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The Somfit D is a single-use, non-invasive prescription device for home use with patients suspected to have sleep-related breathing disorders. The Somfit D is a diagnostic aid for the detection of sleep-related breathing disorders, sleep staging (REM, N1, N2, N3, Wake), and snoring level. The Somfit D system acquires electrical data from three frontal electrodes, tri-axial accelerometer data, acoustical and plethysmographic data. The Somfit D calculates and reports to clinicians EEG/EOG channels, Sleep Stages, SpO2, Peripheral Arterial Tonometry signal, pulse rate, and snoring level. The Somfit D calculates and reports to clinicians derived parameters such as Peripheral Arterial Tonometry-derived Apnea Hypopnea Index, Obstructive Desaturation Index; and hypnogram-derived indices such as time in each sleep stage. Somfit D data is 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. The Somfit D is not intended for use as life support equipment, for example vital signs monitoring in intensive care unit. The Somfit D is a prescription device indicated for adult patients aged 21 years and over.

The Somfit D is a home-based sleep monitoring device which records signals from the patient's forehead. Somfit D is a wearable, low voltage, battery operated device which is attached to subject forehead via a self-adhesive and disposable skin electrode patch. The electrodes are placed on the anterior Prefrontal cortex (PFC) at the Fp1 and Fp2 positions according to the 10/20 EEG system. The device allows for recording of two frontal EEG signals, pulse rate, SPO2, PAT, PPG, motion, and snore. Somfit D uses a mobile phone application to acquire data wirelessly via Bluetooth BLE technology, then transfer into a secure cloud, for management, storage and post-processing. The software reports measured parameters in a format compatible with the American Academy of Sleep Medicine guidelines, including sleep time, ODI, pAHI and conventional graphical displays such as a hypnogram.

The provided FDA 510(k) clearance letter and Somfit D 510(k) Summary describe the acceptance criteria and the study that proves the device meets those criteria. However, it explicitly states that the Somfit D is substantially equivalent to the predicate device, Somfit (K231546), and therefore, the performance data for the Somfit D is derived from the studies conducted on the Somfit. The summary then refers to already submitted and approved studies for the Somfit device.

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

Acceptance Criteria and Device Performance (Derived from Predicate Device, Somfit)

Table 1: Acceptance Criteria and Reported Device Performance

Study Details (Pertaining to the Predicate Device, Somfit, as explicitly stated for Somfit D equivalence)

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

   • Oximeter Validation: Controlled desaturation study in accordance with ISO 80601-2-61. Specific sample size not specified in this document, but implied to be sufficient for standard compliance. Data provenance is implied to be from a "Hypoxia Lab." The document doesn't specify if it was retrospective or prospective, or country of origin, but clinical studies for FDA clearance are typically prospective to ensure controlled conditions.
   • Home Sleep Apnea Test Validation (pAHI, ODI, Sleep Staging): A "Multi-Site Clinical Study" was conducted. Specific sample sizes for each of these validations are not provided in this summary. The document states "clinical data for the purpose of the predicate device Somfit (K231546), already submitted and approved," indicating these details would be found in the original Somfit 510(k) submission. The provenance is from "Multi-Site Clinical Study," implying multiple locations, likely within the regulatory jurisdiction where the clearance was sought (e.g., US, Australia). It's implied to be prospective for validation purposes.

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

   • This information is not explicitly stated in the provided 510(k) summary for any of the clinical validations (Oximeter, pAHI, ODI, Sleep Staging). It only mentions that the studies were "meaningful validations" and "concordance," implying comparison to a gold standard. For sleep staging, ground truth is typically established by certified polysomnography technologists and/or sleep physicians.

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

   • This information is not explicitly stated in the provided 510(k) summary for any of the clinical validations.

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 MRMC study is mentioned. The Somfit D (and its predicate Somfit) is described as a diagnostic aid that calculates and reports parameters to clinicians. It's not presented as an AI-assissted reading tool for human interpretation, but rather a device that quantifies specific physiological signals and derives standard indices. The human role is in interpretation of the reported data, not in an AI-assisted reading workflow.

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

   • Yes, the device (Somfit D, through its predicate Somfit) performs standalone algorithmic analysis to calculate:
     • Sleep Stages (REM, N1, N2, N3, Wake)
     • SpO2
     • Peripheral Arterial Tonometry (PAT) signal
     • Pulse rate
     • Snoring level
     • PAT-derived Apnea Hypopnea Index (pAHI)
     • Obstructive Desaturation Index (ODI)
     • Hypnogram-derived indices (e.g., time in each sleep stage)
   • The "meaningful validation" studies for these parameters (pAHI, ODI, Sleep Staging) suggest a comparison of the device's algorithmic outputs against established ground truth.

