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The Huxley Home Sleep Apnea Test (SANSA) is a wearable device intended for use in the recording, and storage of biophysical parameters to aid in the evaluation of sleep-related breathing disorders of adults suspected of sleep apnea. The device is intended for the clinical and home use setting under the direction of a Healthcare Professional (HCP).

The Huxley Home Sleep Apnea Test (SANSA™) is a wearable device intended for use in the recording, analysis, and storage of biophysical parameters to aid in the evaluation of sleep-related breathing disorders of adults suspected of sleep apnea. The device is intended for clinical and home use setting under the direction of a Healthcare Professional (HCP). The system is prescription use only.

The SANSA HSAT collects multiple physiological signals using a single wearable patch worn on the chest. The SANSA device contains a reflective PPG sensor, a single-lead ECG sensor, and a 3-axis accelerometer. The signals from these sensors are passed into a cloud-based algorithm which utilizes a combination of signal processing and Al/ML components to compute time-series data for clinician review and summary metrics for report output. The device outputs the following time-series channels: Oximetry, Heart Rate, Chest Movement, Snoring, Body Position, Respiratory Effort, Actigraphy, Sleep staging (Sleep/Wake), and ECG (reference channel only). The following summary metrics are calculated: sansa-Apnea Hypopnea Index (sAHI) and Total Sleep Time (TST).

Recorded data are uploaded to a software portal where physiological tracings are made available for review and event editing by a qualified healthcare professional. The device is intended to be worn for 10 hours per study. The ECG channel is intended to be used as a reference channel and is not intended to be used for diagnostic purposes and is not intended by any automated ECG analysis system or algorithm.

Here's a breakdown of the acceptance criteria and study details for the Huxley SANSA Home Sleep Apnea Test (SANSA HSAT), based solely on the provided text:

1. Table of acceptance criteria and the reported device performance:

Note: The table combines the "Performance" section for the predicate and subject devices from the Device Comparison table (page 7) and the "Clinical Performance Data" section for additional reported performance values (page 12). For Sleep/Wake classification, no direct "acceptance criteria" based on the predicate were provided in the document.

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

• SpO2 Accuracy Test Set: The number of subjects is not explicitly stated, but the test was conducted on "healthy subjects" (page 12).
• Comparison to PSG (Moderate to Severe SDB Diagnosis Test Set):
  • Sample Size: n = 533
  • Data Provenance: Prospective multi-center clinical study in the United States (page 12).
• Sleep/Wake Classification Validation Test Set:
  • Sample Size: n = 340 (ITD - likely "Intention To Diagnose")
  • Data Provenance: Not explicitly stated beyond being "gold standard scored PSG data" (page 12).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

This information is not explicitly provided in the text. The ground truth for the comparison to PSG study is stated as "gold standard polysomnography (PSG)" (page 12), and for SpO2, it's "arterial blood gas samples" (page 12). While PSG scoring generally involves experts (e.g., sleep specialists, polysomnographic technologists), the number and specific qualifications of these experts are not detailed in this document.

4. Adjudication method for the test set:

This information is not explicitly provided in the text.

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, an MRMC comparative effectiveness study was not explicitly described. The study focused on the standalone diagnostic performance of the SANSA device compared to PSG. The predicate device's diagnostic performance is noted as being based on "manual scoring of data by HCP" (Healthcare Professional), while the subject device "utilizes an autoscored algorithm with no overread and correction." This suggests a comparison of the AI-driven auto-scoring performance to a human-scored gold standard, but not a study of human readers improving with AI assistance.

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

• Yes, a standalone performance study was done. The "Comparison to PSG" study (n=533) directly evaluates the diagnostic performance of the SANSA device's algorithm for moderate to severe SDB, stating it "utilizes an autoscored algorithm with no overread and correction" (page 7) and yielded specific sensitivity and specificity values. The Sleep/Wake classification also reports algorithm-only performance.

7. The type of ground truth used:

• For SpO2 Accuracy: Arterial blood gas samples (page 12).
• For comparison to PSG (SDB diagnosis) and Sleep/Wake classification: Gold standard polysomnography (PSG) data (page 12).

8. The sample size for the training set:

• For the Sansa device AI-based Sleep/Wake classification algorithm: 101 subjects (page 12).
• For other algorithms (e.g., AHI calculation): This information is not explicitly provided.

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

• For the Sansa device AI-based Sleep/Wake classification algorithm: The algorithm was "trained on 101 subjects and validated against the validation dataset (n=340 ITD) taken from gold standard scored PSG data" (page 12). This implies the ground truth for the training set was also established using "gold standard scored PSG data."
• For other algorithms: This information is not explicitly provided.

