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The Lunoa System is indicated for prescription use for the treatments with positional obstructive sleep apnea with a non-supine apnea-hypopnea index

The Lunoa System is a rechargeable battery-operated medical device, worn around the chest in an elasticized chest strap (Figure 1), intended to keep patients with positional obstructive sleep apnea (POSA) from sleeping in the supine position. The System consists of a sensor device, chest strap, docking station, power adapter, travel case, and portal.

The Lunoa System is a medical device for treating positional obstructive sleep apnea (POSA). The acceptance criteria for the device were implicitly established through the clinical studies conducted to demonstrate its safety and effectiveness. The summarized results from these studies serve as the reported device performance.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are inferred from the demonstrated improvements in clinical endpoints through various studies. The reported device performance is taken directly from the "Results Summary" (Table 5-2) and the descriptions within the text.

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

The text describes eight investigator-initiated clinical studies. Each study contributed to the overall clinical evidence. There isn't a single "test set" described in the conventional sense of a distinct dataset used solely for final validation after development. Instead, the performance is demonstrated across these multiple clinical trials.

• Sample Sizes: The number of patients in each study varied:
  • Van Maanen et al. 2013: 31 patients
  • Van Maanen & De Vries 2014: 106 patients
  • Benoist et al. 2016: 33 patients
  • Eijsvogel et al. 2015: 21 TBT, 27 SPT
  • Dieltjens et al. 2015: 20 patients
  • Benoist & de Ruiter et al. 2016: 81 patients
  • Laub et al. 2016: 52 SPT, 49 non-treatment control
  • De Ruiter et al. 2017: 29 SPT, 29 MAD
• Data Provenance (Country of Origin):
  • Amsterdam, The Netherlands (multiple studies)
  • Enschede, The Netherlands
  • Edegem, Belgium
  • Glostrup, Denmark
• Retrospective or Prospective: All studies are described as prospective, with some being randomized, parallel, cohort studies, and others single-arm cohort studies.

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

The text does not explicitly state the number of experts used to establish ground truth or their specific qualifications for individual patient diagnoses or data interpretation within the clinical studies. However, the studies were conducted by named authors (researchers/clinicians) and published in peer-reviewed sleep and breathing journals, implying that clinical diagnoses and assessments (e.g., AHI determined by Polysomnography (PSG)) were performed by qualified medical professionals in sleep medicine.

4. Adjudication Method for the Test Set

The text does not explicitly describe an adjudication method (like 2+1, 3+1) for the data collected in the clinical studies. Clinical studies typically involve standard diagnostic procedures (like PSG) which are interpreted by trained staff, but specific adjudication processes for individual case interpretations are not detailed in this summary.

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 of human readers with and without AI assistance was not conducted. The Lunoa System itself is a therapeutic device, not an AI diagnostic tool primarily interpreted by human readers. The studies compared the Lunoa System (or its previous version, SPT v1.1) against other treatments or control groups.

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

The Lunoa System is a standalone device in the context of its therapeutic function. It independently detects sleep position and provides vibro-tactile feedback. The "algorithm" in this case refers to the device's inherent logic for sensing position and initiating vibration. Its performance was tested as a standalone therapy, without a human actively intervening based on its real-time output (beyond initially setting it up and monitoring compliance). The clinical studies evaluated its effectiveness directly as a therapeutic intervention.

7. The Type of Ground Truth Used

The primary ground truth for evaluating the effectiveness of the Lunoa System was Polysomnography (PSG) data. PSG is considered the gold standard for diagnosing sleep disorders, including obstructive sleep apnea. The key metrics derived from PSG, such as Apnea-Hypopnea Index (AHI) and percentage of supine sleeping time, were used as objective measures of treatment efficacy. Subjective ground truths, such as Epworth Sleepiness Scale (ESS) and Functional Outcomes of Sleep Questionnaire (FOSQ), were also used to assess patient-reported outcomes.

8. The Sample Size for the Training Set

The text does not mention a distinct "training set" for an algorithm in the machine learning sense. The Lunoa System appears to rely on established principles of accelerometry for position detection and vibro-tactile feedback to deter supine sleep. Its development would likely involve engineering validation and perhaps iterative testing, but not necessarily a "training set" as understood for complex AI models in diagnostic imaging. The clinical studies evaluated the final device's performance, not the training of an underlying AI model.

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

As no explicit "training set" for an AI algorithm is mentioned, the method for establishing its ground truth is not applicable or described in this document. The device's fundamental function (position detection) relies on accelerometer technology, which is verified through engineering principles rather than a labeled training dataset in the AI context.

