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The Apnea Risk Evaluation System (ARES), Model 620 is indicated for use in the diagnostic evaluation by a physician of adult patients with possible sleep apnea. The ARES can record and score respiratory events during sleep (e.g., apneas, hypopneas, mixed apneas and flow limiting events). The device is designed for prescription use in the patient's home to aid a physician in diagnosing adults with possible sleep-related breathing disorders.

The Apnea Risk Evaluation System (ARES™) includes a battery powered patient worn device called a Unicorder (Model 620). The Unicorder is worn by a patient for one to three nights, each night recording up to 7 hours of data. Data recorded includes oxygen saturation, snoring level, head movement, head position, and airflow. Additionally, the Unicorder 620 allows collection of data from ARES compatible peripheral devices. The device monitors signal quality during acquisition and notifies the user via voice messages when adjustments are required. A standard USB cable connects the Unicorder to a USB port on a host computer when patient data is to be uploaded or downloaded. The USB cable provides power to the Unicorder during recharging from the host computer or from a USB wall charger. The Unicorder cannot record nor can it be worn by the patient when connected to the host computer or the wall charger. Software, residing on a local PC or a physical or virtual server controls the uploading and downloading of data to the Unicorder, processes the sleep study data and generates a sleep study report. The ARES™ can auto-detect positional and non-positional obstructive and mixed apneas and hypopneas similarly to polysomnography. It can detect sleep/wake and REM and non-REM. After the sleep study has been completed, data is transferred off the Unicorder is prepared for the next study. The downloaded sleep study record is then processed with the ARES ™ Insight software to transform the raw signals and derive and assess changes in oxygen saturation (SpO2), head movement, head position, snoring sounds, airflow, and EEG or respiratory effort. The red and IR signals are used to calculate the SpO₂. The actigraphy signals are transformed to obtain head movement and head position. A clinician can convert an auto-detected obstructive apnea to a central apnea based on visual inspection of the waveforms. ARES "" Screener can predict pre-test probability of obstructive sleep apnea (OSA). The ARES "" data can also assist the physician to identify patients who will likely have a successful OSA treatment outcome, including CPAP and oral appliance therapies. ARES™ can help identify patients who would benefit from a laboratory PAP titration.

The provided text does not contain detailed information about a study proving the device meets acceptance criteria. Instead, it focuses on demonstrating substantial equivalence to a predicate device through a comparison of specifications and non-clinical testing. Therefore, I cannot fully answer all aspects of your request as the specific study details, sample sizes, expert qualifications, and ground truth methodologies for performance evaluation are not present.

However, I can extract the available information regarding acceptance criteria and reported device performance from the comparison table.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly defined by the "Performance" section of the comparison table between the predicate device (ARES Model 610) and the proposed device (ARES Model 620). For most parameters, the goal is "Identical" or "Equivalent," meaning the new device should perform at least as well as the predicate.

2. Sample size used for the test set and the data provenance:

The document describes "Comparative testing between the Predicate Device ARES Model 610, K111194 as cleared on 07/07/2011 and the proposed ARES Model 610 demonstrates substantial equivalence." However, it does not specify the sample size (number of patients or recordings) used for this comparative testing or the data provenance (e.g., country of origin, retrospective/prospective nature).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

This information is not provided in the document. The document refers to "nonclinical and clinical tests" but does not detail how ground truth was established for these tests, nor the involvement or qualifications of any experts.

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

This information is not provided in the document.

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:

The document does not describe an MRMC comparative effectiveness study involving human readers or AI assistance effect size. The comparison is between two devices, not human performance with and without AI.

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

The document states, "The ARES™ can auto-detect positional and non-positional obstructive and mixed apneas and hypopneas similarly to polysomnography. It can detect sleep/wake and REM and non-REM." This implies a standalone algorithmic performance for detecting and scoring respiratory events. However, no specific standalone performance metrics (e.g., sensitivity, specificity, accuracy) are reported for this automated detection/scoring. The "SpO2" and other sensor accuracy values are "device performance" but not necessarily "standalone algorithm performance" in the context of diagnostic output.

