Search Results

Sleepiz One+ is a contactless medical device intended to measure heart rate and respiration rate in adult patients, at rest or during sleep (in non-motion condition) and to detect patient presence and body movements.

The Sleepiz One+ hardware unit is intended to be used by a healthcare professional when the recordings are performed in a clinical setting, or by patients or their caregivers when the recordings are performed in a home environment. The Sleepiz One+ cloud software is intended for use by healthcare professionals.

This device is not indicated for active patient monitoring, as it does not provide alarms for timely response in life-threatening situations. It is not indicated for use on pregnant women or patients with active implantable devices.

Sleepiz One+ is a contactless medical device that uses radar technology to measure respiration rate and heart rate from a resting or sleeping patient.

The Sleepiz One+ consists of a hardware unit and cloud-based software The hardware unit can be positioned on a bedside table, mounted on a stand, or attached to the wall behind the patient's bed. It is designed to monitor physiological signals by detecting small body movements, such as those caused by breathing and heartbeat, using Doppler radar. The recorded signals are then transmitted via Wi-Fi to cloud-based software, where they are analyzed to obtain respiration rate, heart rate, and body movement. These outputs can be exposed via the Application Programming Interfaces (APIs) to allow healthcare professionals the review and annotation of the data and compilation of results into reports.

Outputs

• Breathing pattern
• Instantaneous breathing rate [breaths per minute]
• Breathing rate statistics (10th, 50th, and 90th quantiles) [breaths per minute]
• Body movement
• Time in bed [hours]
• Presence detection
• Heart rate [beats per minute]
• Heart rate statistics (10th, 50th, and 90th quantiles) [beats per minute]

The overall system can be grouped into 4 major components, which are classified on the basis of the logical component interfaces where data exchange is occurring.

• Sleepiz Hardware - This is a hardware component serving as primary data acquisition device.
• Embedded Software - This encompasses the firmware running of the Sleepiz Hardware. This, together with Sleepiz hardware, is responsible for data acquisition. The embedded software forms the crux of the Sleepiz hardware such that it defines and controls the data acquisition process. The security aspects related to the operation of the device are incorporated in the design and implementation of embedded software.
• Sleep Analytics Software - The sleep analytics software is responsible for processing data from the Sleepiz Hardware and returning its analytics (e.g., breathing rate, heart rate), as well as its statistics (e.g., mean breathing rate, total recording time, etc.). This refers to the ML model deployed within the cloud software. By itself, the Sleep Analytics Software does not have an external interface. It is wholly encapsulated by the cloud software component Data Processing Layer.
• Cloud Software - The cloud software can be divided into the backend service and the analytics service. The backend service includes modules for data ingestion, a public API, a private API, and a module for sending analysis process requests. The analytics service is responsible for receiving analysis requests and interacting with the sleep analytics software.

The FDA 510(k) clearance letter for Sleepiz One+ (2.5) indicates that the device's substantial equivalence to a predicate device (Sleepiz One+) was established primarily through non-clinical performance testing, focusing on software verification and validation, electrical safety, and electromagnetic compatibility. The document states that the subject device and the predicate device have the same intended use, principle of operation, and similar technological characteristics. The minor modifications (API-based data access instead of web interface and plug-in power instead of battery) were assessed for safety and effectiveness without requiring extensive new clinical studies.

The provided document does not detail specific acceptance criteria for the accuracy of heart rate and respiration rate measurements, nor does it provide a study proving the device meets these specific performance criteria. The clearance is based on the conclusion that "The verification and validation tests performed on the subject device confirm that the device performs as intended in the specified use conditions and comparably to the predicate device. The performance testing conducted shows comparable results between the two models, thereby, demonstrating the safety and performance of the Sleepiz One+ (V.2.5)."

Therefore, based solely on the provided text, a comprehensive table of acceptance criteria and the detailed study proving the device's accuracy against those criteria cannot be constructed. The document infers that the device performs as intended and comparably to the predicate, but it does not present the raw performance data or the specific acceptance thresholds for heart rate and respiration rate accuracy.

Here's a breakdown of the requested information based on the provided text, with clear indications where the information is NOT available.

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

Information NOT available in the provided text. The 510(k) summary states that "performance testing conducted shows comparable results between the two models," but it does not quantify these results or list specific acceptance criteria for heart rate and respiration rate accuracy. The testing primarily focused on software validation, electrical safety, and EMC.