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

   • Oximeter Validation: Performed in a "Hypoxia Lab," implying comparison to a highly accurate laboratory reference oximeter or blood gas analysis (gold standard for SpO2 measurements).
   • Home Sleep Apnea Test Validation (pAHI, ODI, Sleep Staging): While not explicitly stated, for HSAT devices, "ground truth" for pAHI and ODI is typically derived from comparison to full in-lab Polysomnography (PSG) data scored by a certified sleep technologist and/or interpreted by a board-certified sleep physician, which is considered the clinical gold standard. For sleep staging, the ground truth would be expert-scored PSG recordings.

7. The sample size for the training set:

   • This information is not provided in the summary. The summary focuses on the validation studies, which imply the device's algorithms were already developed and trained.

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

   • This information is not provided in the summary, as it pertains to the development phase rather than the validation phase described.

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Onera STS 2 measures and records multiple physiological parameters from a patient during a sleep study, which are used by clinicians to decide on the diagnosis of sleep disorders.

Onera STS 2 is intended to be used on a patient who has been prescribed a polysomnography study by a healthcare professional. The device is designed to be used under the direction of a physician or trained technician but applied by a layperson.

The recorded data will be made available to the healthcare professional to assist in the diagnosis of sleep disorders.

The device is intended to be used for adults.

The device is not a life supporting physiological monitor.

Onera Sleep Test System 2 (Onera STS 2) is a hardware, wearable system for measuring physiological signals during a sleep study. The device can be used in the home (Home Healthcare Environment) as well as in Professional Healthcare Facilities.

The device measures EEG, EOG, EMG, ECG, respiratory signals, cannula based respiratory flow, oxygen saturation, activity, position, ambient light level and sound pressure level.

The ECG signal is not intended for diagnosis of cardiac disorders, except for the manual determination of arrhythmia during polysomnography studies.

The Onera STS 2 does not provide any automated output like heart rate, assessments of arrhythmia, heart rate variability, or other related heart rate measurement functions.

Onera STS 2 consists of five Sensors applied on the forehead, upper chest area, abdomen and lower leg area (both left and right leg).

The Sensors should be placed on intact skin. During the night measurement it is not needed to inspect the application sites. The Sensors encrypt the recorded signals and upload the measurement data during the night to the Patient App installed on the patient's phone via Bluetooth. The Patient App securely transfers the data to the cloud interface for further processing once all data has been uploaded. The output of the system is represented by a file in EDF format which contains the recorded (physiological) signals. EDF files can be read by any application software that accepts such files as input.

It is not possible to relocate the Sensors during a sleep study since the Sensor is single-use and for one sleep study only.

Here's a summary of the acceptance criteria and study information for the Onera STS 2, based on the provided FDA 510(k) clearance letter:

Onera STS 2: Acceptance Criteria and Performance Study Summary

1. Table of Acceptance Criteria and Reported Device Performance

The provided document primarily focuses on the SpO2 measurement accuracy as a key performance metric with specific acceptance criteria.

Note: While other parameters are listed as "Identical" to the predicate, specific numerical acceptance criteria for those parameters are not explicitly stated in this document beyond their qualitative equivalence.

2. Sample Size and Data Provenance for the Test Set

• Sample Size: 12 healthy subjects
  • 9 male, 3 female
  • Aged between 23 and 46 years old
• Data Provenance: The study was conducted in an "independent research laboratory." The country of origin is not explicitly stated in the provided text. The study involved "induced hypoxia," indicating a prospective, controlled experimental design.

3. Number and Qualifications of Experts for Ground Truth

• The document does not mention the use of experts to establish ground truth for the SpO2 accuracy test.
• The ground truth for SpO2 was established by "laboratory co-oximeter" measurements of arterial hemoglobin oxygen (SaO2) values from blood samples.

4. Adjudication Method for the Test Set

• The document does not describe any adjudication method. The SpO2 accuracy was determined by direct comparison of the device's SpO2 measurements to SaO2 values from a laboratory co-oximeter.

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

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not conducted or described in this document. The device primarily measures physiological parameters, and the study focused on the accuracy of these measurements rather than human reader interpretation with or without AI assistance.

6. Standalone (Algorithm Only) Performance Study

• Yes, a standalone performance study was conducted for SpO2 measurement accuracy. The device's SpO2 readings were directly compared to reference SaO2 values without human intervention in the SpO2 measurement process itself. The Onera STS 2 is described as measuring and recording parameters, with the output as an EDF file to be read by other software. The SpO2 accuracy assessment is specifically for the device's measurement capability.

7. Type of Ground Truth Used

• Objective Measurement (Laboratory Co-oximeter): For SpO2 accuracy, the ground truth was established by arterial hemoglobin oxygen (SaO2) values determined from blood samples using a laboratory co-oximeter, which is considered a gold standard for blood oxygen saturation.

