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Biofourmis Everion+ (G2) provides continuous monitoring of the following vital signs in adults, 18 years of age or older, when at rest:

• · Pulse rate
• · Respiration rate
• · Movement
• · Skin temperature

Biofourmis Everion+ (G2) also provides Blood oxygen saturation (SpO2) as a vital for continuous data collection in adults, 18 years of age or older, when at rest.

Biofourmis Everion+ (G2) is intended for use in a hospital or home environment to support monitoring of wearers under the care of a trained healthcare professional. Biofourmis Everion+ (G2) is not intended for use in a critical care environment such as an ICU or operating room. The device information should not be the sole basis for clinical decisions.

The Biofourmis Everion+ (G2) is a wireless multi-parameter vital-signs monitoring system. The Everion+ was includes an Application Programming Interface (API), which is intended to allow development of user interface applications that enable clinicians and medically-qualified personnel to access recorded vital signs information for patient monitoring.

The system is comprised of the following components:

• . Wearable device with multiple sensors
• . Secure cloud environment with an API
• Charger with accessories
• . Armband

The Everion+ G2 wearable is battery-operated with integrated sensors and wireless transceiver. The device is reusable and considered multi-patient use. After a healthcare professional (HCP) prescribes a device to a patient, they can clean the device according to the accompanying documentation for normal expected wear and buildup on the device. When the patient no longer needs the device for remote monitoring, the device can be returned to the HCP and undergo a low-level disinfection process, so it can be prescribed to a new patient.

The wearable is worn on the upper arm via the adjustable armband that snaps to it. The armband is made of a stretchy material and has an adjustable clip to enable fitting to most adults. The patient contacting components primarily involved in permanent contact are the bottom device housing and the armband. The wearable continuously gathers multiparameter vital signs data from the person being monitored and securely transmits the data to the server component of the system, via cellular communication, when in range of a third-party receiver. When not in range, the collected data is stored on the Everion+ G2 wearable and transmitted when connection has been restored. Through APIs of the cloud environment, the data may be accessed from the cloud storage or integrated into a third-party application for monitoring.

I am sorry, but the provided text from the FDA 510(k) submission does not contain the detailed information necessary to fully answer your request regarding the acceptance criteria and the study that proves the device meets them.

Specifically, the document lists:

• Indications for Use for the Biofourmis Everion+ (G2) for continuous monitoring of pulse rate, respiration rate, movement, skin temperature, and blood oxygen saturation (SpO2) in adults (18+) at rest in hospital or home environments.
• A Summary of Non-Clinical Tests indicating that the device met applicable standards for electrical, mechanical, thermal safety (IEC 60601-1), electromagnetic compatibility (IEC 60601-1-2, ANSI IEEE C63.27, AIM 7351731), packaging (ISTA 3A), biocompatibility (ISO 10993-1), and cleaning/disinfection (ISO 17664-2).
• A Summary of Animal & Clinical Studies mentions that SpO2 accuracy was assessed by comparing the device to arterial blood samples analyzed by CO-Oximetry, aiming for a root-mean-square (RMSE) comparison of no greater than 3.5% difference over a range of 70-100% SaO2, in accordance with ISO 80601-2-61 and FDA Guidance. It also mentions validation of skin temperature accuracy with laboratory test data per ISO 80601-2-56.

However, the document does not provide:

1. A table of specific acceptance criteria and the reported device performance for each vital sign, outside of the SpO2 RMSE target.
2. Sample sizes used for the test set (clinical studies) for SpO2, and other parameters like pulse rate, respiration rate, movement, or skin temperature. It only broadly mentions "multiple subjects."
3. Data provenance (country of origin, retrospective/prospective).
4. Number of experts and their qualifications for establishing ground truth.
5. Adjudication method.
6. Whether an MRMC comparative effectiveness study was done, or any effect size of human readers improving with AI assistance.
7. Whether a standalone (algorithm only) performance was done.
8. Type of ground truth for all parameters (beyond CO-Oximetry for SpO2, and "corresponding FDA cleared reference devices" generally).
9. Sample size for the training set.
10. How the ground truth for the training set was established.

The provided text focuses on demonstrating substantial equivalence to predicate devices and general compliance with regulatory standards, rather than a detailed breakdown of specific performance study results against defined acceptance criteria for each monitored parameter.

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Everion+ provides continuous monitoring of the following vital signs in adults, 18 years of age or older, when at rest:

• Pulse rate
• Respiration rate
• Movement
  The data from Everion+ is intended to be used in a hospital or home environment in order to support monitoring of wearers under the care of a trained healthcare professional. Everion+ is not intended for use in a critical care environment such as an ICU or operating room. The device information should not be the sole basis for clinical decisions.

