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Onera STS 2 measures and records multiple physiological parameters from a patient during a sleep study, which are used by clinicians to decide on the diagnosis of sleep disorders.

Onera STS 2 is intended to be used on a patient who has been prescribed a polysomnography study by a healthcare professional. The device is designed to be used under the direction of a physician or trained technician but applied by a layperson.

The recorded data will be made available to the healthcare professional to assist in the diagnosis of sleep disorders.

The device is intended to be used for adults.

The device is not a life supporting physiological monitor.

Onera Sleep Test System 2 (Onera STS 2) is a hardware, wearable system for measuring physiological signals during a sleep study. The device can be used in the home (Home Healthcare Environment) as well as in Professional Healthcare Facilities.

The device measures EEG, EOG, EMG, ECG, respiratory signals, cannula based respiratory flow, oxygen saturation, activity, position, ambient light level and sound pressure level.

The ECG signal is not intended for diagnosis of cardiac disorders, except for the manual determination of arrhythmia during polysomnography studies.

The Onera STS 2 does not provide any automated output like heart rate, assessments of arrhythmia, heart rate variability, or other related heart rate measurement functions.

Onera STS 2 consists of five Sensors applied on the forehead, upper chest area, abdomen and lower leg area (both left and right leg).

The Sensors should be placed on intact skin. During the night measurement it is not needed to inspect the application sites. The Sensors encrypt the recorded signals and upload the measurement data during the night to the Patient App installed on the patient's phone via Bluetooth. The Patient App securely transfers the data to the cloud interface for further processing once all data has been uploaded. The output of the system is represented by a file in EDF format which contains the recorded (physiological) signals. EDF files can be read by any application software that accepts such files as input.

It is not possible to relocate the Sensors during a sleep study since the Sensor is single-use and for one sleep study only.

Here's a summary of the acceptance criteria and study information for the Onera STS 2, based on the provided FDA 510(k) clearance letter:

Onera STS 2: Acceptance Criteria and Performance Study Summary

1. Table of Acceptance Criteria and Reported Device Performance

The provided document primarily focuses on the SpO2 measurement accuracy as a key performance metric with specific acceptance criteria.

Note: While other parameters are listed as "Identical" to the predicate, specific numerical acceptance criteria for those parameters are not explicitly stated in this document beyond their qualitative equivalence.

2. Sample Size and Data Provenance for the Test Set

• Sample Size: 12 healthy subjects
  • 9 male, 3 female
  • Aged between 23 and 46 years old
• Data Provenance: The study was conducted in an "independent research laboratory." The country of origin is not explicitly stated in the provided text. The study involved "induced hypoxia," indicating a prospective, controlled experimental design.

3. Number and Qualifications of Experts for Ground Truth

• The document does not mention the use of experts to establish ground truth for the SpO2 accuracy test.
• The ground truth for SpO2 was established by "laboratory co-oximeter" measurements of arterial hemoglobin oxygen (SaO2) values from blood samples.

4. Adjudication Method for the Test Set

• The document does not describe any adjudication method. The SpO2 accuracy was determined by direct comparison of the device's SpO2 measurements to SaO2 values from a laboratory co-oximeter.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not conducted or described in this document. The device primarily measures physiological parameters, and the study focused on the accuracy of these measurements rather than human reader interpretation with or without AI assistance.

6. Standalone (Algorithm Only) Performance Study

• Yes, a standalone performance study was conducted for SpO2 measurement accuracy. The device's SpO2 readings were directly compared to reference SaO2 values without human intervention in the SpO2 measurement process itself. The Onera STS 2 is described as measuring and recording parameters, with the output as an EDF file to be read by other software. The SpO2 accuracy assessment is specifically for the device's measurement capability.

7. Type of Ground Truth Used

• Objective Measurement (Laboratory Co-oximeter): For SpO2 accuracy, the ground truth was established by arterial hemoglobin oxygen (SaO2) values determined from blood samples using a laboratory co-oximeter, which is considered a gold standard for blood oxygen saturation.

8. Sample Size for the Training Set

• The document does not provide information regarding the sample size for a training set. This is likely because the performance study described (SpO2 accuracy) is a validation of the device's sensor capabilities, not an evaluation of a machine learning algorithm that would typically require a training set. The device outputs raw physiological signals in EDF format for clinicians to interpret, rather than providing automated diagnoses based on an internal algorithm.

9. How the Ground Truth for the Training Set Was Established

• As no training set is mentioned or implied for the device's core functionality (measuring and recording parameters for clinician interpretation), this information is not applicable and not provided in the document.

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Onera STS measures and records multiple physiological parameters from a patient during a sleep study which are used by clinicians to make a decision on the diagnosis of sleep disorders.

Onera STS is intended to be used on a patient, who has been prescribed a sleep study by a healthcare professional. The device is designed to be used under the direction of a physician or trained technician but applied by a layperson. The recorded data will be made available to a healthcare professional to assist in the diagnosis of sleep disorders.

The device is intended to be used for adults.

Onera STS is a wearable system for measuring (physiological) signals during a sleep study. The device can be used in home (Home Healthcare Environment) as well as Professional Healthcare Facilities, to perform the sleep study.