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

This information is not explicitly stated. Given that the device "can auto-detect positional and non-positional obstructive and mixed apneas and hypopneas similarly to polysomnography," it is highly probable that Polysomnography (PSG) was used as the ground truth. However, the document does not explicitly confirm this or specify how the PSG data was analyzed to establish ground truth (e.g., by experts, automated scoring, etc.).

8. The sample size for the training set:

The document describes comparative testing and verification/validation but does not mention a "training set" or its size, which would typically be associated with machine learning model development. This implies the comparison is more about hardware and firmware functionality and existing algorithms rather than the development of a new AI model requiring a separate training set.

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

Since no training set is mentioned (see point 8), there is no information on how its ground truth was established.

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The Apnea Risk Evaluation System (ARES™), Model 610 is indicated for use in the diagnostic evaluation by a physician of adult patients with possible sleep apnea. The ARES™ can record and score respiratory events during sleep (e.g., apneas, hypopneas, mixed apneas and flow limiting events). The device is designed for prescription use in home diagnosis of adults with possible sleep-related breathing disorders.

The Apnea Risk Evaluation System (ARES™) includes a device called a Unicorder which records oxygen saturation, pulse rate, snoring level, head movement and head position, and airflow. Additionally, a physiological signal from the forehead used to stage sleep or respiratory effort signal obtained from an optional piezo respiratory effort belt can be acquired. The battery powered Unicorder provides sufficient capacity to record two nights of data. The device monitors signal quality during acquisition and notifies the user via voice messages when adjustments are required. A standard USB cable connects the Unicorder to a USB port on a host computer when patient data is to be uploaded or downloaded. The USB cable provides power to the Unicorder during recharging from the host computer or from a USB wall charger. The Unicorder cannot record nor can it be worn by the patient when connected to the host computer or the wall charger. Software, residing on a local PC or a physical or virtual server controls the uploading and downloading of data to the Unicorder, processes the sleep study data and generates a sleep study report. The ARES™ can auto-detect positional and non-positional obstructive and mixed apneas and hypopneas similarly to polysomnography. It can detect sleep/wake and REM and non-REM. After the sleep study has been completed, data is transferred off the Unicorder is prepared for the next study. The downloaded sleep study record is then processed with the ARES™ Insight software to transform the raw signals and derive and assess changes in oxygen saturation (SpO2), pulse rate, head movement, head position, snoring sounds, airflow, and EEG or respiratory effort. The red and IR signals are used to calculate the SpO2 and pulse rate. The actigraphy signals are transformed to obtain head movement and head position. A clinician can convert an auto-detected obstructive apnea to a central apnea based on visual inspection of the waveforms. ARES™ Screener can predict pre-test probability of obstructive sleep apnea (OSA). The ARES™ can also assist the physician to identify patients who will likely have a successful OSA treatment outcome, including CPAP and oral appliance therapies. ARES™ can help identify patients who would benefit from a laboratory PAP titration.

The provided FDA 510(k) summary for the Apnea Risk Evaluation System (ARES™), Model 610 (K112514) primarily focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study proving the device meets specific acceptance criteria in a standalone performance evaluation. The changes in the modified device are related to software platform, improved filtering of the SpO2 signal, and new claims in the report messages.

Here's an attempt to extract and organize the information based on your request, with significant caveats that much of the requested detail is not explicitly provided in the document for the performance of the modified device in the way you've outlined:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are primarily for the SpO2 accuracy after the filtering changes. The document explicitly states that the accuracy in all ranges is less than 3.5% as recommended by draft FDA guidance.

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The Apnea Risk Evaluation System (ARES™), Model 610 is indicated for use in the diagnostic evaluation by a physician of adult patients with possible sleep apnea. The ARES™ can record and score respiratory events during sleep (e.g., apneas, hypopneas, mixed apneas and flow limiting events). The device is designed for prescription use in home diagnosis of adults with possible sleep-related breathing disorders.

