.0%, 81.0%), NA 96.3% (96.2%, 96.5%), OA 95.0% (94.9%, 95.2%)
  - REM: PA 90.9% (90.4%, 91.5%), NA 99.3% (99.2%, 99.3%), OA 98.3% (98.2%, 98.4%)
  - Total: PA 86.6% (86.4%, 86.9%)
- Pediatric Sample (N=47, 38,568 PSG epochs):
  - Wake: PA 93.1% (92.5%, 93.6%), NA 99.2% (99.1%, 99.3%), OA 97.9% (97.8%, 98.1%)
  - N1: PA 43.2% (40.4%, 45.9%), NA 98.8% (98.7%, 99.0%), OA 97.0% (96.8%, 97.1%)
  - N2: PA 92.6% (92.3%, 93.0%), NA 89.4% (89.0%, 89.8%), OA 90.9% (90.6%, 91.2%)
  - N3: PA 92.3% (91.6%, 92.9%), NA 97.5% (97.3%, 97.7%), OA 96.6% (96.4%, 96.7%)
  - REM: PA 80.9% (79.6%, 82.0%), NA 99.1% (99.0%, 99.2%), OA 97.0% (96.8%, 97.2%)
  - Total: PA 89.7% (89.4%, 90.0%)
Sleep Apnea Diagnostic Agreement: The subject device's PA, NA, and OA point-estimates were generally greater than or equivalent to the predicate device for OSA severity categories.
- Adult Sample (N=100):
  - AHI >= 5: PA 94.4%, NA 89.7%, OA 93.0%
  - AHI >= 15: PA 94.0%, NA 96.3%, OA 95.0%
  - REM AHI >= 5: PA 86.7%, NA 83.0%, OA 85.0%
  - REM AHI >= 15: PA 81.5%, NA 93.3%, OA 90.0%
- Pediatric Sample (N=47):
  - AHI >= 1: PA 94.4%, NA 77.8%, OA 89.4%
  - AHI >= 5: PA 90.5%, NA 100.0%, OA 95.7%
  - AHI >= 10: PA 78.6%, NA 94.9%, OA 91.5%
  - AHI >= 15: PA 85.7%, NA 100.0%, OA 97.9%
Scoring Events (Detection): The subject device's PA, NA, and OA point-estimates generally exceeded or were equivalent to the predicate device's for SDB, HYP, OSA, CSA, Arousal, and Leg Movement events.
- Adult Sample (N=100, 84,408 PSG epochs):
  - Sleep Disordered Breathing Events: PA 75.4%, NA 97.0%, OA 94.9%
  - Hypopnea Events: PA 66.3%, NA 97.1%, OA 95.5%
  - Obstructive Apnea Events: PA 74.1%, NA 99.3%, OA 98.8%
  - Central Apnea Events: PA 65.3%, NA 99.5%, OA 98.9%
  - Arousal Events: PA 73.6%, NA 95.6%, OA 93.2%
  - Leg Movement Events: PA 82.0%, NA 92.4%, OA 91.7%
- Pediatric Sample (N=47, 38,568 PSG epochs):
  - Sleep Disordered Breathing Events: PA 72.7%, NA 98.6%, OA 97.6%
  - Hypopnea Events: PA 68.8%, NA 98.9%, OA 98.0%
  - Obstructive Apnea Events: PA 45.5%, NA 99.7%, OA 99.5%
  - Central Apnea Events: PA 68.9%, NA 99.7%, OA 99.5%
  - Arousal Events: PA 78.6%, NA 97.0%, OA 95.5%
  - Leg Movement Events: PA 66.0%, NA 95.5%, OA 94.5%
Physiologic Analysis Events (Detection): For Sleep-Wake (SW) and Respiratory Rate (RR) events, the subject device's performance was statistically similar to the predicate device. For Total Sleep Time (TST), Deming regression and Bland-Altman analysis met or exceeded all acceptance criteria.
- Total Sleep Time (TST) Performance (across RR, Adult, Pediatric samples):
  - Deming Regression Slope (beta 1): Near unity (e.g., PPG-TST RR Sample: 0.964, EEG-TST RR Sample: 0.984, EEG-TST Adult Sample: 1.037, EEG-TST Pediatric Sample: 1.006)
  - Deming Regression Intercept (beta 0): Near zero (e.g., PPG-TST RR Sample: 0.089, EEG-TST RR Sample: 0.156, EEG-TST Adult Sample: -0.181, EEG-TST Pediatric Sample: 0.021)
  - Bland-Altman Mean Difference (MD): Near zero within

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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Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health & Human Services logo on the left and the FDA text logo on the right. The FDA text logo is in blue and includes the letters "FDA" followed by the words "U.S. Food & Drug Administration".