8. Sample Size for the Training Set

• The document does not provide information regarding the sample size for a training set. This is likely because the performance study described (SpO2 accuracy) is a validation of the device's sensor capabilities, not an evaluation of a machine learning algorithm that would typically require a training set. The device outputs raw physiological signals in EDF format for clinicians to interpret, rather than providing automated diagnoses based on an internal algorithm.

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

• As no training set is mentioned or implied for the device's core functionality (measuring and recording parameters for clinician interpretation), this information is not applicable and not provided in the document.

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The Happy Health Home Sleep Test is a Software as a Medical Device that uses data from wearable devices to record, analyze, display, export, and store biophysical parameters to aid in evaluating sleep‐related breathing disorders of adult patients suspected of sleep apnea. The device is intended for use on individuals who are 22 years of age or older in clinical and home settings under the direction of a trained healthcare provider.

The Happy Health Home Sleep Test is a Software as a Medical Device that uses data from wearable devices to record, analyze, display, export, and store biophysical parameters to aid in evaluating sleep-related breathing disorders of adult patients suspected of sleep apnea.

The device is intended for use on individuals who are 22 years of age or older in clinical and home settings under the direction of a trained healthcare provider. The device is intended to process input data streams received from an external hardware device (i.e., a smart ring, K240236) and uses these signals to determine various sleep parameters that may be used and interpreted by a clinician in diagnosing sleep disorders such as sleep apnea.

The input physiologic signals from the external device are:

• Acceleration / Movement
• Photoplethysmography (PPG)

The external hardware device (K240236) includes a PPG sensor and accelerometer embedded within a housing to capture the above physiological signals. The K240236 device is worn on the finger and is indicated for continuous data collection of the above signals. Data from the external hardware device is transmitted over a secure API to the subject device for analysis.

The device then uses a set of algorithms to compute the following outputs:

• Happy Health Apnea Hypopnea Index (hAHI)
• Total Sleep Time

The outputs are available for a clinician to review as a report, accessible through a web-based viewer application.

The provided FDA 510(k) clearance letter and summary for the Happy Health Home Sleep Test give a good overview of the device's performance testing. Here's a structured breakdown of the acceptance criteria and the study proving the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly list "acceptance criteria" as a separate section with specific thresholds that were agreed upon before the study. Instead, it presents performance metrics of the Happy Health Home Sleep Test and compares them to the predicate and reference devices, implying these metrics are the basis for demonstrating substantial equivalence. For clarity, I'm inferring the acceptance criteria from the "Equivalent" column in the comparison tables and the detailed performance results.

2. Sample Size and Data Provenance

• Test Set Sample Size: 90 subjects.
• Data Provenance:
  • Country of Origin: Not explicitly stated, but the study was conducted at "two sleep labs", implying a clinical setting within the country of submission (likely USA, given FDA submission).
  • Retrospective or Prospective: The wording "Data from a total of 90 subjects referred to the sleep clinic by a physician was manually scored" suggests the data was collected prospectively for the purpose of the study. The phrasing "A clinical study was performed to evaluate the performance..." also indicates a planned, prospective study.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Not explicitly stated how many experts were involved in the manual scoring. The text only mentions "manually scored in accordance with the American Academy of Sleep Medicine (AASM) guidelines."
• Qualifications of Experts: Not explicitly stated, but implied to be qualified sleep technicians/physicians capable of AASM-compliant scoring.

4. Adjudication Method for the Test Set

The adjudication method for reconciling discrepant manual scores (if multiple scorers were used) is not specified in the provided text. It simply states "manually scored." If only one scorer per patient, no adjudication would be needed.

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

There is no indication that a multi-reader multi-case (MRMC) comparative effectiveness study was done to evaluate how human readers improve with AI vs. without AI assistance. The study focuses solely on the device's standalone performance compared to manual PSG scoring.

6. Standalone (Algorithm Only) Performance

Yes, a standalone performance study was done. The entire clinical testing section details the performance of the "Happy Health Home Sleep Test" algorithm (hAHI and TST) compared to manually scored Polysomnography (PSG) data, without human-in-the-loop assistance.

7. Type of Ground Truth Used

The primary ground truth used was expert consensus / manual scoring of Polysomnography (PSG) data in accordance with American Academy of Sleep Medicine (AASM) guidelines. This is the gold standard for sleep studies.

8. Sample Size for the Training Set

The sample size for the training set is not provided in this document. The clinical study details describe the test set used for validation.

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

The document does not provide information on how the ground truth for the training set was established. It only discusses the ground truth for the clinical validation (test) set.

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AcuPebble Ox200 is a wearable device intended for use in the recording, analysis, displaying, exporting, and storage of biophysical parameters to aid in the evaluation of adult patients with, or with suspected, obstructive sleep apnea (OSA). The device is primarily intended for home setting use (although can also be used in healthcare settings) under the direction of a Healthcare Professional (HCP).