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

Information NOT available in the provided text. The document mentions "non-clinical performance tests" and "verification and validation tests," but it doesn't specify any sample sizes for a test set related to the accuracy of vital sign measurements, nor the provenance of any data used for such testing.

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)

Information NOT available in the provided text. There is no mention of external experts or ground truth establishment in the context of vital sign accuracy, as the clearance seems to rely on comparability to a predicate device and engineering verification/validation. For devices measuring physiological parameters, ground truth is typically established via reference medical devices (e.g., ECG, capnography) rather than expert consensus on subjective data.

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

Information NOT available in the provided text. Since no details on a clinical or performance study involving human subjects and expert review are provided, there is no mention of an adjudication method.

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

Information NOT available in the provided text. The Sleepiz One+ is a vital signs monitor, not typically an AI-assisted diagnostic imaging device that would undergo MRMC studies. The device primarily measures heart rate and respiration rate via radar and processes this data in cloud software (Sleep Analytics Software contains the ML model). The interaction is between the device and the patient, not a "human reader" interpreting AI outputs in a MRMC context. The cleared device provides raw data and statistics (like quantiles), which healthcare professionals would then interpret.

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

The device's core function, measuring heart rate and respiration rate from radar signals using its Sleep Analytics Software (which contains the ML model), operates in a standalone manner to generate these outputs. The outputs themselves (instantaneous rates, statistics) are generated by the algorithm without human intervention in the loop of the measurement process itself. Healthcare professionals then access and interpret these results via API. The non-clinical performance testing would have validated the output of this standalone algorithm against internal specifications or a reference.

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

Information NOT explicitly stated in the provided text regarding vital sign accuracy. For devices measuring heart rate and respiration rate, ground truth is typically established using established reference medical devices (e.g., synchronously recorded ECG for heart rate, capnography or impedance pneumography for respiration rate). While not stated, it can be inferred that if accuracy was evaluated, it would be against such objective physiological measurements rather than subjective expert consensus or pathology.

8. The sample size for the training set

The device uses an "ML model deployed within the cloud software" for "Sleep Analytics Software." However, the provided 510(k) summary does NOT provide any details about the training set size or methodology for this ML model. The focus of the substantial equivalence claim is on the overall system's safety and performance comparability to the predicate, with modifications primarily linked to data access and power source.

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

Information NOT available in the provided text. As with the training set size, the 510(k) summary does not provide details on how the ground truth for the training set (if any specific to the ML model) was established.

Ask a specific question about this device

Sleepiz One+ is a contactless medical device intended to measure heart rate and respiration rate in adult patients, at rest or during sleep (in non-motion condition).

The Sleepiz One+ hardware unit is intended to be used by a healthcare professional when the recordings are performed in a clinical setting, or by patients or their caregivers when the recordings are performed in a home environment. The Sleepiz One+ web application is Intended for use by healthcare professionals.

Sleepiz One+ device can also detect the presence of patients and their body movements at rest or during sleep. This device is not indicated for active patient monitoring, as it does not provide alarms for timely response in life-threatening situations. It is not indicated for use on pregnant women or patients with active implantable devices.

Sleepiz One+ is a contactless medical device that uses radar technology to measure respiration rate and heart rate. The device is placed on a bedside table or a stand, mounted slightly higher than the mattress level, from where it detects the presence of a patient and their physiological signals. From that position, distance changes between the device and the patient's body are captured by Doppler radar. The recorded signals are then transmitted to the cloud software where these are analyzed by the signal processing software ("Sleep Analytics Software") to obtain respiration rate, heart rate and facilitate the monitoring of the presence of the patient and their body movement. These outputs are then displayed on the web application to allow the annotation of the data, compilation of results into reports, and the management of the hardware units.