EnsoData, Inc. Sigrid Schoepel Director of Regulatory Affairs 111 S. Hamilton St. Suite 30 Madison, Wisconsin 53703

Re: K210034

Trade/Device Name: EnsoSleep Regulation Number: 21 CFR 882.1400 Regulation Name: Electroencephalograph Regulatory Class: Class II Product Code: OLZ Dated: May 11, 2021 Received: May 12, 2021

Dear Sigrid Schoepel:

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 (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 located 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.

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 803) for

1

devices or postmarketing safety reporting (21 CFR 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 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 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 medical devices and radiation-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).

Sincerely,

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

2

Indications for Use

510(k) Number (if known) K210034

Device Name EnsoSleep

Indications for Use (Describe)

EnsoSleep is intended for use in the diagnostic evaluation by a physician to assess sleep quality and as an aid for physicians in the diagnosis of sleep disorders and respiratory related sleep disorders in pediatric as follows:

· Pediatric patients 13 years and older with polysomnography (PSG) tests obtained in a Hospital or Sleep Clinic
· Adult patients with PSGs obtained in a Hospital or Sleep Clinic
· Adult patients with Home Sleep Tests

EnsoSleep is a software-only medical device to be used under the supervision of a clinician to analyze physiological signals and automatically score sleep study results, including the staging of arousals, leg movements, and sleep disordered breathing events including obstructive apneas (OSA), central sleep apneas (CSA), and hypopneas.

All automatically scored events and physiological signals which are retrieved, analyzed, displayed, and summarized are subject to verification by a qualified clinician. Central sleep apneas (CSA) should be manually reviewed and modified as appropriate by a clinician.

All events can be manually marked or edited within records during review.

Photoplethysmography (PPG) total sleep time is not intended for use when electroencephalograph (EEG) data is recorded. PPG total sleep time is not intended to be used as the sole or primary basis for diagnosing any sleep related breathing disorder, prescribing treatment, or determining whether additional diagnostic assessment is warranted.

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

☑ Prescription Use (Part 21 CFR 801 Subpart D)
☐ Over-The-Counter Use (21 CFR 801 Subpart C)

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K210034 EnsoSleep Traditional 510(k) Summary Prepared in accordance with the content and format outlined in 21 CFR 807.92

T SUBMITTER INFORMATION

Name:	EnsoData, Inc.
Address:	111 S. Hamilton Street, Suite 30
	Madison, WI 53703 USA
Phone:	(608)509-4704
Contact Person:	Sigrid Schoepel
Email:	sigrid@ensodata.com
Date:	June 8, 2021

II. SUBJECT DEVICE INFORMATION

Trade Name:	EnsoSleep
Common Name:	Automatic Event Detection Software for Polysomnography with Electroencephalograph (EEG)
Classification Name:	Electroencephalograph 21 CFR 882.1400
Regulatory Class:	II
Product Code:	OLZ
Intended Use:	EnsoSleep is intended for use for the diagnostic evaluation by a physician to assess slee

leep quality and as an aid for the diagnosis of sleep disorders and respiratory related sleep disorders in pediatric patients ages 13 years and older. EnsoSleep is a software-only medical device to be used under the supervision of a clinician to analyze physiological signals and automatically score sleep study results, including the staging of sleep, detection of arousals, leg movements, and sleep disordered breathing events including obstructive apneas, central apneas, and hypopneas. All automatically scored events and physiological signals analyzed are retrieved, displayed, and summarized, and are subject to verification by a qualified clinician. All events can be manually marked or edited within records during review.

Target Patient Population: Adult and Pediatric

III. PREDICATE DEVICE K162627 Trade Name: EnsoSleep Target Patient Population: Adults only

4

SUBJECT DEVICE DESCRIPTION IV.