AcuPebble Ox200 is prescribed by a Health Care Professional for the patient to use in the home as a 'home sleep apnea test' (HSAT). AcuPebble Ox200 comprises: 1- A small microphones/accelerometer sensor, identical to the one in the previously cleared devices AcuPebble SA100 (K210480) and AcuPebble Ox100 (K222950) that is worn on the front of the neck around the suprasternal notch area (the "AcuPebble SA100 sensor"), and attaches with a single use biocompatible adhesive tape (same one as for "AcuPebble SA100" and "AcuPebble Ox100)); 2- Another PPG/accelerometer sensor ("AcuPebble_oximetry sensor") worn either on the finger or on the forehead; 2- A mobile device app (the "AcuPebble Ox200 app") that guides the patient through the steps of the test, collects the data from the sensors, and uploads them in the cloud ; 3- A cloud-based software that analyses the collected signals as in the previously cleared devices; 4- A web app user interface for healthcare professionals where they can set up a study and see the results, including different physiological channel traces and OSA diagnostic parameters, as in the previously cleared devices.

The differences between AcuPebble Ox200 and the previously cleared device (K222950) are:

• A new sensor for sensing the PPG signal and extraction of the SpO2 and pulse rate channel from. This new sensor can be placed either on the finger or the forehead.
• The addition of new parameters extracted from the acoustic neck sensor including position, respiratory efforts and respiratory rate channels.

The OSA diagnostic indexes are still extracted from the signals measured with the identical sensor as in the predicate (neck sensor only), and with the same algorithms, remain unchanged with respect to the predicate device (K222950) and hence have not been separately tested in this device.

Here's a summary of the acceptance criteria and the studies that prove the device meets those criteria, based on the provided text:

AcuPebble Ox200 Acceptance Criteria and Performance Study Summary

1. Table of Acceptance Criteria and Reported Device Performance

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The TipTraQ is a wearable device intended for aiding in sleep apnea evaluation/diagnosis for adult patients suspected of sleep apnea in both home-based and clinical-use environments.

TipTraQ is a prescription-only medical device aiding in sleep apnea evaluation/diagnosis comprising a fingertip wearable device, a companion mobile app, a cloud-based AI analysis and an information display system. It collects essential physiological waveform information, including Photoplethysmogram (PPG) and accelerometer data. The TipTraQ Algorithm System determines Total Sleep Time (TST), Total REM Time (TREMT), Oxygen Desaturation Index (ODI), and Apnea-Hypopnea Index (AHI) from the recorded waveform signals.

TipTraQ Sensor includes a PPG sensor, which uses light sources (green, red, and infrared) and two photodetectors to measure the blood volume changes in the microvascular bed of tissue. Additionally, the TipTraQ Sensor utilizes an Inertial Measurement Unit (IMU) with three-axis accelerometers (device-function) and three-axis gyroscopes (non-device function), monitoring movement and actigraphy to assess sleep stages. The TipTraQ Expert Panel can display recorded physiological waveforms, while the TipTraQ API System generates output for essential physiological parameters analyzed by the TipTraQ Algorithm System.

The TipTraQ Sensor is rechargeable and designed to provide at least 12 hours of usage after fully charged. The TipTraQ Charging Case, which is also rechargeable, provides a battery capacity of eight full charges of the TipTraQ Sensor for user convenience. The TipTraQ Charging Case can be powered and charged using an external USB-C.

Here's a breakdown of the acceptance criteria and the study details for the TipTraQ (TTQ001) device, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document presents the performance results directly without explicitly stating the "acceptance criteria" as a separate, quantified threshold. However, for the SpO2 validation, it states "met the predefined acceptance criteria

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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 AI/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 used for diagnostic purposes and is not intended by any automated ECG analysis system or algorithm.

This document (K244027) is a Special 510(k) submission for the SANSA HSAT device, focusing on adding cellular capability. This type of submission is used when a modification to an already cleared device does not significantly change its safety or effectiveness or its indications for use. Therefore, the information provided primarily concerns the equivalence of the modified device to its predicate (which is its own previous version, K240285).

The document states that there are no changes to the Indications for Use, physical hardware, principles of operation, device offerings, manufacturing process, or device packaging as part of the cellular update. This means that the core performance characteristics related to sleep apnea detection and physiological measurements have already been established and cleared with the predicate device.

Given this context, the document does not contain a new, comprehensive clinical study proving the device meets new acceptance criteria for its core function (sleep apnea detection). Instead, it focuses on non-clinical testing to demonstrate that the addition of cellular capability does not negatively impact the device's original performance and introduces no new safety or effectiveness concerns.