The Apnea Risk Evaluation System (ARES™) includes a device called a Unicorder which records oxygen saturation, pulse rate, snoring level, head movement and head position, and airflow. Additionally, a physiological signal from the forehead used to stage sleep or respiratory effort signal obtained from an optional piezo respiratory effort belt can be acquired. The battery powered Unicorder provides sufficient capacity to record two nights of data. The device monitors signal quality during acquisition and notifies the user via voice messages when adjustments are required. A standard USB cable connects the Unicorder to a USB port on a host computer when patient data is to be uploaded or downloaded. The USB cable provides power to the Unicorder during recharging from the host computer or from a USB wall charger. The Unicorder cannot record nor can it be worn by the patient when connected to the host computer or the wall charger. Software controls the uploading and downloading of data to the Unicorder, processes the sleep study data and generates a sleep study report. The ARES™ can auto-detect positional and non-positional obstructive and mixed apneas and hypopneas similarly to polysomnography. It can detect sleep/wake and REM and non-REM. After the sleep study has been completed, data is transferred off the Unicorder is prepared for the next study. The downloaded sleep study record is then processed with the ARES™ Insight software to transform the raw signals and derive and assess changes in oxygen saturation (SpQ2), pulse rate, head movement, head position, snoring sounds, airflow, and EEG or respiratory effort. The red and IR signals are used to calculate the SpO- and pulse rate: The actigraphy signals are transformed to obtain head movement and head position. A clinician can convert an auto-detected obstructive apnea to a central apnea based on visual inspection of the waveforms. ARES™ Screener can predict pre-test probability of obstructive sleep apnea (OSA). The ARES™ can assist the physician to identify patients who will likely have a successful OSA treatment outcome, including CPAP and oral appliance therapies. ARES™ can also help identify patients who would benefit from a laboratory PAP titration.

Here's an analysis of the provided text regarding the ARES device's acceptance criteria and studies:

1. Table of Acceptance Criteria and Reported Device Performance:

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

The document mentions "Two clinical studies were conducted," but does not explicitly state the sample size for either clinical study.

The data provenance is not explicitly stated (e.g., country of origin, retrospective or prospective). However, the description of clinical studies implies prospective data collection for the purpose of validating the device.

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

The document does not specify the number of experts used to establish ground truth for the clinical studies.

It notes that the "signals acquired... would allow a physician, trained in sleep medicine to interpret the signals." This implies that the interpretation of signals for the "ground truth" or comparison in the equivalence study would be done by physicians trained in sleep medicine, but their specific qualifications (e.g., years of experience) are not provided.

4. Adjudication Method for the Test Set:

The document does not describe any specific adjudication method (e.g., 2+1, 3+1). For the first clinical study, it states the ARES chest signal and Somté chest signal were "equivalent in their response," implying a direct comparison rather than a consensus among multiple human readers.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size:

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done as described in this 510(k) summary. The clinical studies focused on signal equivalence and interpretability, not on the improvement of human readers with or without AI assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

The document mentions that the ARES™ can "auto-detect positional and non-positional obstructive and mixed apneas and hypopneas similarly to polysomnography" and that "A clinician can convert an auto-detected obstructive apnea to a central apnea based on visual inspection of the waveforms."

However, beyond these functional descriptions, the reported clinical studies primarily focus on signal acquisition, equivalence, and interpretability by a physician, rather than a standalone performance evaluation of the scoring algorithm's accuracy against a gold standard without human intervention. The statement "at least 95% of signals from the ARES effort belt recorded during overnight studies are interpretable and behave consistently based on the airflow signal" suggests a focus on the quality of the raw data for human interpretation, not the autonomous performance of an algorithm.

7. The Type of Ground Truth Used:

For the first clinical study (signal equivalence), the "ground truth" appears to be the signals simultaneously acquired using the predicate device, Compumedics Somté System. This functions as a form of comparative ground truth against an established device.

For the second clinical study (usability/interpretability), the ground truth for "interpretable and behave consistently" is implied to be expert visual assessment based on consistency with airflow signals by a physician trained in sleep medicine. Additionally, subject feedback from a Usability survey served as a form of ground truth for ease of use.

8. The Sample Size for the Training Set:

The document does not provide any information regarding a training set or its sample size. This 510(k) summary focuses on the validation of modifications to an existing device (adding a respiratory effort belt) and demonstrating substantial equivalence, rather than the initial development and training of the core algorithmic components for apnea detection.