EnsoSleep is a software-only medical device that analyzes previously recorded physiological signals obtained during sleep. Users of EnsoSleep are consistent with the roles required to run a sleep clinic: sleep physicians, sleep technicians, clinic operations managers, and IT administrators. EnsoSleep can analyze at-home and in-lab sleep studies for both adult and pediatric patients who are at least 13 years old. Automated algorithms are applied to the raw signals in order to derive additional signals and interpret the raw and derived signal information. The software automates recognition of the following: respiratory events, sleep staging events, arousal events, movement events, cardiac events, derived signals, and calculated indices. EnsoSleep does not interpret the results, nor does it suggest a diagnosis. The device only marks events of interest for review by a physician who is responsible for diagnoses. The device does not analyze data that are different from those analyzed by human scorers.

The signals and automated analyses can be visually inspected and edited prior to the results being integrated into a sleep study report.

The software consists of 4 major components:

The Application Platform runs on local clinic workstations and manages the detection, ● upload, and download of study records and scoring to and from the Storage Platform
The Processing Platform accepts raw physiological signals as inputs in order to recognize events, derive signals, and calculate indices
. The Storage Platform facilitates file and database storage in the EnsoSleep cloud through an API
The Dashboard is a web-based user interface to support configuration, clinic management, and sleep study scoring

Input signals used to derive outputs include:

Electroencephalogram (EEG) ●
Electrocardiogram (ECG) ●
Electro-oculogram (EOG) ●
Electromyogram (EMG) ●
Actigraphy
Airflow
Oximetry
Saturation of Peripheral Oxygen (SpO2)
Respiratory Inductance Plethysmogram (RIP)
Polyvinylidene Flouride (PVDF)
Photoplethysmogram (PPG)
Pulse Rate
Snoring Microphone ●
. Esophogeal Manometry

Outputs that are displaved to users include:

Respiratory Events
- o Obstructive Sleep Apneas (OSA)

5

Central Sleep Apneas (CSA) o
Mixed Sleep Apneas (MSA) O
Hypopneas O
Cheyne-Stokes Respiration O
Periodic Breathing O
Sleep Staging Events ●
- Stage Wake O
- Stage N1 O
- Stage N2 O
- Stage N3 O
- O Stage REM (rapid eye movement)
Arousal Events ●
- O Arousals
Movement Events ●
- o Leg Movements (LM)
- o Periodic Leg Movement Series (PLMS)
Cardiac Events* ●
- o Bradycardia
- o Tachycardia
Respiratory Rate Events
- o Respiratory Rate
Sleep-Wake Events ●
- o Wake
- o Sleep
Apnea-Hypopnea Index (AHI) ●
Sleep Architecture ●
Sleep Efficiency (SE) ●
Arousal Index (ArI) ●
Sleep Latency (SL) .
REM Latency (RL)
Total Sleep Time (TST)
Periodic Leg Movements (PLMS) Index ●

Capnogram data are not displayed to users.

The primary differences between the predicate device and subject device include:

-Target patient population: pediatric patients are included

-Automated scoring of Cheyne-Stokes and Periodic Breathing respiration events and Total Sleep Time

-Browser-based scoring interface to view and edit sleep studies

-Home-sleep studies are supported

The tachycardia and bradycardia outputs are not for use for cardiovascular monitoring or diagnosis, nor does the device detect arrhythmias.

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V. COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH THE PREDICATE DEVICE

The table below compares the predicate device EnsoSleep with the subject device EnsoSleep.