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The WatchPAT ONE (WP1) device is a noninvasive home care device for use with patients suspected to have sleep related breathing disorders. The WP1 is a diagnostic aid for the detection of sleep related breathing disorders, sleep staging (Rapid Eye Movement (REM) Sleep, Light Sleep, Deep Sleep and Wake), snoring level and body position. The WP1 generates a peripheral arterial tonometry ("PAT") Respiratory Disturbance Index ("PRDI"), Apnea- Hypopnea index ("PAHI"), Central Apnea-Hypopnea index ("PAHIc"), PAT sleep staging identification (PSTAGES) and optional snoring level and body position discrete states from an external integrated snoring and body position sensor. The WP1's PSTAGES and snoring level and body position provide supplemental information to its PRD/PAHI/PAHIc. The WP1's PSTAGES and snoring level and body position are not intended to be used as the sole or primary basis for diagnosing any sleep related breathing disorder, prescribing treatment, or determining whether additional diagnostic assessment is warranted.

PAHIc is indicated for use in patients 17 years and older. All other parameters are indicated for 12 years and older.

The subject WatchPAT ONE (WP1) has the same intended use and indications for use as the cleared predicate WP300 (K222331) and the cleared reference WP1 (K183559). The subject WP1 combines the software arrhythmia feature of the WP300 cleared predicate (K222331) into the WP1 cleared reference (K183559).

The subject WP1 consists of: A wrist worn Control Unit, Actigraphy (in the Control Unit), Wrist Strap, Power Supply (battery), uPAT probe, Chest sensor (optional), Management and Analysis Software (SW) and mobile application.

The subject WP1, like the predicate WP300 and reference WP1, uses the same Management and Analysis Software (SW). The arrhythmia feature is to be used for informational use only, to flaq patients suspected of having arrhythmias, thereby aiding the physician to decide if further arrhythmia investigation is needed. The device is not intended to be used as a diagnostic device for cardiac arrhythmia and it is not intended to replace traditional methods of diagnosis. The arrhythmia detection is not intended for use in life supporting or sustaining systems or monitor and alarm devices. It provides the sleep physician with additional information to that of the WP1 cleared capabilities of detecting sleep disorders, to be considered in conjunction with the physician's knowledge of patient background, clinical history, symptoms, and other diagnostic information.

The document provided does not contain the specific details required to complete all sections of your request. This is largely due to the nature of a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than providing a full clinical study report with detailed performance metrics, ground truth establishment, or multi-reader multi-case studies.

However, I can extract the following information based on the text provided:

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

The document does not explicitly state "acceptance criteria" with numerical targets or direct "reported device performance" in the context of a clinical study for the newly added arrhythmia feature. It states: "SW Design verification was performed on the subject WP1 device with the SW containing the additional arrhythmia feature. The testing and acceptance criteria are the same as those in the predicate WP300 and reference WP1 devices." This implies that the acceptance criteria for the existing functionalities of the WatchPAT ONE (WP1) were met, and the new arrhythmia feature also adhered to the criteria established for the predicate WP300. Without further information on the WP300's performance from its original 510(k) for the arrhythmia feature, specific numerical acceptance criteria and performance for the arrhythmia detection cannot be provided from this document.

The document emphasizes substantial equivalence to the predicate device WP300 (K222331) and reference device WP1 (K183559). The "performance data" section states: "Bench testing was previously conducted on the reference WP1 (K183559) to show that the acquisition system of the WP1 and WP300 generate equivalent input signals to the analysis algorithms. Specifically, the equivalence of the PAT and the actigraphy signals which are used in the newly added arrhythmia algorithm were tested. This testing provides evidence that the WP1 signals are equivalent to the WP300 signals."

This suggests that the performance of the arrhythmia detection algorithm in the subject WP1 is assumed to be equivalent to that of the predicate WP300 because the input signals are equivalent and the software algorithm is identical.

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

The document does not specify a separate test set sample size or data provenance for the new arrhythmia feature. It refers to "bench testing" that validated the equivalence of signals between WP1 and WP300. This implies that no new clinical test set was used for the arrhythmia feature's performance validation in this specific 510(k) submission, as the feature itself originated from a previously cleared device (WP300).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable for this submission, as no new clinical test set for the arrhythmia detection was performed or described. The validation focuses on signal equivalence and software transfer from the predicate.

4. Adjudication method for the test set

Not applicable, as no new clinical test set for the arrhythmia detection was performed or described.

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 such study is mentioned or implied for the new arrhythmia feature. The device's arrhythmia flagging is described as "informational use only" to "flag patients suspected of having arrhythmias, thereby aiding the physician to decide if further arrhythmia investigation is needed." It is explicitly stated: "The device is not intended to be used as a diagnostic device for cardiac arrhythmia and it is not intended to replace traditional methods of diagnosis." Therefore, a comparative effectiveness study with human readers improving with AI assistance is outside the scope of this particular submission.

