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The NightOwl is a wearable device intended for use in the recording, analysis, displaying, exporting, and storage of biophysical parameters to aid in the evaluation of sleep-related breathing disorders of adult patients suspected of sleep apnea. The device is intended for the clinical and home setting use under the direction of a Healthcare Professional (HCP).

The NightOwl comprises a sensor that is worn on the fingertip (the "NightOwl Sensor") over-night whilst the subject is sleeping and cloud-based analysis software (the "NightOwl Software"). The NightOwl Sensor has a small biocompatible enclosure. The sensor has 2 LEDs, one in the red spectrum and the other in the infrared spectrum, and an accelerometer. The sensor is attached to the fingertip by single-use biocompatible adhesive tape, with the sensor window applied against the fingerprint area of the fingertip. The sensor measures the reflected red/infrared signals to record the photoplethysmograph (PPG) signal. The accelerometer is used to detect movement. The data recorded by the NightOwl Sensor can either be stored in on-board memory ("Offline" mode) or streamed via a Bluetooth link to an Ectosense app on a smartphone ("Streaming" mode). The NightOwl Software signal processing algorithms produce a number of sleep and sleep-disordered breathing related traces and parameters. The trace and parameter information are passed to a company-managed database for storage and access by the prescribing Health Care Professional in the Ectosense Dashboard.

Here's a breakdown of the acceptance criteria and study information for the NightOwl device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document focuses on the validation of the "Total REM Time" calculation, as this was the new feature introduced by the device modification. The acceptance criteria themselves are not explicitly stated as numerical thresholds (e.g., "correlation must be > X"). Instead, the performance metrics reported serve as the basis for demonstrating substantial equivalence. The implication is that the reported performance is acceptable for the device's intended use, particularly when compared to the established performance of the previously cleared device for Total Sleep Time.

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

• Sample Size: 71 patients
• Data Provenance: The study was conducted in a "US population," implying that the data was collected prospectively for this clinical validation.

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 or qualifications of experts used to establish the ground truth. It states that the NightOwl performance for Total REM Time determination was "compared to the gold standard polysomnography (PSG)." PSG is typically scored by trained polysomnographic technologists and/or sleep physicians, but the exact number and qualifications are not detailed here.

4. Adjudication Method for the Test Set

The document does not explicitly state an adjudication method (e.g., 2+1, 3+1). The comparison is made against the "gold standard polysomnography (PSG)," which implies that the PSG results were considered the definitive ground truth without a separate adjudication process for the test set scores of the device.

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 reported. This study focuses on the standalone performance of the device's algorithm for Total REM Time against the PSG gold standard. There is no mention of human readers or AI assistance for human readers.

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

Yes, a standalone performance study was done. The "Performance of modified device (Subject)" table directly reports algorithm performance metrics (Root Mean Square Difference, Correlation, Bias, Limits of Agreement) when compared to the "gold standard polysomnography (PSG)." This indicates the algorithm's performance without human intervention in the scoring process.

7. The Type of Ground Truth Used

The type of ground truth used was Polysomnography (PSG), which is referred to as the "gold standard." PSG involves comprehensive physiological monitoring during sleep, typically including electroencephalography (EEG), electrooculography (EOG), electromyography (EMG), and respiratory parameters, among others, from which sleep stages (including REM) are scored by trained professionals.

8. The Sample Size for the Training Set

The document does not provide information regarding the sample size for the training set. The reported study focuses solely on the clinical validation of the modified device's performance for Total REM Time using a test set of 71 patients.

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

The document does not provide information on how the ground truth for any training set was established. It only details the ground truth used for the validation (test) set (PSG). It states that the "Total REM Time was validated using the identical method and protocol used to validate the TST supporting the previously cleared 510(k)," implying that similar PSG-based ground truth would have been used for any prior training as well, but no specifics are given.

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The NightOwl is a wearable device intended for use in the recording, analysis, displaying, exporting, and storage of biophysical parameters to aid in the evaluation of sleep-related breathing disorders of adult patients suspected of sleep apnea.

The device is intended for the clinical and home setting use under the direction of a Healthcare Professional (HCP).

The NightOwl is prescribed by a Health Care Professional for the patient to use in the home as a 'home sleep apnea test' (HSAT).

The NightOwl comprises a sensor that is worn on the fingertip (the "NightOwl Sensor") over-night whilst the subject is sleeping and cloud-based analysis software (the "NightOwl Software").

