Search Results

The SOMNOscreen® plus is a non-life-supporting portable physiological signal recording device intended to be used for testing adults and children (age 2 to 12 years)/adolescents (age 12 and above) suspected of having sheep related breathing disorders.

The SOMNOscreen® plus is a modular system with the following components available .: Thermistor, Nasal Canula, Effort belts with respective sensor, SpO2-Sensor, Microphone, Headbox (EXG Channels), external body position sensor, shoulder belts, activity sensor, EMG-PLM sensor, pressure sensor, gold cup electrodes and LoFlo CO2-module (optional). The SOMNOscreen® plus device provides 13 AC channels (10 Referential and 3 Differential), 11 Respiratory and AUX Channels, and 8 Internal Channels.

The SOMNOscreen plus is available in 4 different configurations.

• . Cardio-RESP
• Home Sleep
• PSG .
• . EEG 32

The purpose of this 510(k) submission is to expand the patient population to include children and adolescents. For the use in pediatric patients the DOMINO software only allows manual (visual) scoring by qualified RPSG. There is no automated analysis or highlighting available for pediatric patients.

The provided text describes a medical device, SOMNOscreen plus, and its FDA 510(k) clearance. The submission focuses on expanding the patient population to include children and adolescents, emphasizing that for this new population, only manual scoring by qualified personnel is allowed, with no automated analysis.

Here's an analysis of the acceptance criteria and study information, based only on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of "acceptance criteria" against "reported device performance" in a quantitative manner for specific diagnostic metrics (e.g., accuracy, sensitivity, specificity for detecting sleep-related breathing disorders). Instead, it discusses compliance with general safety and performance standards for electroencephalographs and polysomnographs.

However, we can infer some performance aspects based on the technical specifications and comparisons:

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

The document explicitly states: "Clinical data were not relied upon for a determination of substantial equivalence." This means no specific clinical test set was used to evaluate the device's diagnostic performance for sleep-related breathing disorders in humans for this submission. The evaluation focused on technical and safety equivalence to predicate devices and adherence to standards.

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

As no clinical data was relied upon, there was no test set requiring expert-established ground truth. The "ground truth" implicitly referred to here is compliance with technical standards and AASM recommendations for polysomnography signal acquisition. For pediatric applications, the text mentions "manual (visual) scoring by qualified RPSG" (Registered Polysomnographic Technologist), implying that human experts are crucial for interpreting the device's output, especially in the expanded pediatric population. However, this is about the use of the device, not the validation of its performance in a clinical study for this submission.

4. Adjudication Method for the Test Set

Not applicable, as no clinical test set was used or described.

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

No, an MRMC comparative effectiveness study was not done, as stated by "Clinical data were not relied upon for a determination of substantial equivalence." The document indicates that for pediatric populations, the software "only allows manual (visual) scoring by qualified RPSG. There is no automated analysis or highlighting available for pediatric patients." This suggests that any comparative effectiveness of human readers with AI assistance versus without AI assistance is not relevant to this specific clearance for the pediatric population, as AI assistance for scoring is explicitly not provided for them.

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

No standalone algorithm performance study was described. In fact, for the new pediatric population, the device explicitly does not offer automated analysis or highlighting, emphasizing human interpretation.

7. The Type of Ground Truth Used

For the purposes of this 510(k) submission, the "ground truth" used was primarily compliance with recognized standards (IEC 60601-1, IEC 60601-1-2, ISO 14971, ISO 10993, IEC 62366-1) and technical specifications, as well as adherence to minimum performance specifications recommended by the American Academy of Sleep Medicine (AASM) for signal types. No clinical ground truth (like pathology, expert consensus on diagnostic outcomes, or long-term outcomes data) was used in a specific clinical study for this submission.

8. The Sample Size for the Training Set

No training set information is provided, as the submission did not rely on clinical data or automated algorithms that would require a training set for this clearance. The "training" here refers to the design and verification process of the device itself against engineering and safety requirements.

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

Not applicable, as no training set for an AI algorithm was described. The device's "training" in an engineering sense involved verification and validation against pre-specified requirement specifications and relevant performance standards, ensuring basic safety and essential performance.

Ask a specific question about this device

The SOMNOscreen EEG10-20 is a non-life-supporting portable physiological signal recording device intended to be used for testing adult patients suspected of having sleep-related breathing disorders.

The SOMNOscreen EEG10-20 is a portable physiological signal recording system intended to be used to record, display, monitor, print and store biophysical events to aid in the diagnosis of neurologic and sleep disorders. The device is intended to be prescribed for use by a physician in the office, sleep laboratory or patient's home.

The SOMNOscreen EEG10-20, a portable physiological signal recording system, did not undergo a study with acceptance criteria in the provided documentation. Instead, its substantial equivalence to a predicate device, the Somnomedics SOMNOscreen (K060708), was established through performance testing and a comparison of technological characteristics.

Here's an analysis 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: Not applicable. The submission describes performance testing for device specifications and compliance with standards, not a clinical study with a patient test set.
• Data Provenance: Not applicable. The testing was described as "performance testing" and "testing to the international standards," which implies internal device validation rather than clinical data.

3. Number of Experts Used to Establish Ground Truth and Qualifications

• Not applicable. This information is not provided because no clinical (human subject) test set requiring expert adjudication was conducted for this 510(k) submission.