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

Since no training set information is provided, the method for establishing its ground truth is also not described.

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The Apnea Risk Evaluation System (ARES™), Model 610 is indicated for use in the diagnostic evaluation by a physician of adult patients with possible sleep apnea. The ARES™ can record and score respiratory events during sleep (e.g., apneas, hypopneas, mixed apneas and flow limiting events). The device is designed for prescription use in home diagnosis of adults with possible sleep-related breathing disorders.

The Apnea Risk Evaluation System (ARES™) includes a device called a Unicorder which records oxygen saturation, pulse rate, snoring level, head movement and head position, airflow, and a physiological signal from the forehead used to stage sleep. The battery powered Unicorder provides sufficient capacity to record two nights of data. The device monitors signal quality during acquisition and notifies the user via voice messages when adjustments are required. A standard USB cable connects the Unicorder to a USB port on a host computer when patient data is to be uploaded or downloaded. The USB cable provides power to the Unicorder during recharging from the host computer or from a USB wall charger. The Unicorder cannot record nor can it be worn by the patient when connected to the host computer or the wall charger. Software controls the uploading and downloading of data to the Unicorder, processes the sleep study data and generates a sleep study report. The ARES can auto-detect positional and non-positional obstructive and mixed apneas and hypopneas similarly to polysomnography. It can detect sleep/wake and REM and non-REM. After the sleep study has been completed, data is transferred off the Unicorder is prepared for the next study. The downloaded sleep study record is then processed with the ARES™ Insight software to transform the raw signals and derive and assess changes in oxygen saturation (SpO2), pulse rate, head movement, head position, snoring sounds, airflow, and EEG. The red and IR signals are used to calculate the SpO2 and pulse rate. The actigraphy signals are transformed to obtain head movement and head position. ARES™ Screener can predict pre-test probability of obstructive sleep apnea (OSA). The ARES can assist the physician to identify patients who will likely have a successful OSA treatment outcome, including CPAP and oral appliance therapies. ARES™ can also help identify patients who would benefit from a laboratory PAP titration.

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

2. Sample size used for the test set and the data provenance

• Sample Size for Clinical Tests: 14 subjects.
• Number of Overnight Sleep Studies: 20.
• Data Provenance: Not explicitly stated, but the study was conducted to compare the new model to the predicate, implying it was likely a prospective study undertaken specifically for this submission. The country of origin is not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

The document does not specify the number of experts used or their qualifications for establishing ground truth in the clinical study. The study focused on comparing the performance of the stabilizing strap and enclosure pad of the ARES™ Model 610 to the ARES™ Model 600 regarding signal quality, comfort, and pressure. It appears to be a technical comparison rather than a diagnostic accuracy study requiring expert-established ground truth for medical outcomes.

4. Adjudication method for the test set

Not applicable. The clinical study was a direct comparison of physical components (stabilizing strap and enclosure pad) between two device models, focusing on comfort and pressure applied, rather than a diagnostic accuracy study that would typically involve adjudication of diagnostic outcomes.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The submission is for a modified version of an existing device (ARES™ Model 610 vs. ARES™ Model 600) and focused on demonstrating equivalent performance of physical components and compliance with safety and performance standards, not on AI assistance for human readers.

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

The document does not explicitly state that a standalone (algorithm only) performance study was conducted. The main clinical study focused on the physical components of the device (stabilizing strap and enclosure pad) and ensuring equivalent signal quality and comfort compared to the predicate device. The ARES™ Insight software processes sleep study data and auto-detects events, which implies an algorithm, but a standalone performance study with metrics like sensitivity/specificity for these detections (separate from the physical modifications) is not detailed in this submission.

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

For the clinical study described, the "ground truth" was related to the equivalent signal quality, comfort, and pressure applied to the forehead sensor as compared to the predicate device. This was likely assessed via subjective feedback (comfort) and objective measurements of signal quality, with the predicate device (Model 600) serving as the reference for equivalence. It wasn't about diagnostic accuracy for sleep apnea via expert consensus, pathology, or outcomes data in this specific submission.