The Everion+ is a wireless multi-parameter vital-signs monitoring system. The Everion+ was includes an Application Programming Interface (API), which is intended to allow development of user interface applications that enable clinicians and medically-qualified personnel to access recorded vital signs information for active patient monitoring.
The system is comprised of the following components:

• Wearable device with multiple sensors
• Secure cloud environment with an API .
• Charger with accessories .
• Armband .
  The Everion+ wearable is battery-operated with integrated sensors and wireless transceiver. The wearable is worn on the upper arm via the adjustable armband that snaps to it. The armband is made of a stretchy material and has an adjustable clip to enable fitting to most adults. The wearable continuously gathers multi-parameter vital signs data from the person being monitored and securely transmits the data to the server component of the system, via cellular communication, when in range of a third-party receiver.

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

1. Table of Acceptance Criteria and Reported Device Performance

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The Biovitals Analytic Engine (BA Engine) is intended to be used with continuous biometric data from already cleared sensors measuring heart rate, respiratory rate, and activity in ambulatory patients being monitored in a healthcare facility or at home, during periods of minimal activity. The device learns the correlation between multiple vital signs during the patient's daily activity and builds an individualized biometric signature which is dynamically updated based on incoming data. The device computes a time series Biovitals Index (BI), which reflects changes in the patient's measured vital signs from their measured baseline, which is derived from the individualized biometric signature of the patient.

The BA Engine is a cloud-based software engine, intended to be an adjunct to and is not intended to replace vital signs monitoring. The BI is intended for daily intermittent, retrospective review by a qualified practitioner. The BA Engine is intended to provide additional information for use during routine patient monitoring. The BI is not intended for making clinical decisions regarding patient treatment or for diagnostic purposes.

The device is intended for an adult population.

Biovitals Analytics Engine consists of:

• An automated proprietary algorithm to analyze data and generate Biovitals Index.
• A cloud-based database to store the input, intermedium output and the final output
• A web application programming interface (API) which handle the continuous physiology data.
• A web application programming interface (API) query the databases and get output.
• A web dashboard to render the BA Engine output in a continuous graph format, which can help intended users to monitor a patient's Biovitals Index.

Biovitals Analytics Engine works in the following sequence:

• Accept input data via secure API;
• Analyze the input data using Biovitals Analytics Engine proprietary algorithm, which generate Biovitals Index:
• Personal physiology signature data base initialization (at the early stage on the algorithm when the engine learns the patients and builds the personal baseline)
• Biovitals Index calculation
• Biovitals Analytics engine generates the Biovitals Index which is a time series scalar value from 0 to 1.
• The output of BA Engine is stored in a cloud-based database.
• The output API queries the databases and gets the output, and the output shall be reviewed by the qualified practitioner via a dashboard.

The Biovitals Analytics Engine (BA Engine) computes a time series Biovitals Index (BI) that reflects changes in a patient's vital signs from their measured baseline. The device's performance was evaluated through clinical testing to show its correlation with changes in the relationship among vital sign parameters as assessed by a panel of physicians.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: 50 subjects.
• Data Provenance: The subjects were patients presenting at an Emergency Department and were deemed appropriate for home monitoring. The document does not specify the country of origin, but given the FDA review, it is likely from the US, or data collected in a manner suitable for US regulatory submission. The study appears to be prospective as it describes patients presenting at an ED and being monitored.

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

• Number of Experts: A panel of three physicians.
• Qualifications: The document only states "a panel of three physicians" and does not provide specific qualifications (e.g., years of experience, sub-specialty).

4. Adjudication Method for the Test Set

• The document states that the performance was compared "against a panel of three physicians evaluating the changes in the relationship among the patients' vital sign parameters." This implies a consensus or majority opinion (e.g., 2+1, where at least two physicians agree). However, the specific adjudication method (e.g., 2+1, 3+1, none) is not explicitly stated.

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

• No, a formal MRMC comparative effectiveness study was not explicitly described for evaluating how human readers improve with AI vs. without AI assistance. The study described focuses on the standalone performance of the BI in correlating with physician assessments of vital sign changes, rather than comparing human reader performance with and without AI assistance. The device is intended as an "adjunct" for "daily intermittent, retrospective review," suggesting it provides additional information to a practitioner, which could imply human-in-the-loop, but the study design does not directly evaluate this human improvement.

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

• Yes, a standalone performance evaluation of the algorithm was conducted. The study evaluated the Biovitals Index (BI) directly against the assessment of a panel of physicians. The PPA (Positive Percent Agreement) of the BI itself was measured against the physician panel's assessment, indicating a standalone performance evaluation.

7. The Type of Ground Truth Used

• The ground truth used was expert consensus / clinical assessment from a panel of three physicians. They evaluated the "changes in the relationship among the patients' vital sign parameters."

8. The Sample Size for the Training Set

• The document does not specify the sample size used for the training set. It only describes the methodology for establishing the personalized baseline: "The baseline is initially established using data from the first 24 hours and updated periodically as new data is received." And for the within-subject variability calculation: "The expected within-subject variability was computed using data from a clinical study involving 50 emergency department patients that were deemed appropriate for home monitoring." This suggests the 50 patients mentioned for the test set might also be involved in data used for variability computation, but it doesn't describe the training set for the core algorithm that generates the BI.

