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The Silent Night I is indicated for use in the diagnostic evaluation of adults with possible Obstructive Sleep Apnea. It is intended to record a patient's respiratory pattern. The device is designed for use in home screening of adults with possible sleep disorders.

The Silent Night I (SNI) consists of a metal box measuring approximately 23 centimeters wide by 17 centimeters deep by 7.5 centimeters high. The device is portable, line-powered and weighs approximately three pounds. The box contains the operational components of the device and has two receptacle connectors: one for input power and another for the sensing microphone. This microphone is attached to the SNI by means of an eight-foot flexible cable and connector. Another microphone is built into the rear of the box and senses room ambient noise. A POWER switch is located on the back of the unit. A switch enabling the user to PAUSE and RESUME device operation is located on the side of the unit.

The device operates as follows: the sound field (breathing sounds + room ambient noise) is sensed by the two microphones and sent to the controller, which extracts breathing sounds from all sounds received. These signals are then sent through bandpass filters and the amplitude characteristics of the signals in the frequency realm are analyzed. The signals are then processed by the pattern recognizer, which differentiates between types of sounds and classifies them as regular snoring or breathing, hypopnea, or apnea. These classified events are logged cumulatively and shown on a liquid crystal display as Disordered Breathing Events (DBE) on the front control panel of the device.

Here's an analysis of the acceptance criteria and study information for the Silent Night I device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The document does not explicitly state the specific number of patients included in the clinical study. It only mentions "Patients were subjected to sleep laboratory evaluation."
• Data Provenance: The document does not specify the country of origin. The study appears to be prospective as it involved patients being simultaneously evaluated by both the Silent Night I and a standard polysomnograph.

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

• The document does not explicitly mention the number of experts or their qualifications for establishing ground truth.
• The "ground truth" was established by a standard polysomnograph (the Grass Model 7P511 High Performance AC Amplifier), which is considered a benchmark device in sleep studies. While experts would interpret polysomnography data, the document doesn't detail this process for the ground truth establishment itself.

4. Adjudication Method for the Test Set

• The document does not describe a formal adjudication method. The comparison was statistical, correlating the measurements between the Silent Night I and the Grass polysomnograph. It doesn't mention multiple readers independently assessing data and then having an adjudication process.

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 explicitly described.
• The study focuses on the device's standalone performance compared to a gold standard, not on how it assists human readers. The device performs the analysis and displays the results directly ("These classified events are logged cumulatively and shown on a liquid crystal display"). Therefore, there is no mention of effect size related to human reader improvement with AI assistance.

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

• Yes, a standalone study was done. The Silent Night I is described as a device that "extracts breathing sounds from all sounds received," "processes... by the pattern recognizer," and "differentiates between types of sounds and classifies them as regular snoring or breathing, hypopnea, or apnea." The classified events are then "logged cumulatively and shown on a liquid crystal display." This indicates the device autonomously performs the detection and classification. The clinical study compares these device-generated results directly to the polysomnograph.

7. The Type of Ground Truth Used

• The ground truth used was data from a standard polysomnograph (the Grass Model 7P511 High Performance AC Amplifier). This is considered a clinical gold standard for measuring respiratory events during sleep.

8. The Sample Size for the Training Set

• The document does not specify a sample size for a training set. This device predates widespread explicit mention of "training sets" in regulatory submissions for AI/ML devices in the way we understand them today. The device uses "pattern recognizer" technology, implying some form of internal logic or learning, but the details of its development data are not provided.

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

• As the document does not specify a training set sample size, it also does not describe how the ground truth for any potential training set was established.

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