| Element | Predicate Device
EnsoData, Inc.
K162627
EnsoSleep | Submitted Device
EnsoData, Inc.
K210034
EnsoSleep | Discussion |
|----------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Indications for use | EnsoSleep is intended for use
for the diagnostic evaluation
by a physician to assess sleep
quality and as an aid for the
diagnosis of sleep and
respiratory related sleep
disorders in adults only.
EnsoSleep is a software-only
medical device to be used
under the supervision of a
clinician to analyze
physiological signals and
automatically score sleep
study results, including the
staging of sleep, detection of
arousals, leg movements, and
sleep disordered breathing
events including obstructive
apneas. All automatically
scored events are subject to
verification by a qualified
clinician. Central apneas,
mixed apneas, and hypopneas
must be manually marked
within records. | EnsoSleep is intended for
use in the diagnostic
evaluation by a physician
to assess sleep quality and
as an aid for physicians in
the diagnosis of sleep
disorders and respiratory
related sleep disorders in
pediatric and adult patients
as follows:
• Pediatric patients ages 13
years and older with
polysomnography (PSG)
tests obtained in a Hospital
or Sleep Clinic
• Adult patients with PSGs
obtained in a Hospital or
Sleep Clinic
• Adult patients with
Home Sleep Tests
EnsoSleep is a software-
only medical device to be
used under the supervision
of a clinician to analyze
physiological signals and
automatically score sleep
study results, including the
staging of sleep, detection
of arousals, leg
movements, and sleep
disordered breathing
events including
obstructive apneas (OSA),
central sleep apneas
(CSA), and hypopneas.
Central sleep apneas
(CSA) should be manually
reviewed and modified as
appropriate by a clinician. | Different The subject
device includes expansion
of the indications for use to
the pediatric population.
Clinical testing using the
scoring methodology for
the predicate device were
applied and validation to
demonstrate scoring for
expanded uses to pediatric
population and new
automated outputs. |
| Element | Predicate Device
EnsoData, Inc.
K162627
EnsoSleep | Submitted Device
EnsoData, Inc.
K210034
EnsoSleep | Discussion |
| | | All events can be
manually marked or edited
within records during
review. | |
| | | Photoplethysmography
(PPG) total sleep time is
not intended for use when
electroencephalograph
(EEG) data is recorded.
PPG total sleep time is not
intended to be used as the
sole or primary basis for
diagnosing any sleep
related breathing disorder,
prescribing treatment, or
determining whether
additional diagnostic
assessment is warranted. | |
| Intended Use | Analyze pre-recorded
physiological data acquired
during sleep. | Same as predicate. | Same |
| Patient
population | Adults only. | Adults and pediatric
patients 13 years old and
above. | Different |
| Environment of
use | Physician office (data analysis
and reporting). No limitation
on where data are acquired. | Same as predicate. | Different; the subject
device includes analysis of
home sleep testing (HST)
of adult patients. |
| Signals analyzed | EEG, ECG, EOG, EMG
waveforms; SpO2; respiratory
effort; airflow; heart/pulse
rate; snoring loudness; head
movement and position. | EEG, ECG, EOG, EMG
waveforms; SpO2;
respiratory effort; airflow;
heart/pulse rate; snoring
loudness; head movement
and position. | Similar |
| Sleep measures | Sleep, REM and N3 onset;
total sleep and recording
times; sleep efficiency % time
by sleep stage; awakenings
per hour; wake after sleep
onset. | Same as predicate. | Same |
| Automatically
score sleep stages | Yes; automatically detects
stage Wake (W), REM (R), | Same as predicate. | Same |
| Element | Predicate Device
EnsoData, Inc.
K162627
EnsoSleep | Submitted Device
EnsoData, Inc.
K210034
EnsoSleep | Discussion |
| | NREM 1 (N1), NREM 2 (N2)
and slow wave sleep (N3). | | |
| Automatically
score sleep
disordered
breathing events | No; OSA, CSA and mixed
hypopneas must be manually
scored | Yes; automatic detection
of the following events:
Obstructive apneas
(OSA), Central
apneas (CSA), Hypopneas, Cheyne-Stokes
respiration (CSR), and Periodic breathing
(PBE). Additional apnea and
sleep disordered
breathing event types
may be manually
marked within the
records. CSA events
should also be
manually scored | Similar
Sleep disordered breathing
events are detected, and the
additional events are
identified using the existing
airflow inputs as in the
predicate device. |
| Automatically
score arousal
events | Yes; automatically detects
arousal events. | Yes; automatically detects
arousal events;
respiratory-effort related
arousals, limb movement
related arousals, and
spontaneous cortical
arousal. | Different
The general arousal events
detected by the subject
device are now identified
more specifically as to the
type of arousal events
(same events as detected by
the predicate). |
| Automatically
score movement
events | Yes; automatically detects leg
movement events. | Same as predicate. | Same |
| Automatically
score cardiac
events | No. | Yes; brachycardia and
tachycardia. | Different
The ECG signals used to
determine these events
were used in the predicate
device to determine
breathing, arousal, and
movement events are also
used to detect cardiac
events. The tachycardia and
bradycardia feature is not
intended for use for
cardiovascular monitoring
or diagnosis, nor does the |
| Element | Predicate Device
EnsoData, Inc.
K162627
EnsoSleep | Submitted Device
EnsoData, Inc.
K210034
EnsoSleep | Discussion |
| Automatically
determine
derived values | No. | Yes; effort belt respiratory
rate and PPG respiratory
rate. | subject device detect
arrhythmias.