The NightOwl Sensor has a small biocompatible enclosure. The sensor has 2 LEDs, one in the red spectrum and the other in the infrared spectrum, and an accelerometer. The sensor is attached to the fingertip by single-use biocompatible adhesive tape, with the sensor window applied against the fingerprint area of the fingertip. The sensor measures the reflected red/infrared signals to record the photoplethysmograph (PPG) signal. The accelerometer is used to detect movement.

The data recorded by the NightOwl Sensor can either be stored in on-board memory ("Offline" mode) or streamed via a Bluetooth link to an Ectosense app on a smartphone ("Streaming" mode)

• if the data is stored on the device, the data is retrieved when the NightOwl sensor . is returned to the prescribing HCP and passed up to a cloud-based signal processing suite, the NightOwl Software.
• If the device is used in Streaming mode, the data is stored by the Ectosense app . on the smartphone during the recording. At the end of the recording, it is then passed directly up to the cloud-based signal processing suite.
• The NightOwl Software signal processing algorithms produce a number of sleep . and sleep-disordered breathing related traces and parameters. The trace and parameter information are passed to a company-managed database for storage and access by the prescribing Health Care Professional in the Ectosense Dashboard.

The provided text describes the 510(k) premarket notification for the NightOwl device, focusing on a modification that includes a new algorithm tuning (1B rule) for calculating the probable Apnea-Hypopnea Index (pAHI). The document outlines the device's technical characteristics, intended use, and performance data from a clinical study comparing the modified device's 1B rule performance to the predicate device's 1A rule performance against polysomnography (PSG).

Here's an analysis of the acceptance criteria and the study proving the device meets those criteria, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly defined by the performance metrics reported in the "Clinical Study" section, comparing the modified device's 1B rule performance to the predicate device's 1A rule performance. The goal is to demonstrate substantial equivalence, which implies that the 1B rule performance is comparable to or better than the 1A rule performance, and both are clinically acceptable against the gold standard.

Note: The document states that the new 1B rule tuning "does not alter the device's intended use and does not introduce any change to the safety and effectiveness of the originally cleared device (predicate device)." The acceptance criteria are therefore implicitly met if the performance characteristics of the 1B algorithm are demonstrated to be clinically acceptable and substantially equivalent to the already cleared 1A algorithm, which the data suggests.

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

The document states, "The clinical validation of the NightOwl performance using 1B rule was compared to the gold standard polysomnography (PSG) in the US population."

• Sample Size: The document does not explicitly state the sample size used for the clinical validation test set.
• Data Provenance: The data provenance is from the US population. The study type is retrospective, as it describes a "clinical validation" comparing the device's output against established PSG data.

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

The document does not provide information on the number or qualifications of experts used to establish the ground truth (e.g., scoring of PSG studies). It only mentions that the comparison was against "gold standard polysomnography (PSG)." Typically, PSG studies are scored by trained polysomnographic technologists and/or interpreted by sleep physicians.

4. Adjudication Method for the Test Set

The document does not specify any adjudication method (e.g., 2+1, 3+1, none) for the test set's ground truth.

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

An MRMC study was not conducted as described in the provided text. The study focuses on comparing the algorithmic performance of the device against a gold standard (PSG) and comparing the performance of the new algorithm (1B) to the predicate's algorithm (1A). There is no mention of human readers assisting with the AI or their improved performance with AI assistance.

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

Yes, a standalone performance study was conducted. The reported "Sensitivity," "Specificity," and "pAHI correlation" values are direct measurements of the NightOwl's algorithm (both 1A and 1B tunings) against the PSG gold standard without human intervention or interpretation as part of the performance metrics. The device provides "traces and parameters" to be accessed by a "Healthcare Professional (HCP)," implying the algorithm generates these outputs independently, for the HCP to use in evaluation.

7. Type of Ground Truth Used

The type of ground truth used was expert-scored polysomnography (PSG). PSG is widely considered the gold standard for diagnosing sleep-related breathing disorders. The reference to "AASM's '1A Rule'" and "AASM's '1B Rule'" for hypopnea scoring indicates that the PSG studies would have been scored according to these established clinical criteria.

8. Sample Size for the Training Set

The document does not explicitly state the sample size for the training set. The clinical study described appears to be a validation study for the pre-trained algorithm.

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

The document does not provide information on how the ground truth for any potential training set was established. It only discusses the ground truth for the clinical validation test set (PSG).

Ask a specific question about this device

The NightOwl is a wearable device intended for use in the recording, analysis, displaying, exporting, and storage of biophysical parameters to aid in the evaluation of sleep-related breathing disorders of adult patients suspected of sleep apnea.

The device is intended for the clinical and home setting use under the direction of a Healthcare Professional (HCP).