4. Adjudication Method

• Not applicable. No clinical test set requiring ground truth establishment through expert adjudication was mentioned.

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

• No. An MRMC study was not described in the provided text. The device is a physiological signal recording system, and the submission focuses on its technical performance and equivalence to a predicate, not on human reader interpretation or AI assistance.

6. Standalone Performance Study

• Yes, effectively. The performance testing described ("Performance testing was conducted to confirm compliance to device specifications; all functions were verified to operate as designed. Measured parameters met required ranges and accuracies.") can be considered a standalone assessment of the device's functional performance, albeit at a technical level rather than a clinical performance (e.g., diagnostic accuracy) level. The submission is for a recording device, not an analytical algorithm.

7. Type of Ground Truth Used

• Technical specifications/Compliance Standards. The "ground truth" for the performance testing was derived from the device's technical specifications and the requirements of international standards for electrical safety and electromagnetic compatibility. This is not clinical ground truth like pathology or expert consensus.

8. Sample Size for the Training Set

• Not applicable. This device is a physiological signal recording system, not an AI/ML algorithm that requires a training set of data for development.

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

• Not applicable. As the device is not an AI/ML algorithm, it does not have a training set.

Ask a specific question about this device

The SOMNOscreen is a non-life-supporting portable physiological signal recording device intended to be used for testing adult patients suspected of having sleep-related breathing disorders.

The SOMNOscreen is indicated for use in the recording, displaying, monitoring, and storage of biophysical parameters for the purpose of assisting in the diagnosis of Neurological and Sleep Disorders.

The SOMNOscreen is a portable physiological signal recording system intended to be used to record, display, monitor, print and store biophysical events to aid in the diagnosis of neurologic and sleep disorders. The device is intended to be prescribed for use by a physician in the office, sleep laboratory or patient's home.

This device is NOT designed to be used in a Life Support situation. This device is not designed for use on patients with cardiac pacemakers.

The system provides up to 28 channels for data acquisition; 10 AC Channels, 8 Referential and 2 Differential, 11 Respiratory and AUX Channels, 7 Internal Channels (SPO2, Pulse Rate, Plethysmogram, Body Position, Light, Patient Marker, Thorax/Abdominal Respiratory Effort)

The SOMNOscreen is available in 6 different configurations. All configurations include a Compact Flash Card and Reader, Li ION Batteries, (2000mAh) with 1 x Battery Charger, a Carry Bag for housing the SOMNOscreen and Sensors, Instruction Manuals and the DOMINO software for Initialization, Data Transfer and Analysis.

Here's a summary of the acceptance criteria and study details for the Somnomedics SOMNOscreen based on the provided 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly state quantitative "acceptance criteria" for the SOMNOscreen's clinical performance. Instead, it states that the device's clinical performance was found to be "equivalent to the predicate Sleepscreen and the manual scored Polysomnography." Therefore, the reported device performance is its equivalence to these established methods.

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

• Sample Size: 25 patients
• Data Provenance: Not explicitly stated, but the applicant (Somnomedics GmbH & Co.KG) is based in Kist, Germany. It is common for clinical studies associated with German manufacturers to originate from Germany or other European countries; however, this is not confirmed in the document. The study evaluates the device "when used as intended in the targeted patient population," implying prospective data collection for this validation.

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

The document states that the comparison was made against "manual scored Polysomnography." This heavily implies that sleep experts (e.g., polysomnography technologists, sleep physicians) were involved in scoring the PSG data, which would serve as the ground truth. However:

• Number of experts: Not specified.
• Qualifications of experts: Not specified, but generally, manual PSG scoring is performed by registered polysomnographic technologists (RPSGTs) and interpreted by board-certified sleep physicians.

4. Adjudication Method for the Test Set

The document does not describe an explicit adjudication method (e.g., 2+1, 3+1). The "manual scored Polysomnography" itself is considered the reference standard, and deviations from this standard for the SOMNOscreen's output would be assessed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No. The study described compares the SOMNOscreen to a predicate device and manual PSG. It does not appear to be an MRMC study designed to evaluate the improvement in human reader performance with or without AI assistance. The SOMNOscreen, as described, is a physiological signal recording system, not an AI-assisted diagnostic tool in the sense of providing automated interpretations that would then be reviewed by human readers.

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

Yes, in essence. The study evaluates the "clinical performance of the SOMNOscreen" itself against predicate devices and manual PSG. While a human would still interpret the output from the SOMNOscreen, the study aims to validate the device's ability to record, display, monitor, print, and store biophysical events reliably, standalone from a human "AI assistance" workflow. The device does not appear to have an AI component for automated interpretation that would undergo a separate standalone performance evaluation.

7. The Type of Ground Truth Used

The ground truth used was manual scored Polysomnography (PSG), which is typically considered the gold standard for sleep disorder diagnosis.

8. The Sample Size for the Training Set

The document does not mention a training set or any details about an algorithm that would require one. The SOMNOscreen is described as a physiological signal recording system, implying it captures raw physiological data rather than employing a machine learning algorithm that would need training.

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

Since no training set is mentioned and the device appears to be a data acquisition system rather than an AI/ML-based interpretive algorithm, this information is not applicable and not provided in the document.

Ask a specific question about this device