7

8

9

10

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VI. PERFORMANCE DATA

The following performance data were provided in support of the substantial equivalence determination. Since this is a software-only medical device that does not control other devices the performance data do not include biocompatibility, electrical safety, electromagnetic compatibility, mechanical, acoustic, or animal testing.

The intended use population, study population, conditions of interest, designated comparative reference, designated comparative benchmarks, and experimental endpoints were defined. Following the application of clinical laboratory selection controls, five (5) clinical testing laboratories were evaluated, and two (2) AASM Accredited Sleep Testing Facilities were selected each with two (2) regional sleep testing centers that met all laboratory quality, external validity, and subject spectrum controls. Following a cross-sectional study design, an archived collection of retrospective diagnostic clinical PSG subject data was collected and verified to meet the specified disease spectrum, medical condition, medication, and demographic requirements. To construct the final study sample from the archived collection population, a randomized sampling with proportionate allocation across each sleep apnea disease severity quantile (normative, mild, moderate, and severe sleep apnea) was used to construct a valid Adult Sample of N=100 adult subjects (AHI mean: 22.4 [95% Cl: 18.6%, 26.1%], std: 18.8, median: 17.2, min: 0, max: 109.2, rule: 1.a.) and Pediatric Sample of N=47 pediatric subjects (AHI mean: 11.4 [95% CI: 7.6%, 15.6%], std: 13.6, median: 7.0, min: 0, max: 60.3, rule: 1.a.) from the first laboratory N=1984 archived collection of retrospective diagnostic clinical PSG data, and a valid Respiratory Rate Sample of N=100 adult subjects (AHI mean: 13.2 [95% Cl: 9.7%, 16.5%], std: 17.1, median: 6.6, min: 0, max: 82.9, rule: 1.b.) from the second laboratory N=1079 archived collection of retrospective diagnostic clinical PSG data.

The N=100 Adult, N=47 Pediatric, and N=100 Respiratory Rate Study Samples were observed and verified to have no statistically significant differences in the sleep apnea disease state distributional characteristics relative to the laboratory archived collection populations, confirming preservation of disease spectrum breadth and representativeness with respect to the intended use population. The N=100 study samples were verified to contain subjects from all (4/4) sleep apnea disease state severity quantiles, including normative, mild, moderate, and severe sleep apnea. subjects from all (7/7) of the predetermined relevant and/or confounding medical condition groups of interest, including sleep disorders, psychiatric disorders, neurologic disorders, neuro-developmental disorders, cardiac disorders, pulmonary disorders, metabolic and other disorders, subjects from all (5/5) predetermined relevant and/or confounding medication groups of interest, including benzodiazepines, antidepressants, stimulants, opiates, and sleep aids, subjects from each of (7/7) identified demographic group of interest, including all sexes, adult age groups, pediatric age groups, BMI groups, weight groups, and sleepiness groups. Based on these verification and control procedures, the study sample was determined to be a representative sample of the defined intended use and user population. Following the finalization of each N=100 subject Adult, N=47 Pediatric, and N=100 Respiratory Rate study sample respectively, six (6) clinical testing laboratories were evaluated for independent manual scoring, three (3) laboratories were selected, and the clinical test setting was established for constructing a valid 2/3 Majority Scoring consensus reference, using N=9 total registered scoring technologists (RPSGTs) with 5 to 20+ years clinical experience by verification