Therefore, many of the requested points regarding acceptance criteria and clinical study details for the sleep apnea detection function are not included in this specific Special 510(k) document, as they were addressed in the original clearance (K240285). The performance claims for the device (e.g., Sensitivity, Specificity for OSA) are listed as "Identical" to the predicate, meaning these were established in the predicate's clearance.

However, I can extract the information related to the changes made and the testing performed for this specific submission (K244027):

Here's an analysis based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

For the specific change (cellular capability), the document does not present a table of new clinical acceptance criteria. Instead, it asserts that the performance remains "Identical" to the predicate, and non-clinical testing verifies that the cellular addition does not degrade this performance.

The "Performance" criteria listed under the "Device Comparison" table are for the main function of the device (sleep apnea detection and physiological measurements), which are stated to be identical to the predicate. These are not new acceptance criteria for the cellular update, but rather the previously established performance of the base device.

For the cellular capability itself, the acceptance is implicitly based on:

• Successful wireless data transfer via Cellular (LTE-M).
• No regression in existing functionality.
• Maintenance of data integrity during upload.
• Meeting cybersecurity requirements.
• Compliance with wireless testing standards (FCC 47 CFR Part 15, Part 24, Part 27, Part 2).

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

This Special 510(k) primarily relies on non-clinical testing for the cellular capability. Therefore, there is no "test set" in the sense of a patient cohort for a clinical study.

• Test Set (for the cellular update): Not applicable in terms of patient data. The testing involved software testing, cybersecurity testing, and wireless testing. The sample size for these types of tests would be in terms of test cases, configurations, and test environments, not patient data.
• Data Provenance: Not applicable for the cellular update. The statement "Identical" for performance refers to the original data from the predicate device's clearance.

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

Not applicable for this Special 510(k) submission, as no new clinical study requiring ground truth establishment by experts for sleep apnea diagnosis was performed for the cellular update. The "Identical" performance refers to the ground truth established for the predicate device.

4. Adjudication Method for the Test Set

Not applicable for this Special 510(k) submission.

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

No. This submission is for a modification (cellular capability) to an existing device, not a new AI-assisted diagnostic tool requiring a human-in-the-loop MRMC study. The "device performance" listed is for the standalone device, not in assistance with human readers in a comparative setting.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) was Done

Yes, the performance metrics (Sensitivity, Specificity for OSA, Heart Rate, SpO2 accuracy) listed in the "Device Comparison" table represent the standalone performance of the SANSA HSAT device's algorithms, without human intervention in the interpretation of these core metrics. These metrics are stated to be "Identical" to the predicate, implying this standalone performance was established during the predicate's clearance.

7. The Type of Ground Truth Used

For the core function of sleep apnea evaluation (sAHI, etc.), the document does not explicitly state the ground truth used. However, for sleep apnea diagnostics, the common ground truth is Polysomnography (PSG) scored by board-certified sleep technologists and interpreted by board-certified sleep physicians. Since the device aids in the evaluation of sleep-related breathing disorders, it's highly likely that full PSG served as the ground truth for the predicate device's performance validation. This document does not provide details of the ground truth for the predicate.

8. The Sample Size for the Training Set

The document does not provide information on the training set sample size. This would have been part of the original K240285 submission, as this document focuses only on changes related to cellular connectivity.

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

The document does not provide information on how the ground truth for the training set was established. This would have been part of the original K240285 submission.

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The DormoTech Nlab is a physiological data recorder intended to collect and record data from multiple physiological channels for use by clinical software used in polysomnography and sleep disorder studies. It is intended for use by or on the order of a physician. It is intended for use on patients greater than 6 years of age in a supervised (hospital) or unsupervised (home) environments.

The DormoTech Nlab is a physiological data recorder intended to collect and record data from multiple physiological channels for use by clinical software used in polysomnography and sleep disorder studies. It is intended for use by or on the order of a physician and is intended for use on patients greater than 6 years of age in a supervised (hospital) or unsupervised (home) environment.

It consists of:

The Head Unit
The head unit acquires electric signals indicative of EEG and eye movement located in the upper part of the unit (on the patient's forehead). Plethysmograph for Heart rate and SpO2 measurements, and head relative position to body position are also measured using accelerometer sensors located in the upper part of the unit. The middle part of the unit is located below the mouth, it contains 2 nasal (one in each nostril) and 1 oral airflow sensors (thermistors), 1 EMG sensor, along with a snoring sensor.

The Body Unit
The body unit is made of 2 belts, the upper belt sits on the lower belt sits on the stomach of the patient. Both belts contain respiratory effort and accelerometer sensors, in addition, the upper belt contains an accelerometer to measure body position.

The ExG Unit
The ExG unit is put on using an adhesive sticker on the leg/arm/chest (either leg/arm is ok). It consists of 3 electrodes that acquire leg/arm/chest ExG signal.