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

The document implies a standalone algorithm performance implicitly by stating the "SW Design verification was performed on the subject WP1 device with the SW containing the additional arrhythmia feature. The testing and acceptance criteria are the same as those in the predicate WP300". The feature "flags" abnormal events for a physician's review, suggesting the algorithm operates in a standalone manner to generate these flags. However, whether a dedicated standalone performance study (beyond software design verification) was done for the arrhythmia feature (as distinct from device equivalence) is not detailed here. The focus is on the equivalence of the acquisition system and the software algorithm to the predicate device, where the arrhythmia feature was initially cleared.

7. The type of ground truth used

The document does not describe the ground truth used for the arrhythmia feature validation in this submission. For the sleep-related breathing disorders, the general method would typically involve comparison to Polysomnography (PSG) as the gold standard, but this document focuses on the arrhythmia feature's integration, not re-validation of the entire device. Since the arrhythmia feature was inherited from the WP300, the ground truth establishment would have been part of the WP300 clearance.

8. The sample size for the training set

Not specified in this document. This submission is for enabling an existing algorithm from a predicate device (WP300) onto a different hardware platform (WP1), not for developing a new algorithm. Therefore, training set information is not relevant to this specific 510(k) summary.

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

Not specified in this document, as it is not a new algorithm development and relies on the ground truth establishment from the predicate device (WP300) for the arrhythmia feature.

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Belun Ring BLR-100X is a wireless, non-invasive and stand-alone pulse oximeter intended to be used for continuous data collection and recording of oxygen saturation of arterial hemoglobin (SpO2) and the pulse rate of adult patients through index finger in hospital and home environment for up to ten hours, during no motion and motion conditions, and for patients who are well or poorly perfused. It is not intended for single-use and out-of-hospital transport use and does not have alarms.

Belun Ring BLR-100X is a wireless, non-invasive and stand-alone pulse oximeter intended to be used for continuous data collection and recording of oxygen saturation of arterial hemoglobin (SpO2) and the pulse rate of adult patients through index finger in hospital and home environment for up to ten hours, during no motion and motion conditions, and for patients who are well or poorly perfused. It is not intended for single-use and out-of-hospital transport use and does not have alarms. The proposed device consists of three parts: A Ring, a Cradle and a Host program. The Ring is intended to be worn on the base of the index finger. It provides comfortable and accurate measurements without the Cradle in the recording mode. The soft part of the Ring is designed to be changeable for fitting different sizes of fingers. The Cradle collects data from the Ring and charges up the Ring. It transfers the collected data to host via an attached USB cable or Bluetooth low power technology. The host program translates the data into text and graph which can be easily understood by the user. Using spectrophotometric methodology, the proposed device measures oxygen saturation by illuminating the skin and measuring changes in the light absorption of oxygenated (oxyhemoglobin) and deoxygenated blood (reduced hemoglobin) using light of two wavelengths: red and infrared. The ratio of absorbance at these wavelengths is calculated and calibrated against direct measurements of arterial oxygen saturation (SaO2) to establish the pulse oximeter's measurement of functional oxygen saturation of arterial hemoglobin (SpO2). The sensor of the Ring should be placed on the palmar side of the proximal phalanx of the index finger and along the radial artery. The system consists of three main platforms. Ring is responsible for signal acquisition, data processing, parameters calculation (SpO2/PR algorithm), sensor interfacing and user interface. Cradle takes care of the data storage, data transfer and user interface. Host program is for data export and user interface. The system includes two embedded software and one host program, namely the Ring firmware, the Cradle firmware and the Belun Ring Management.

Acceptance Criteria and Device Performance:

Study Details:

1. Sample Size and Data Provenance:

   • Test Set (Clinical Study): The document does not explicitly state the sample size used for the clinical test set. It only mentions the purpose of the study was to evaluate SpO2 accuracy during steady state/non-motion conditions.
   • Data Provenance: The document does not explicitly state the country of origin or whether the clinical data was retrospective or prospective.

2. Number of Experts and Qualifications for Ground Truth (Test Set):

   • Ground Truth for SpO2: Arterial blood samples assessed by CO-Oximetry.
   • The document does not mention the number of experts or their qualifications for establishing the ground truth from the CO-Oximetry results, as CO-Oximetry is a direct measurement method.

3. Adjudication Method for the Test Set:

   • Not applicable as the ground truth for SpO2 was established by CO-Oximetry, which is a direct measurement.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The study was focused on the standalone accuracy of the device.

5. Standalone Performance:

   • Yes, a standalone performance study was done for the algorithm. The clinical test evaluated the SpO2 accuracy performance of the Belun Ring BLR-100X as a standalone device.

6. Type of Ground Truth Used:

   • For the clinical study, the ground truth for SpO2 accuracy was established using arterial blood samples assessed by CO-Oximetry.

7. Sample Size for the Training Set:

   • The document does not provide information regarding a specific training set or its sample size. The focus is on the validation of the device's performance through bench and clinical testing.

8. How Ground Truth for the Training Set Was Established:

   • Not applicable, as information about a training set is not provided.

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