12

of meeting all defined study scoring-acquisition, scoring-blind, and rater-quality certification controls. Manual scoring for sleep stage, hypopnea events, obstructive sleep apnea (OSA) events, central sleep apnea (CSA) events, arousal events, limb movement events, respiratory effort related arousal (RERA) events, cheyne-stokes (CS) respiration events, and periodic breathing (PB) events were prospectively collected from three (3) independent, registered sleep technologists (RPSGT) for the N=100 Adult and N=47 Pediatric subjects, and manual scoring for sleep stage and respiratory rate events for the N=100 Respiratory Rate subjects, selected as the study population sample, by randomized, double-blinded assignment of each subject to three (3) additional, prospective scorers from the panel of N=9 total independent registered sleep technologists. The designated comparative reference was constructed using 2/3 Majority Scoring to evaluate the subject EnsoSleep device performance versus the predicate EnsoSleep device (K162627) performance for all event types and experimental endpoints evaluated, and the reference device Michele Sleep Scoring device (K112102) performance for hypopnea and central sleep apnea event types specifically. Objective performance benchmarks and acceptance criteria in terms of positive agreement (PA), negative agreement (NA), overall agreement (OA), mean absolute error (MAE), Deming Regression analysis slope and intercept coefficients, Bland-Altman mean difference and 95% upper and lower limits of agreement, each with 95% two-sided bootstrap confidence intervals (R=2000), were predefined competitively based on analysis of reported performance in the predicate device 510(k) event detection and diagnostic agreements reported. In particular, the acceptance criteria were selected based on PA, NA, OA, MAE, Deming Regression coefficient, Bland-Altman mean difference and limits of agreement performance criteria that validate performance substantially equivalent to, or greater than, but not lesser than by more than 10% or similarly defined criteria in any category of the predicate 510(k) reported device performance across all endpoints respectively.

Clinical validation testing performance analysis was collected with the final EnsoSleep software release version, final revision level, final design specification, final instructions for use, and indications for use, in the intended use environment, on the intended use population, and by the intended users, in order to validate the substantial equivalence, and the safety and effectiveness of the subject EnsoSleep device for its intended use. EnsoSleep device performance was evaluated using the defined cross-sectional experimental design, statistical methodology, and set of comprehensive experimental controls, across the following four (4) experimental endpoints:

1. EnsoSleep is intended to assist clinicians with the assessment of sleep quality, therefore performance of device sleep scoring must be validated.
1. EnsoSleep is intended to assist clinicians with the scoring sleep disordered breathing events used in diagnostic evaluation, therefore device performance for diagnosing sleep apnea must be validated.
1. EnsoSleep is intended to analyze physiological signals and automatically score sleep study results, including detection of SDB events, Hypopnea events, Apnea events, including OSA events, CSA events, Arousal events, Limb Movement events, RERA events, CS events, and PB events, therefore device performance for detecting each event type must be validated.
1. EnsoSleep is intended to analyze physiological signals and automatically score sleep study results, including detection of Respiratory Rate events, Sleep-Wake events, and Total Sleep Time, therefore device performance for detecting each event type must be validated.

13

The final experimental results and statistical analysis were reported for each endpoint. In total PA, NA, OA. Kappa and two-sided 95% bootstrap median confidence intervals (R=2000) were calculated by pooled-epochs versus 2/3 Majority Scoring in 20 event detection experiments evaluating 6 sleep staging events (Wake, N1, N2, N3, REM, Total) in 3 samples (adult, pediatric, and RR), 11 scoring events (SDB, HYP 1.a. (3%), HYP 1.b. (4%), Apnea, OSA, CSA, Arousal, Limb Movement, RERA, CSE, PBE) in 2 samples (adult and pediatric ), and 3 physiologic analysis events (RR. Sleep-Wake. TST) with PA. NA. OA. Kappa. Deming Regression 01 slope and B0 intercept regression coefficients, and Bland-Altman analysis, including mean differences (MD), upper limits of agreement (ULOA), and lower limits of agreement (ULOA) with twosided 95% bootstrap confidence intervals for Sleep-Wake, TST in 3 samples (adult, pediatric, and RR) as well as mean absolute error (MAE) and percent epochs ±2 breaths per minute for respiratory rate (RR) scoring in the RR adult sample, and 6 sleep apnea diagnostic severity categories (AHI ≥ 5, AHI ≥ 15, REM-AHI ≥ 15, REM-AHI ≥ 15, subgroup AHI ≥ 1, subgroup AHI ≥ 10) in 2 samples (adult and pediatric) with PA, NA, OA, Kappa, two-sided 95% bootstrap median confidence intervals (R=2000), and positive and negative likelihood ratio pairs, across all 4 experimental endpoints respectively.