The Central Unit
The head, chest and ExG units communicate with the central unit via Bluetooth, the wearable units send the measured data to the central unit receives the data, stores it within an internal flash drive and then transmits the data via Wi-Fi to online servers for further diagnosis. The central unit is located in the test room (up to 10 meters from the patient). The central unit has no contact with the patient.

To ensure device reusability between sessions or patients, sections of the head unit have been designed to be detachable or with barriers between the sensor and patient's skin to stop direct contact. Specifically, the head unit incorporates (1) a detachable nasal and oral airflow section to allow for replacement of the section between each use of the device, (2) a removable barrier over the plethysmograph recorder to create a separation between the patient's skin and the recording device which is replaced between each use of the device and (3) a detachable textile on the inner side of the head unit (i.e., the side in direct contact with the patient's skin) to allow for replacement between each use of the device.

Here's a breakdown of the acceptance criteria and the studies that prove the DormoTech NLab device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are effectively demonstrated by the "good agreement" between the DormoTech NLab and the gold standard PSG, and the acceptable RMSE for the SpO2 sensor.

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

• Polysomnography (PSG) Study:
  • Sample Size: 24 subjects (out of 26 recruited) completed the study.
  • Data Provenance: Prospective clinical study conducted in two sleep labs in Israel (Shamir Medical Center Be'er Ya'akov, and Millenium Sleep Clinic Be'er Sheva).
• SpO2 Sensor Study:
  • Sample Size: 12 patients. 259 data points were included in the analysis.
  • Data Provenance: Prospective clinical study. No specific country of origin is mentioned, but it's likely part of the overall clinical trials for the device, potentially in Israel as well.

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

The document does not explicitly state the number of experts or their specific qualifications (e.g., "radiologist with 10 years of experience") used to establish the ground truth for human-scored parameters in the PSG study. However, the ground truth for the PSG study is based on a "gold standard polysomnogram (PSG) study," which inherently implies scoring by trained sleep specialists.

For the SpO2 sensor study, the ground truth was established by "simultaneous monitoring of arterial HbO2 saturations at six different levels of oxyhemoglobin saturation between 70-100%," which is a direct physiological measurement, not an expert-based ground truth.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method (e.g., 2+1, 3+1) for the human-scored PSG parameters. The mention of "gold standard PSG" suggests that standard clinical scoring practices were followed, which typically involve certified polysomnography technologists scoring sleep studies.

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

No multi-reader multi-case (MRMC) comparative effectiveness study was done. The study compares the device's readings directly to a gold-standard PSG for the sleep parameters and directly to arterial blood gas measurements for SpO2, not comparing human readers with and without AI assistance.

6. Standalone (Algorithm Only) Performance

The device is described as a "physiological data recorder intended to collect and record data from multiple physiological channels for use by clinical software used in polysomnography and sleep disorder studies." This implies that the device itself is a data acquisition unit, and its performance is evaluated in terms of its ability to accurately record these physiological signals compared to established methods.

• For PSG parameters: The "DormoTech NLab" is compared to a "gold standard polysomnogram (PSG)." This is a standalone performance evaluation of the device as a data recorder, with the implicit understanding that the data collected by both the NLab and the predicate PSG would then be analyzed by clinical software (or human scorers). The "mean difference" and "limits of agreement" directly assess the NLab's standalone measurement accuracy against the gold standard.
• For SpO2 sensor: The "DormoTech NLab SpO2 sensor" is compared to "arterial HbO2 saturations." This is a standalone performance evaluation of the sensor's accuracy.

7. Type of Ground Truth Used

• Polysomnography (PSG) Parameters: "Gold standard polysomnogram (PSG) study." This refers to a comprehensive sleep study recorded and scored according to established clinical guidelines, serving as the benchmark for various sleep parameters. It's essentially expert-interpreted physiological data.
• SpO2 Sensor: "Arterial HbO2 saturations." This is direct physiological outcomes data obtained through arterial blood gas measurements, which is considered the most accurate measure of blood oxygen saturation.

8. Sample Size for the Training Set

The document does not explicitly state the sample size for any training set. It focuses on the validation studies, which are test sets. This device primarily functions as a physiological data recorder, not necessarily an AI/machine learning algorithm requiring a separate training set in the typical sense. Any internal calibration or algorithm development would likely have used internal datasets, but these are not detailed in this premarket notification.

9. How Ground Truth for the Training Set Was Established

Since no training set details are provided, the method for establishing its ground truth is also not mentioned.

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The Bluebird Single-Use Respiratory Effort Belt is intended to measure respiratory effort to assist in the diagnosis of sleep disorders or sleep related respiratory disorders. The respiratory effort belt signals are suitable for connection to sleep/polysomnography (PSG) systems. The intended environments are hospitals, institutions, sleep clinics, or other test environments, including the patient's home.