The Ectosense NightOwl comprises a sensor that is worn on the fingertip (the "NightOwl Sensor") and cloud-based analysis software (the "NightOwl Software").

The NightOwl Sensor is a small biocompatible enclosure with a sensor window made from PMMA (bottom part) and ABS (top part). The sensor has 2 LEDs, one in the red spectrum and the other in the infrared spectrum, and an accelerometer. The sensor is attached to the fingertip by single-use biocompatible adhesive tape, with the sensor window applied against the fingerprint area of the fingertip. The sensor measures the reflected red/infrared signals to record the photoplethysmograph (PPG) signal. The accelerometer is used to detect movement.

The data recorded by the NightOwl Sensor can either be stored in on-board memory ("Offline" mode) or streamed via a Bluetooth link to an Ectosense app on a smartphone ("Streaming" mode).

If the data is stored on the device, the data is retrieved when the NightOwl sensor is returned to the prescribing HCP and passed up to a cloud-based signal processing suite, the NightOwl Software.
If the device is used in Streaming mode, the data is stored by the Ectosense app on the smartphone during the recording. At the end of the recording, it is then passed directly up to the cloud-based signal processing suite.
The NightOwl Software signal processing algorithms produce a number of sleep and sleep-disordered breathing related traces and parameters. The trace and parameter information are passed to a company-managed database for storage and access by the prescribing Health Care Professional in the Ectosense Dashboard.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly present acceptance criteria in a formal table with pass/fail thresholds. Instead, it describes various tests and their outcomes. The closest information related to "acceptance criteria" and "reported device performance" for the primary function (pAHI accuracy) is derived from the clinical study results.

Derived Acceptance Criteria & Reported Performance for pAHI Accuracy:

Other Performance Data (No explicit criteria given, but compliance is stated):

• Biocompatibility: Passed tests (Cytotoxicity, Sensitization, Irritation) in accordance with ISO 10993-1.
• Electrical Safety & EMC: Complied with IEC60601-1:2012 and IEC60601-1-2:2014, including bench tests for close-proximity RF emitters.
• Software Verification & Validation: Documentation provided as per FDA guidance, considered "moderate" level of concern.
• SpO2 Accuracy: Within pass/fail criteria of ISO80601-2-61:2019 Clause 201.12.1.101.1.
• Pulse Rate RMS: 2.26 bpm for claimed range of 50 to 118 bpm (within acceptable limits per ISO 80601-2-61:2019 Annex EE.2, implied acceptance).

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

The text mentions "three clinical studies" and then details two "comparison to PSG Sleep Lab Results" studies, one in Belgium and one in the United States, followed by a "pooled analysis." It doesn't explicitly state the sample size for each individual study, nor the combined sample size.

• Data Provenance: Belgium and United States (sleep lab settings).
• Retrospective or Prospective: Not explicitly stated, but the description of "clinical trials" and "repeat study" suggests prospective data collection for validation.

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

The document refers to the "gold standard analysis of the polysomnography (PSG)" and "AHI (Expert PSG)" in the regression formula. However, it does not specify:

• The number of experts involved in establishing the PSG ground truth.
• The qualifications of these experts (e.g., board-certified sleep physicians, polysomnography technologists).

4. Adjudication Method for the Test Set

The document states that the ground truth was the "gold standard analysis of the polysomnography (PSG)." It does not mention any specific adjudication method (e.g., 2+1, 3+1 consensus) for establishing this PSG ground truth. It implies that the standard clinical PSG analysis was used as the ground truth.

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 where human readers' performance with and without AI assistance was evaluated. The studies focused on the standalone performance of the NightOwl device (its pAHI accuracy compared to PSG).

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

Yes, a standalone study was done. The clinical studies described focused on validating the NightOwl device's accuracy in calculating pAHI against the "gold standard" PSG. This means the device's algorithm output was directly compared to the PSG, indicating a standalone performance evaluation.

7. The Type of Ground Truth Used

The primary ground truth used for the pAHI accuracy validation was:

• Polysomnography (PSG) Analysis: Referred to as the "gold standard" and "Expert PSG." This typically involves detailed scoring of sleep stages, respiratory events (apneas, hypopneas), and other physiological parameters by trained personnel following established scoring rules.

8. The Sample Size for the Training Set

The document does not provide any information about the sample size used for the training set of the NightOwl's algorithms. It only discusses the clinical validation studies (test sets).

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

Since the document does not mention the training set, it does not describe how the ground truth for any training set was established. The clinical studies described are clearly for validation/testing purposes.

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