Here's a breakdown of the acceptance criteria and study information for the Sleepiz One+ device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

• Accuracy: +/- 3 breaths per minute (99% accuracy rate)
• 95% Limits of Agreement: -1.42 to 0.97 breaths/min (for neurorehabilitation ward patients)
• 95% Limits of Agreement: -1.3 to 0.8 breaths/minute (for patients suspected of sleep apnea)

Compared to end-tidal CO2 (etCO2) via capnography:

• Accuracy: +/- 2 breaths/minute (93.7% accuracy)
• 95% Limits of Agreement (instantaneous breathing rate): -2.51 to 2.04 breaths/minute
• Mean Absolute Error (average breathing rate): 0.79 breaths/minute
• 95% Limits of Agreement (average breathing rate): -2.63 to 2.01 breaths/minute |
  | Heart Rate Accuracy | The subject device performs comparably to established methods for heart rate measurement. | Compared to Electrocardiography (ECG):
• Accuracy: +/- 5 beats per minute (94% accuracy rate)
• 95% Limits of Agreement: -2.64 to 5.82 beats/min (for neurorehabilitation ward patients)
• 96% heart rate accuracy (for patients suspected of sleep apnea) |
  | Safety | Complies with relevant electrical, mechanical, and emission safety standards. | Passed all electrical and mechanical safety tests per ANSI AAMI ES60601-1 and IEC 60601-1-11. Passed all emission tests per IEC 62304 and Federal Register CFR 47 Part 15 subpart B. Passed Coexistence Immunity and Wireless Crosstalk tests per 27701:2019 and ANSI IEEE C63.27-2017. |
  | Software Performance | Software components function as intended and meet user needs. | All software components verified against System Requirements Specifications and system-level validated against user needs. All tests passed. |
  | Risk Management | Identified hazards are mitigated through risk controls. | Risk analysis performed per ISO 14971; risk controls implemented. Cybersecurity risks identified and addressed through penetration testing. |
  | Usability | Device is usable for intended users in intended environments. | Extensive Human Factor Engineering/Usability Engineering performed per IEC 62366-1 and FDA guidance; found substantially equivalent for intended users, uses, and environments. |

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

The clinical studies involved a total of 199 subjects.
The data provenance is from clinical studies conducted with patients in a neurorehabilitation ward and patients suspected of suffering from sleep apnea. The studies were prospective as patients were continuously monitored overnight.

Specific sample sizes for each comparison are:

• Neurorehabilitation ward patients: 59 patients for respiration rate (compared to respiratory effort belt), 32 patients for heart rate (compared to ECG).
• Patients suspected of sleep apnea: 105 patients for respiration rate, 73 patients for heart rate.
• etCO2 comparison: 35 participants.

The country of origin is not explicitly stated in the provided text.

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

The text indicates that some measurements were "manually scored by a healthcare professional" for the comparison with end-tidal CO2 (etCO2). However, it does not specify the number of experts involved or their specific qualifications (e.g., years of experience, specialty). For other comparisons (respiratory effort belt, ECG), the ground truth devices are referenced, but expert involvement in scoring those particular signals is not detailed beyond the etCO2 mention.

4. Adjudication Method for the Test Set

The text does not explicitly state an adjudication method (e.g., 2+1, 3+1). It implies that the comparator device measurements (e.g., respiratory effort belt, ECG, etCO2) served as the direct reference or "ground truth." For the "manually scored" etCO2 data, it's not clear if multiple healthcare professionals scored the data and an adjudication process was used.

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

An MRMC comparative effectiveness study was not explicitly mentioned or performed to assess improvement of human readers with AI assistance. The studies described are focused on the device's accuracy against established medical reference standards.

6. Standalone (Algorithm Only) Performance

Yes, the studies described are primarily standalone (algorithm only) performance evaluations. The Sleepiz One+ outputs (heart rate, respiration rate) were compared directly against reference devices (ECG, pulse oximetry, respiratory effort belt, nasal cannula, etCO2 measurements). While the device records and transmits data for healthcare professionals to view, the reported accuracy metrics are for the device's automated estimation of these vital signs.

7. Type of Ground Truth Used

The ground truth for the test set was established using:

• Established Medical Devices: Electrocardiography (ECG), pulse oximetry, respiratory effort belt, nasal cannula, and an FDA-cleared device for end-tidal CO2 (etCO2) measurements.
• Expert Scoring: For the etCO2 comparison, the ground truth was "manually scored by a healthcare professional."

Polysomnography devices (Somnotouch RESP (K140861), Nox A1 (K192469)) were used as comparator devices in the clinical studies, specifically using subsets of their channels for the performance assessment.

8. Sample Size for the Training Set

The document does not specify the sample size used for the training set for the Sleepiz One+ device's algorithms.

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

The document does not specify how the ground truth for the training set was established. It only describes the methodology for the performance evaluation (test set).

Ask a specific question about this device