The Bluebird Single-Use Respiratory Effort Belt is intended for diagnostic purposes only on patients greater than 2 years of age and is not intended to be used as an apnea monitor.

The Bluebird Single-Use Respiratory Effort Belt (Bluebird) is used to measure chest and abdomen expansion and contraction during respiration. The sensor consists of a sinusoidal wire coil attached along the length of an elastic belt. The inductance of the sensor changes as the belt is stretched. The Bluebird is suitable for connection to the inputs of physiological recording equipment. The Bluebird measures inductance and generates an output signal proportional to the amount of stretch. The elastic belt is held in place by a quick release buckle with a cinch function and the belt is adjusted to fit snugly but comfortably. Electrical connection to the two ends of the embedded coil is through a 1.5mm female touch proof connection jack on each side of belt buckle. The materials are elastics and plastics used in the clothing industry, and fine gauge copper wire for the embedded coil.

The provided text describes a 510(k) summary for the "Bluebird Single-Use Respiratory Effort Belt" (subject device) and its equivalence to a predicate device, the "XactTrace® Single Use Respiratory Effort Belt System."

Here's an analysis of the acceptance criteria and the study that proves the device meets those criteria:

1. Table of Acceptance Criteria and Reported Device Performance

The FDA 510(k) summary doesn't explicitly state "acceptance criteria" in a quantitative, pass/fail format like a clinical trial. Instead, it focuses on demonstrating substantial equivalence to a predicate device. The performance testing outlined serves to demonstrate that the subject device performs comparably to the predicate and meets design requirements.

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

• Sample Size for Test Set: The document does not specify a sample size for the comparative performance testing. It mentions "Performance testing was performed for the Bluebird rip belt connected to a Cadwell recording device and simultaneously to an XactTrace belt." This suggests a comparative test, but the number of devices or data points isn't quantified.
• Data Provenance: The document does not provide information on country of origin or whether the data was retrospective or prospective. It describes non-clinical laboratory testing ("Nonclinical tests were performed on the subject device").

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

• This information is not provided in the document. As this is a non-clinical, performance-based study comparing a physical device to another, the concept of "ground truth" as established by medical experts for diagnostic accuracy studies does not directly apply here. The "ground truth" seems to be the expected physical and electrical performance characteristics of such a device, and its output signal, which were compared against the predicate.

4. Adjudication Method for the Test Set

• Adjudication methods (e.g., 2+1, 3+1) are typically used in clinical studies involving interpretation by multiple readers. This information is not applicable/provided as this is a non-clinical performance study comparing two medical devices' physical and electrical outputs.

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

• No, an MRMC comparative effectiveness study was not done. This type of study is relevant for AI-powered diagnostic tools or imaging devices where human readers interpret patient data. The Bluebird Single-Use Respiratory Effort Belt is a sensor intended to measure respiratory effort, not an interpretive AI tool.
• Therefore, information on the effect size of human readers improving with AI vs. without AI assistance is not applicable.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• No, a standalone (algorithm only) study was not done. This device is a physical sensor, not an algorithm. Its performance is about accurately capturing a physiological signal.

7. Type of Ground Truth Used

• The "ground truth" in this context is the expected physical and electrical performance of a respiratory effort belt and its output signal, as demonstrated by the legally marketed predicate device.
• The study aimed to show that the subject device's performance, particularly its breathing effort signal output, was equivalent to that of the predicate device. The statement "The resulting waveforms are the same for both belts" indicates that the predicate's output served as the benchmark.

8. Sample Size for the Training Set

• Not applicable. This device is a physical sensor, not an AI/ML algorithm that requires a training set.

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

• Not applicable. As no training set was used for an AI/ML algorithm.

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Withings Sleep Rx is indicated to record a patient's Withings index during sleep as an aid for diagnosis of obstructive sleep apnea (OSA).

The Withings Sleep Rx is also indicated to record heart rate and movement in an automatic contactless manner.

The device is designed for use in home-screening of adults with suspected possible sleep breathing disorders. Results are used to assist the healthcare professional in determining the need for further diagnosis and evaluation. The system is not intended as a substitute for full polysomnography when additional parameters such as sleep stages, limb movements, or EEG activity are required.

The device is indicated for use in adults weighing ≤ 350 lbs in a home environment during sleep and resting conditions.

This device is not indicated for active patient monitoring, as it does not provide alarms for timely response in life-threatening situations.

The Withings Sleep Rx is a device intended as an aid for diagnosis of obstructive sleep apnea (OSA). It is intended for home use. The device is placed under the mattress and is contactless with the user. It provides a Withings index based on breathing (sound, variations of pressure in the bladder) and heart rate measured in a contactless manner. The number of breathing events per hour is displayed to the user in the companion app. The results are used to assist the healthcare professional in determining the need for further diagnosis and evaluation.