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

• The document does not explicitly describe how ground truth (or the equivalent "gold standard") for the training set was established. Instead, it explains how the BA Engine "learns the correlation between multiple vital signs during the patient's daily activity and builds an individualized biometric signature which is dynamically updated based on incoming data." This is described as a personalized, dynamic baseline for each patient, rather than a pre-established, universal ground truth from a large training dataset. The algorithm "learns" from the individual patient's own physiological data to establish their personal baseline.

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RhythmAnalytics is a software application for the assessment of cardiac arrhythmias using single-lead ECG data in subjects over 18 years of age. It is intended for use by a healthcare solution integrator to build web or mobile applications to let qualified healthcare professionals review and confirm the analytic result. The product supports downloading and analysing data recorded in compatible formats from any FDA cleared device used for the arrhythmia diagnostics such as Holter, event recorder, or other similar devices when of the rhythm is necessary. RhythmAnalytics can also be electronically interfaced, and perform analysis with data transferred from other computer based ECG systems, such as an ECG management system. RhythmAnalytics provides ECG signal processing and analysis, QRS and Ventricular Ectopic Beat detection, QRS feature extraction, interval measurement, heart rate measurement, and rhythm analysis. RhythmAnalytics is not for use in life supporting or sustaining systems or ECG monitor and Alarm devices.

The product can be integrated into medical devices. In this case, the medical device manufacturer will identify the indication for use depending on the application of their device.

RhythmAnalytics interpretation results are not intended to be the sole means of diagnosis. It is offered to physicians and clinicians on an advisory basis only in conjunction with the physician's knowledge of ECG patterns, patient background, clinical history, symptoms, and other diagnostic information.

RhythmAnalytics consists of (1) A web application programming interface (API) which an authentic user to upload single-lead ECG data and reports ECG interpretation results, and (2) An automated proprietary algorithm, i.e., cardiac beats/arrhythmias detection which measures and analyzes ECG data to provide qualified healthcare professional supportive information for review.

RhythmAnalytics is only intended to analyze recordings performed on adults (over the age of 18). RhythmAnalytics works in the following sequence:

• Accept uploading digital ECG files via secure API;
• Analyse the uploaded ECG using RhythmAnalytics proprietary algorithm, which detects cardiac beats/arrhythmias and intervals including:
  • Heart rate determination
  • RR Interval measurements
• ORS
• Non-paced arrhythmias
• Non-paced ventricular arrhythmia calls
• Ventricular ectopic beats
• RhythmAnalytics returns the interpretation result to be reviewed by a qualified healthcare professional.

The provided text describes the RhythmAnalytics device and its clearance by the FDA. Let's break down the information to address your specific questions about acceptance criteria and the study proving the device meets them.

Acceptance Criteria and Reported Device Performance

The document doesn't explicitly present a table of acceptance criteria with specific numerical thresholds for metrics like sensitivity or specificity side-by-side with reported performance. Instead, it states that "Performance testing included the evaluation of sensitivity, specificity, and positive and negative values. All clinical input requirements were validated against a gold standard." It also mentions "No residual anomalies appeared during verification and software validation tests." and that "All software validation testing was completed successfully and met all requirements."

While the document confirms these metrics were evaluated and requirements were met, it does not provide the specific numerical acceptance criteria (e.g., "Sensitivity must be >90%") nor the reported numerical performance values (e.g., "Achieved Sensitivity: 92%").

Therefore, for question 1, I can only state what the document says was evaluated, but not the specific quantitative details.

Let's address the remaining questions based on the provided text:

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

The document does not explicitly state the sample size used for the test set for performance evaluation (sensitivity, specificity, etc.) nor does it specify the data provenance (country of origin, retrospective/prospective). It only mentions "All clinical input requirements were validated against a gold standard."

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

The document does not provide information on the number of experts used to establish the ground truth for the test set, nor their specific qualifications. It only states that validation was performed "against a gold standard."

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

The document does not specify any adjudication method used for establishing the ground truth of the test set. It only refers to a "gold standard."

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

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study. The device is described as providing "supportive information for review" to "qualified healthcare professionals" and its interpretation results "are not intended to be the sole means of diagnosis." This suggests it's an assistive tool, but no study on human-AI collaboration performance or effect size is detailed.

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

Yes, a standalone performance evaluation was done. The "Summary of Performance Testing" section states, "Performance testing included the evaluation of sensitivity, specificity, and positive and negative values. All clinical input requirements were validated against a gold standard." This indicates the algorithm's performance was assessed independently against a "gold standard."

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

The document explicitly states that "All clinical input requirements were validated against a gold standard." However, it does not specify the precise nature of this "gold standard" (e.g., whether it was expert consensus, pathology, or another form of definitive diagnosis).

8. The sample size for the training set

The document does not provide the sample size used for the training set of the proprietary algorithm.

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

The document does not describe how the ground truth for the training set was established. It only refers to the algorithm as an "automated proprietary algorithm, i.e., cardiac beats/arrhythmias detection which measures and analyses ECG data."

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