(182 days)
The Belun Sleep System BLS-100 is a wearable device intended to record, analyze, display, export, and store biophysical parameters to aid in evaluating moderate to severe sleep-related breathing disorders suspected of sleep apnea. The device is intended for use in clinical and home settings under the direction of a Healthcare Professional (HCP).
The Belun Sleep System BLS-100 comprises a sensor that is worn on the proximal phalanx of index finger (Belun Ring) over-night whilst the subject is sleeping and a stand-alone analysis software (Belun Sleep AI). The Belun Ring 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 placed on the proximal phalanx of the index finger, with the sensor window applied against the palmar side of the proximal phalanx of the index finger. 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 Belun Ring is stored in device on-board memory. The data is exported when the Belun Ring is returned to the prescribing HCP via USB or Bluetooth and passed to the Belun Sleep AI Software, which is standalone PC software. The Belun Sleep Al loads and processes the signal from the exported data and generates the apnea-hypopnea index (bAHI) and sleep staging identification (bSTAGES).
Let's break down the information regarding the acceptance criteria and the study that proves the device meets them for the Belun Sleep System BLS-100.
1. Table of Acceptance Criteria and Reported Device Performance
The acceptance criteria are implicitly defined by the clinical study results being presented as sufficient evidence for clearance. While explicit "acceptance criteria" are not listed as pass/fail thresholds in a formal table, the provided performance metrics represent the device's demonstrated capabilities.
Here's a table summarizing the reported device performance, which the FDA accepted as evidence of substantial equivalence:
| Metric (Implicit Acceptance Criteria) | Performance (Belun Sleep System BLS-100) |
|---|---|
| AHI Accuracy (at cutoff 15) | 0.877 |
| AHI Sensitivity (at cutoff 15) | 0.898 |
| AHI Specificity (at cutoff 15) | 0.860 |
| AHI Accuracy (at cutoff 30) | 0.925 |
| AHI Sensitivity (at cutoff 30) | 0.840 |
| AHI Specificity (at cutoff 30) | 0.951 |
| Sleep Stage Accuracy (Wake) | 0.885 |
| Sleep Stage Sensitivity (Wake) | 0.604 |
| Sleep Stage Specificity (Wake) | 0.961 |
| Sleep Stage Accuracy (REM) | 0.908 |
| Sleep Stage Sensitivity (REM) | 0.712 |
| Sleep Stage Specificity (REM) | 0.944 |
| Sleep Stage Accuracy (NREM) | 0.827 |
| Sleep Stage Sensitivity (NREM) | 0.904 |
| Sleep Stage Specificity (NREM) | 0.695 |
| Mean difference between bTST and PSG-TST | 21.8 minutes |
| Standard deviation of difference between bTST and PSG-TST | 41.6 minutes |
| Mean absolute difference between bTST and PSG-TST | 30.8 minutes |
2. Sample Size and Data Provenance
- Sample Size for Test Set: 106 patients suspected of obstructive sleep apnea (OSA).
- Data Provenance: The study compared the device's performance against overnight polysomnography (PSG) studies conducted in a sleep laboratory. The location of the sleep laboratory (country of origin) is not explicitly stated in the provided text. The study design implies this was a prospective collection of data for this evaluation, as it describes patients going through a study with both the Belun device and PSG.
3. Number of Experts and Qualifications for Ground Truth
- Number of Experts: At least two experts, as the text states "a senior sleep tech scorer and reviewed by a board-certified sleep physician."
- Qualifications of Experts:
- One "senior sleep tech scorer."
- One "board-certified sleep physician."
4. Adjudication Method for the Test Set
The adjudication method used to establish the ground truth for the test set was: "All sleep studies were manually scored based on the AASM scoring manual (version 2.4) by a senior sleep tech scorer and reviewed by a board-certified sleep physician." This indicates a two-step process where one scorer performs the primary scoring, and a physician provides a review, implying a form of consensus or verification, though not a multi-reader disagreement resolution specifically.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The study focuses on the standalone performance of the device's AI algorithms (bAHI and bSTAGES) compared to PSG ground truth, not on how human readers' performance improves with or without AI assistance.
6. Standalone Performance
- Yes, a standalone (algorithm only without human-in-the-loop performance) study was done. The clinical study section directly reports the accuracy, sensitivity, and specificity of the Belun Sleep System BLS-100's AHI and sleep staging calculations compared to PSG results, indicating the performance of the device's algorithms themselves. The statement "All investigators, sleep lab team, and scorers were blinded to the results until statistical analysis was performed" further supports that the device's output was generated independently.
7. Type of Ground Truth Used
- The type of ground truth used was expert consensus based on Polysomnography (PSG) studies, manually scored according to the American Academy of Sleep Medicine (AASM) guidelines (version 2.4) by a senior sleep tech scorer and reviewed by a board-certified sleep physician.
8. Sample Size for the Training Set
- The document does not explicitly state the sample size for the training set used for the Belun Sleep AI's deep-learning algorithms. It only provides details for the clinical validation (test) set.
9. How the Ground Truth for the Training Set Was Established
- The document does not explicitly state how the ground truth for the training set was established. It mentions that the clinical evaluation "confirmed that the Belun Sleep System deep-learning algorithms calculating the Belun Apnea Hypopnea Index (bAHI) and Belun Sleep Stage (bSTAGES) generate comparable output to human manual scoring of an Apnea Hypopnea Index (AHI) from Polysomnography (PSG) studies, using American Academy of Sleep Medicine (AASM) scoring guidelines for adult patients". While this describes the validation against PSG ground truth, it doesn't detail the ground truth establishment process for the data used to train the AI models.
§ 868.2375 Breathing frequency monitor.
(a)
Identification. A breathing (ventilatory) frequency monitor is a device intended to measure or monitor a patient's respiratory rate. The device may provide an audible or visible alarm when the respiratory rate, averaged over time, is outside operator settable alarm limits. This device does not include the apnea monitor classified in § 868.2377.(b)
Classification. Class II (performance standards).