In addition, the device records heart rate and movement during sleep in an automatic contactless manner. The recordings are displayed in the companion app.

Withings Sleep Rx is composed of the following components: (1) Mat (hardware); (2) Withings Sleep Rx embedded software included in the Mat and (3) Companion App included in a companion mobile application.

The Withings Sleep Rx device is cleared for recording a patient's "Withings index" during sleep as an aid for diagnosing obstructive sleep apnea (OSA), and for recording heart rate and movement in an automatic, contactless manner. It is intended for home screening of adults with suspected sleep breathing disorders, to assist healthcare professionals in determining the need for further diagnosis.

Here's a breakdown of the acceptance criteria and supporting studies:

1. Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance

• Withings Index (OSA Screening):
  • Sample Size: 118 patients.
  • Data Provenance: The study was conducted with patients referred to a PSG test in a sleep laboratory, suggesting a clinical setting in a specific geographic location (publication mentions "J Clin Sleep Med," and authors are from various institutions, potentially implying an international or multi-center European study due to authors' affiliations). The study involved simultaneous polysomnography (PSG), making it a prospective (or at least concurrent data collection) study.
• Heart Rate Estimation:
  • Sample Size: Data pooled from two clinical studies (ESAS and VPASS). Specific combined sample size not directly stated, but the studies were described as enrolling patients with suspected sleep apnea syndrome referred for a sleep study analysis.
  • Data Provenance: Both studies were conducted with the subject device and involved simultaneous polysomnography (PSG), implying prospective or concurrent data collection in a clinical setting related to sleep studies.
• Movement Detection:
  • Sample Size: Participants in an internal human study. Specific sample size not stated.
  • Data Provenance: Internal study with predetermined movements, suggesting a controlled, laboratory-like setting.

3. Number of Experts and Qualifications for Ground Truth - Test Set

• Withings Index (OSA Screening):
  • Number of Experts: Not explicitly stated, but "simultaneous polysomnography (PSG) manually scored by certified specialists" implies multiple certified specialists.
  • Qualifications: "Certified specialists" in manual scoring of PSG, following AASM guidelines.
• Heart Rate Estimation:
  • Number of Experts: Not explicitly stated, but "simultaneous polysomnography (PSG) scored by a qualified investigator following AASM guidelines" implies qualified investigators.
  • Qualifications: "Qualified investigator" following AASM (American Academy of Sleep Medicine) guidelines.
• Movement Detection: Not applicable as the ground truth was based on predetermined movements by participants.

4. Adjudication Method for the Test Set

• Withings Index (OSA Screening) and Heart Rate Estimation: The information provided does not specify an explicit adjudication method (e.g., 2+1, 3+1). It states "manually scored by certified specialists" or "scored by a qualified investigator," which might imply single scoring or an internal consensus process, but no detail on a formal adjudication protocol is given.
• Movement Detection: Not applicable, as ground truth was based on pre-defined movements.

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

• No information is provided about a multi-reader multi-case (MRMC) comparative effectiveness study to assess the effect size of human readers improving with AI vs. without AI assistance. The studies focused on the performance of the device itself against established clinical standards (PSG).

6. Standalone (Algorithm Only) Performance

• Yes, the studies primarily assessed the standalone performance of the Withings Sleep Rx device.
  • The "Withings Index" for OSA screening was compared directly against PSG.
  • The heart rate estimation was compared against simultaneous PSG data.
  • The movement detection was evaluated based on the device's ability to identify pre-defined participant movements.

7. Type of Ground Truth Used

• Withings Index (OSA Screening) and Heart Rate Estimation: Expert Consensus (PSG scoring). Polysomnography (PSG) manually scored by certified specialists/qualified investigators following AASM guidelines is considered the gold standard for sleep disorder diagnosis.
• Movement Detection: Predefined movements/experimental protocol. The ground truth was based on the participants performing known, predetermined movements for specific durations, allowing for unambiguous identification.

8. Sample Size for the Training Set

• The document explicitly states regarding heart rate estimation:
  • "ESAS was designed to train the algorithm calculating the Withings index of Sleep Rx, but not to train the estimation of heart rate."
  • "VPASS was designed to validate the Withings index, but not to train the estimation of heart rate."
• While these studies mention their role in training or validating the Withings index algorithm, the specific sample size used solely for algorithm training for the Withings Index, heart rate, or movement detection is not provided. The 118 patient study listed under "Clinical study for the validation of the Withings' index" is explicitly for validation of the Withings' index.

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

• For the ESAS study, which was "designed to train the algorithm calculating the Withings index," the ground truth would have been established through simultaneous polysomnography (PSG) manually scored by certified specialists, similar to the validation studies. However, the exact details of the ground truth establishment specifically for the training set are not fully elaborated in this document, beyond stating its purpose was for training.

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