Onera STS consists of four sensors applied on the forehead, upper chest area, abdominal and lower leg area.

The sensors measure EEG, EOG, EMG, ECG, bioimpedance based respiratory effort, bioimpedance based respiratory flow, cannula based respiratory flow, oxygen saturation, activity, position, and sound pressure level.

The study preparation and data retrieval are done in a professional/clinical environment by the trained operator. The device is provided to the user by the trained operator.

The device is not a life supporting physiological monitor.

The provided text is a 510(k) summary for the Onera Sleep Test System (Onera STS). It details the device, its intended use, and a comparison to a previously cleared predicate device (K210593). The primary change in this submission (K223573) is an extension of the device's use time from 8 hours to 16 hours.

It's crucial to understand that this document is a premarket notification asserting substantial equivalence, not a detailed clinical study report proving performance against specific acceptance criteria for diagnostic accuracy. The FDA's review for a 510(k) focuses on safety and effectiveness in comparison to a predicate device, rather than requiring new, full-scale clinical trials for every parameter.

Therefore, the information regarding acceptance criteria and performance studies within this document is limited to demonstrating that the change (extended wear time) does not introduce new safety or effectiveness concerns, and that the device still meets regulatory standards. There is no information provided about a study that assesses the device's diagnostic accuracy or performance against specific, quantifiable "acceptance criteria" for detecting sleep disorders. The device is described as measuring and recording parameters for clinicians to use, not as an automated diagnostic tool itself.

Given this context, I will address your points based on the available information in the provided text.

Acceptance Criteria and Device Performance (Based on provided 510(k) Summary)

The FDA 510(k) summary primarily focuses on demonstrating that the modified device (Onera STS with 16-hour wear time) is substantially equivalent to its predicate device (Onera STS with 8-hour wear time) and that the change does not introduce new safety or effectiveness concerns. There are no explicit "acceptance criteria" for diagnostic accuracy or performance of the device in the context of detecting sleep disorders presented in this document. The "performance testing" mentioned is related to meeting general safety and performance standards, and verifying that the extended wear time does not degrade existing performance or safety.

Table of Comparison (Not "Acceptance Criteria" for Diagnostic Performance):

The table below summarizes the comparison between the proposed device and the predicate, highlighting the only stated difference: extended use time. This is a demonstration of substantial equivalence rather than meeting specific diagnostic acceptance criteria.

Study Details (Based on provided 510(k) Summary)

The provided document describes a 510(k) "premarket notification" which asserts substantial equivalence, not a dedicated clinical study for diagnostic accuracy. Therefore, information related to diagnostic performance studies, AI algorithms, human readers, or specific "acceptance criteria" for disease diagnosis is largely absent.

1. A table of acceptance criteria and the reported device performance:

   • As explained above, the "acceptance criteria" discussed are for substantial equivalence and compliance with general safety and performance standards for a medical device (e.g., biocompatibility for extended wear, electrical safety, EMC).
   • The reported performance for the primary change (extended wear time) is implied by the statement: "The extension is supported by new skin irritation testing and 16-hour wear time testing as part of design verification and validation activities." This testing demonstrated that the device performs safely and effectively for the increased duration. No quantitative performance metrics related to diagnostic accuracy (e.g., sensitivity, specificity for detecting specific sleep disorders) are provided, as the device records data for clinicians to use for diagnosis, it does not autonomously diagnose.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

   • The document states: "No clinical data was required to support equivalence." This means a dedicated clinical test set for diagnostic accuracy was not part of this 510(k) submission.
   • The extended wear time and skin irritation testing would have involved engineering and biocompatibility testing, likely using a limited number of human subjects or in-vitro/in-vivo models. Specific sample sizes and provenance for these verification/validation activities are not detailed in this summary.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

   • Not applicable/Not provided. Since "No clinical data was required," there was no clinical test set for which ground truth needed to be established by experts for diagnostic performance.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • Not applicable/Not provided.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • Not applicable. The document does not describe the device as incorporating AI for automated diagnosis or interpretation to assist human readers. The device records physiological parameters for clinicians to interpret.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • Not applicable. The device's stated function is to "measure and record multiple physiological parameters... which are used by clinicians to make a decision on the diagnosis of sleep disorders." It is not presented as a standalone diagnostic algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • Not applicable for diagnostic ground truth. The "ground truth" for this 510(k) was the predicate device's cleared performance and safety standards, combined with verification and validation of the extended wear time not introducing new risks.

8. The sample size for the training set:

   • Not applicable. This device is not described as involving machine learning or AI that would require a "training set" for diagnostic functions.

9. How the ground truth for the training set was established:

   • Not applicable.

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Onera STS measures and records multiple physiological parameters from a sleep study which are used by clinicians to make a decision on the diagnosis of sleep disorders.

Onera STS is intended to be used on a patient, who has been prescribed a sleep study by a healthcare professional. The device is designed to be used under the direction of a physician or trained technician but applied by a layperson.

The recorded data will be made available to a healthcare professional to assist in the diagnosis of sleep disorders.