The subject EnsoSleep device event detection and diagnostic agreement performance were observed to meet or exceed the PA, NA, and OA performance acceptance in the 26 total experiments (26/26) across all 4 experimental endpoints evaluated, including all 20 event detection experiments (20/20) and all 6 diagnostic agreement experiments (6/6), and with all 4 experimental endpoints (4/4) statistically analyzed and evaluated in two or more samples (2) per each endpoint respectively (2/2 Adults and Pediatrics in Endpoints 2 and 3/3 Adults, Pediatrics, and RR in Endpoints 1 and 4):

For sleep staging events Endpoint 1, all 3 EnsoSleep PA, NA, and OA point-estimates vs ● 2/3 Majority Scoring were observed to be greater than the predicate device PA, NA, and OA point-estimates vs 2/3 Majority Scoring in some events in the Adult Sample (Wake, N2, REM, Total), Pediatric Sample (Wake, N1, N2, N3, REM, Total,), and RR Sample (Wake. N2. N3. REM. Total). Additionally, some of those event detection differences that were in all 3 performance categories (PA/NA/OA) represented a statistically significant result in terms of higher agreement with 2/3 Majority Scoring, based on low/upper-bound comparison of two-sided 95% bootstrap percentile method confidence intervals to the predicate performance, in each sample: Adult Sample (REM). Pediatric Sample (Wake, N3, Total), and RR Sample (Wake, N2, REM, Total). None of the 6 events evaluated were observed with PA, NA, or OA point-estimates vs 2/3 Majority Scoring that were 10% or lower in any of the sleep staging event types evaluated.
For sleep apnea diagnostic agreement Endpoint 2, all 3 EnsoSleep PA, NA, and OA ● point-estimates vs 2/3 Majority Scoring were observed to be greater than the predicate device PA, NA, and OA point-estimates vs 2/3 Majority Scoring in some OSA severity categories in the Adult Sample (AHI ≥ 5) and Pediatric Sample (AHI ≥ 1). There were no samples or OSA severities for which there were statistically significant differences observed in all 3 performance measures (PA/NA/OA), based on low/upper-bound comparison of two-sided 95% bootstrap percentile method confidence intervals. With the exception of Pediatric Sample AHI > 10 PA with an observed comparison of 12.6%, none of the 6 OSA severity categories evaluated were observed with PA, NA, or OA point-

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estimates vs 2/3 Majority Scoring that were 10% or lower in any of the 3 diagnostic agreement performance criteria evaluated (PA/NA/OA) respectively.

. For scoring events Endpoint 3, all 3 EnsoSleep PA, NA, and OA point-estimates vs 2/3 Majority Scoring were observed to be greater than the designated predicate device PA. NA, and OA point-estimates vs 2/3 Majority Scoring in some events in the Adult Sample (SDB, HYP, OSA, CSA, Arousal) and the Pediatric Sample (SDB, HYP, CSA, Arousal, RERA). Additionally, some of those event detection differences that were in all 3 performance categories (PA/NA/OA) represented a statistically significant result, based on low/upper-bound comparison of two-sided 95% bootstrap percentile method confidence intervals, in each sample respectively: Adult Sample (SDB, OSA, and Arousal), and Pediatric Sample (SDB. HYP. Arousal. RERA). None of the 12 events evaluated were observed with PA, NA, or OA point-estimates vs 2/3 Majority Scoring that were 10% or lower in any of the scoring event types evaluated.
For physiologic analysis events Endpoint 4. for SW and RR events. all three EnsoSleep . subject device PA, NA, OA, percent epochs ≤2 brpm, and/or MAE point-estimates vs 2/3 Majority Scoring were observed to be statistically similar to the predicate device PA, NA, and OA point-estimates vs 2/3 Majority Scoring in all SW and RR event types evaluated. None of the PPG-SW events evaluated were observed with PA, NA, OA pointestimates vs 2/3 Majority Scoring that were 10% or lower in any of the EEG-SW sleep staging event types evaluated in the adult, pediatric, or in the RR Samples respectively, and a global minima PPG-SW performance statistic of 89% PA in the RR Sample (4% abs diff vs 93% EEG-SW). No statistically significant differences were observed between PPG-RR and EB-RR respiratory rate events vs 2/3 Majority Scoring; by ≥90% percent epochs with RR-value within ≤2 brpm of 2/3 Majority Scoring RR-value, and by MAE of RR value within ≤ 2 brpm of 2/3 Majority Scoring RR-value, when both were evaluated and compared in the RR Sample respectively. For TST the Deming Regression coefficient parameters Slope B1 was near unity with 0.90