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The Night Shift is indicated for prescription use for the treatment of adult patients with positional obstructive sleep apnea with a non-supine apnea-hypopnea index

The Night Shift is worn around the neck to reduce the amount of time the user sleeps in the supine position as a treatment for positional obstructive sleep apnea. Night Shift combines hardware and firmware to detect when the user attempts to sleep in the supine position and can initiate vibro-tactile feedback with increasing intensity until the user shifts to a non-supine position. The initiation of positional feedback from the Night Shift is turned on is programmable to allow the user to fall asleep (if they must) on their back. Each night the Night Shift is worn, it monitors sleep position (% time supine), behavioral sleep efficiency, and snoring levels (% time snoring > 40 and 50 dB) as well as the frequency, duration and intensity of the feedback (when applied). These data can be optionally transferred via the USB port to the Night Shift Web Portal where the user can generate a report to assess how well the positional feedback is working. A "trial" protocol can include one night with no feedback to establish a baseline and two nights with feedback to assess compliance/efficacy. Utilization information is saved on the device that allows reports to be generated that compares daily use by month and monthly averages for one year. The portal also allows the device to be reformatted (to eliminate all previously recorded data) for a new user, adjust the feedback settings to a new user's personal preferences, and/or upgrade the firmware. For large healthcare organizations that limit internet access, desktop software is provided as an alternative to the portal.

Here's a breakdown of the acceptance criteria and the study details for the Advanced Brain Monitoring, Inc. Night Shift device, based on the provided text:

Acceptance Criteria and Reported Device Performance

Study Details for Clinical Tests:

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

   • Test Set Sample Size for Primary Effectiveness Endpoint: 27 patients with pre-treatment positional obstructive sleep apnea with a non-supine AHI 20).
   • Data Provenance: Not explicitly stated, but the study was a clinical study conducted to evaluate safety and efficacy, implying prospective data collection. The location (country of origin) is not mentioned.

2. 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 given text. Ground truth for sleep studies typically involves highly trained sleep technologists and physicians interpreting polysomnography (PSG) data. However, the document does not specify the number or qualifications for this particular study.

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

   • This information is not provided in the given text.

4. 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 study evaluated the device's performance in treating sleep apnea and recording sleep parameters, not how human readers improve with or without AI assistance in interpreting diagnostic data from the device. The Night Shift is a therapeutic and monitoring device, not an AI diagnostic interpretation tool.

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

   • Yes, the study primarily assessed the standalone performance of the Night Shift device. While it is a prescription device, its effectiveness was measured by its ability to reduce supine sleep and associated AHI, as well as its accuracy in measuring sleep parameters (position, TST, SE) independently. Human interaction is primarily for setup, compliance, and physician review of the generated reports, but the core therapeutic and monitoring function is standalone.

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

   • The ground truth for sleep parameters (AHI, supine time, TST, SE) appears to be Polysomnography (PSG), a gold standard for sleep disorder diagnosis. For the "Accuracy of Supine Position Measurement" endpoint, the ground truth was "video recordings plus chest sensor." For subjective measures (ESS, FOSQ), the ground truth was the participant's self-reported scores.

7. The sample size for the training set:

   • This information is not provided in the given text. The document describes a clinical validation study, not the development or training phase of an algorithm.

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

   • This information is not provided as the training set details are not mentioned.

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The ZZOMA Positional Sleeper is indicated for use and intended for professional use for the treatment of mild to moderate, predominantly positional obstructive sleep apnea (OSA) and to reduce or alleviate snoring.

The ZZOMA Positional Sleeper is intended for use by professional healthcare personnel trained in its use.

The ZZOMA Positional Sleeper is 12 x 5.5 x 4 inches in size and made of lightweight semi-rigid synthetic foam (Figures 1 and 2). It is contained in a backpack type material with an associated Velcro® elastic belt. The device is worn on the back, with the elastic belts brought around each side of the subject and secured anteriorly with the adjustable straps. The particular size and wedge-shaped design on both sides of this device keeps the subject comfortably positioned on their side, and prevents him/her from assuming the supine position. The ZZOMA has a firm inner core made of foam and the outer part of the device is covered in nylon, and the part that touches the subject's body is cotton covered with a coating of PVC dots that help keep the ZZOMA in place while you sleep.

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

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

The provided text does not explicitly state formal "acceptance criteria" for the device, and the direct performance metrics are relative to CPAP therapy. However, the primary objective of the study can be interpreted as the functional "acceptance criteria" for the device's effectiveness.