The device is intended to be used for adults.

Onera STS is a wearable system for measuring (physiological) signals during a sleep study. The device can be used in home (Home Healthcare Environment) as well as Professional Healthcare Facilities, to perform the sleep study.

Onera STS consists of four sensors applied on the forehead, upper chest area, abdominal and lower leg area.

The sensors measure EEG, EOG, EMG, ECG, bioimpedance based respiratory effort, bioimpedance based respiratory flow, cannula based respiratory flow, oxygen saturation, activity, position, and sound pressure level.

The study preparation and data retrieval are done in a professional/clinical environment by a dedicated trained operator.

The device is not a life supporting physiological monitor

Here's an analysis of the acceptance criteria and the study that proves the device meets the acceptance criteria, based on the provided FDA 510(k) summary for the Onera Sleep Test System (K210593):

1. Table of Acceptance Criteria and Reported Device Performance

The FDA 510(k) summary primarily focuses on demonstrating substantial equivalence to a predicate device rather than explicitly stating pre-defined "acceptance criteria" in a quantitative table format for all parameters. However, we can infer some key performance metrics and their proven results:

2. Sample Size Used for the Test Set and Data Provenance

• SpO2 Accuracy Validation:
  • Sample Size: 10 healthy volunteers.
  • Data Provenance: Not explicitly stated regarding country of origin, but described as a controlled study meeting ISO standards. It is a prospective study as it involved active data collection from subjects for the purpose of validating the device.
• Comparative Sleep Study Testing (Primary Clinical Test Set):
  • Sample Size: 32 patients.
  • Data Provenance: Not explicitly stated regarding country of origin or if it was retrospective or prospective. However, the description states "concurrently applied to 32 patients undergoing a routine sleep study," which implies a prospective, clinical data collection for the validation purpose.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

• SpO2 Accuracy Validation: The ground truth for SpO2 accuracy is typically established using a reference oximeter that has been calibrated and validated according to specific standards (e.g., arterial blood gas measurements). The document does not specify the number or qualifications of experts involved in the direct "ground truth" establishment, as it's a technical parameter validated against a standard reference.
• Comparative Sleep Study Testing:
  • Number of Experts: Not explicitly stated. The document mentions "Studies were scored blinded by a qualified sleep professional." This phrasing suggests at least one, but possibly more, qualified sleep professionals were involved.
  • Qualifications: "Qualified sleep professional." Specific details like years of experience or board certification (e.g., diplomate of the American Board of Sleep Medicine) are not provided.

4. Adjudication Method for the Test Set

• SpO2 Accuracy Validation: No explicit adjudication method is mentioned, as SpO2 validation against a reference is a direct measurement comparison.
• Comparative Sleep Study Testing: The scoring was done "blinded" by a qualified sleep professional. It's not explicitly stated if multiple professionals scored and then adjudicated differences (e.g., 2+1, 3+1). The wording "a qualified sleep professional" might suggest single-reader scoring relative to the predicate device, or it might be a simplification of a more complex process. More specific adjudication methods (e.g., consensus, expert panel review) are not described.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study and Effect Size

• No explicit MRMC comparative effectiveness study involving human readers improving with AI vs. without AI assistance was described. This study is focused on the device's ability to record and process physiological parameters similarly to a predicate device, and the sleep staging/scoring is done by a human professional based on the device's output. The device itself is not described as providing AI-assisted interpretations that then improve human reader performance. Its purpose is to provide the raw data for such interpretation.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• The study is essentially a standalone performance evaluation of the device's data collection and preliminary processing capabilities, compared against a predicate device. The "scoring" is done by a human, but the device provides the signals for that scoring. Therefore, the device's performance in generating these signals is evaluated independently of a human's final diagnostic decision. The agreement metrics (Cohen's kappa, accuracy, sensitivity, specificity, correlation) reflect the device's ability to produce data that leads to similar scores as the predicate device.

7. Type of Ground Truth Used

• SpO2 Accuracy Validation: The ground truth for SpO2 was based on a reference standard (likely a co-oximeter or another highly accurate method) as per ISO 80601-2-61:2019, generally derived from arterial blood gas measurements.
• Comparative Sleep Study Testing: The ground truth was established by comparing the Onera STS data to the data from the predicate device (Embletta MPR), with both sets of data scored by a "qualified sleep professional." This means the ground truth for sleep staging and physiological scoring is expert scoring of data from a legally marketed device. It is not stated to be pathology or direct outcomes data, but rather a comparative performance to a widely accepted clinical standard.

8. Sample Size for the Training Set

• The provided document does not mention a specific "training set" or its size for the Onera STS device. This implies that the device's underlying algorithms (if any, separate from standard signal processing) were not developed using a distinct, large, and formally defined training dataset in the way a deep learning AI model would be. The focus is on the device's performance in measuring and recording parameters, and the comparison to an existing predicate device.

9. How the Ground Truth for the Training Set Was Established

• Since a dedicated "training set" is not described, the method for establishing its ground truth is also not applicable or not provided in this document. The device appears to rely on established physiological measurement principles and signal processing, validated against a predicate device and relevant standards.

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