8. The sample size for the training set

The document does not mention the sample size for a training set. This submission is for a modification of an existing device, and the testing described is primarily for demonstrating equivalence and compliance with standards for the modified hardware, not for developing or training a new algorithm.

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

Not applicable, as no training set or its ground truth establishment is described in this submission.

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The Apnea Risk Evaluation System (ARES™) is indicated for use in the diagnostic evaluation by a physician of adult patients with possible sleep apnea. The ARES can record and score respiratory events during sleep (e.g., apneas, hypopneas, mixed apneas and flow limiting events). The device is designed for prescription use in home diagnosis of adults with possible sleep-related breathing disorders.

The Apnea Risk Evaluation System (ARES) includes a device called a Unicorder which records oxygen saturation, pulse rate, snoring level, head movement and head position, airflow, respiratory effort, and a physiological signal from the forehead used to stage sleep. The battery-powered Unicorder provides sufficient capacity to record for 18-hours of continuous use. The device monitors signal quality during acquisition and notifies the user via voice messages when adjustments are required. A standard USB cable connects the Unicorder to a USB port on a host computer when patient data is to be uploaded or downloaded. The USB cable provides power to the Unicorder during recharging from the host computer or from a USB wall charger. The Unicorder cannot record nor can it be worn by the patient when connected to the host computer or the wall charger. Software controls the uploading and downloading of data to the Unicorder, processes the sleep study data and generates a sleep study report. Algorithms are applied to the physiological data to automatically detect apneas and hypopneas, distinguish sleep from awake and rapid eye movement sleep from non-rapid eye movement sleep. A full disclosure recording is provided, allowing a clinician to edit any of the events detection algorithms. The software includes the capability to assign a pre-test probability of a patient having OSA based on questionnaire responses. Six disposable components must be replaced and the forehead sensor must be cleaned before reuse.

The provided text describes the Apnea Risk Evaluation System (ARES) Model 600. It details various performance tests conducted to establish substantial equivalence to predicate devices, but it does not provide specific acceptance criteria or an explicit study that quantifies device performance against those criteria in a table format with numerical results.

However, based on the text, we can infer some aspects related to acceptance criteria and the nature of the validation.

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not present a table of acceptance criteria with corresponding performance metrics. Instead, it indicates that "Design verification and validation tests were performed on the ARES Unicorder Model 600 to ensure it meets the specified product requirements," and states that the accuracy of automated detection was "assessed and compared to the predicate device." This phrasing suggests a comparative approach to acceptance rather than pre-defined numerical thresholds.

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

The document does not explicitly state the sample size used for the test set for performance evaluation of automated detection. It mentions "laboratory PSG" as the gold standard, suggesting the data originated from sleep lab studies. The provenance (country of origin) is not specified, but the submission is to the US FDA, so it's likely US data. The data appears to be retrospective, as it's used for comparison against technician scoring.

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

The document states that "The technician scoring was considered the gold-standard for purposes of assessing accuracy."

• Number of experts: Not specified (implied to be one or more technicians per PSG).
• Qualifications of experts: "Technician scoring" implies trained polysomnography technicians. No specific experience level (e.g., "10 years of experience") is mentioned.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method like 2+1 or 3+1. The ground truth for automated detection was based on "technician scoring," which implies a single-reader assessment per PSG record, rather than a consensus or adjudicated reading.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study is not described. The documentation focuses on the device's standalone performance compared to technician scoring and other predicate devices, not on human readers' improvement with AI assistance.

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

Yes, a standalone performance assessment was done. The document states: "The accuracy of the automated detection of awake and sleep and REM vs. non-REM compared to technician scoring of laboratory PSG was assessed and compared to the predicate device." This directly refers to the algorithm's performance without human intervention.

7. The Type of Ground Truth Used

The ground truth used for assessing the automated detection of sleep stages (awake, sleep, REM vs. non-REM) was expert consensus / technician scoring (specifically stated as "technician scoring of laboratory PSG was considered the gold-standard").

8. The Sample Size for the Training Set

The document does not provide any information regarding the sample size of a training set for the algorithm. It focuses on the validation of the ARES Model 600, not its development.

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

Since no information regarding a training set is provided, there is also no information on how its ground truth was established.

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