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

• Sample Size for Test Set: The text states, "There were 4 major findings in this study: 7/11 patients with positional OSA...". This indicates the study involved 11 patients with positional OSA.
• Data Provenance: The text does not specify the country of origin of the data. The study was conducted to examine the non-inferiority of the device, which typically implies a prospective clinical study.

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)

The text does not provide information on the number of experts used or their qualifications for establishing the ground truth. It mentions a "clinical study" but doesn't detail the methodology for expert
review or assessment of sleep parameters.

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

The text does not provide information on any adjudication method used for the test set.

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

This section is not applicable as the device is a physical positional sleeper for OSA, not an AI-assisted diagnostic or interpretive tool that would involve human "readers." The study compares the device's effectiveness to CPAP therapy, not to human interpretation with or without AI.

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

This section is not applicable. The ZZOMA Positional Sleeper is a physical device, not an algorithm. Its performance is measured directly by its physiological impact on the patient during sleep.

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

The ground truth or primary outcome measure for the study was the apnea-hypopnea index (AHI) and the patient's sleep position, which are objective physiological measurements obtained during sleep studies. This falls under outcomes data or physiological measurements.

8. The sample size for the training set

The text does not provide information on a "training set" as this is a physical device being evaluated in a clinical trial, not a machine learning algorithm.

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

This question is not applicable for the same reason as #8.

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1- MAY STOP OR DECREASE SNORING

2- MAY BE USED TO TREAT MILD OBSTRUCTIVE SLEEP APNEA

3- MAY IMPROVE THE QUALITY OF SLEEP

Not Found

This document is a marketing clearance letter from the FDA for the Sona Pillow, classifying it as an intraoral device for snoring and obstructive sleep apnea. It does not contain information about acceptance criteria or a study proving the device meets those criteria. Therefore, I cannot provide the requested information based on the input document.

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The Sniff Position Pillows are indicated for the following uses:

• 1.) May improve the quality of sleep
• 2.) May improve the symptoms of mild obstructive sleep apnea
• 3.) May improve snoring

Not Found

The provided document is a 510(k) premarket notification letter from the FDA regarding the classification of "Sniff Position Pillows/Popitz Pillows." It does not contain any information about acceptance criteria, device performance studies, sample sizes, expert qualifications, or ground truth establishment.

Therefore, I cannot provide the requested information. The letter primarily addresses the regulatory classification of the device.

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PillowPositive Cervical Pillow ("PillowPositive") is intended for the reduction of symptoms (apnea/hypopnea) associated with mild obstructive sleep apnea by maintaining an open upper airway during sleep.

PillowPositive Cervical Pillow ("PillowPositive") is indicated for the reduction of symptoms (apneas and hypopneas) associated with mild obstructive sleep apnea.

The pillow consists of a custom-fitted high resiliency urethane foundation, an overlying "memory foam" supporting the head and neck, a stretch terry-cloth cover, and removable foam inserts. The PillowPositive is comprised of a thin central area for supine sleeping and two thicker, sloped side panels with earwells for side sleeping.

The provided text describes the regulatory clearance for the "PillowPositive Cervical Pillow" and includes a summary of performance data from a pilot study and a pivotal study. However, it does not explicitly define acceptance criteria as a table with specific metrics or detail the study methodology with the granularity requested in the prompt.

Based on the provided text, here's an attempt to extract and infer the information:

1. Table of acceptance criteria and reported device performance:

The document states that the PillowPositive reduces the Respiratory Disturbance Index (RDI), which is defined as apneas and hypopneas, in subjects with mild obstructive sleep apnea. It also mentions "statistically significant reduction." However, it does not provide specific numerical thresholds or target values for this reduction to constitute "acceptance criteria."

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

• Test Set Sample Size: Not explicitly stated for either the pilot or pivotal study.
• Data Provenance: Not explicitly stated (e.g., country of origin). The studies appear to be prospective as they were conducted "to assess the PillowPositive's use."

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 studies assess the product's effect on RDI, which is typically measured by polysomnography, but the details of who interpreted these studies are not mentioned.

4. Adjudication method 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:

This is not applicable to this device. The PillowPositive Cervical Pillow is a physical medical device, not an AI or imaging diagnostic tool. Therefore, an MRMC study related to human reader performance with or without AI assistance is irrelevant.

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

This is not applicable as the PillowPositive is a physical medical device and not an algorithm.

7. The type of ground truth used:

The "ground truth" for evaluating the device's performance appears to be the Respiratory Disturbance Index (RDI), which is an objective physiological measure obtained through sleep studies (polysomnography).

8. The sample size for the training set:

There is no mention of a training set as this is a physical medical device undergoing clinical studies, not an AI algorithm.

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

This question is not applicable as there is no training set mentioned in the context of this device.

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