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The Nuubo System is indicated for use on patients who may be asymptomatic or who may suffer from transient symptoms such as palpitations, shortness of breath, dizziness, light-headedness, presyncope, syncope, fatigue, or anxiety.

The Nuubo system continuously records and stores ECG and activity data for up to 30 days at a time. The Nuubo System detects arrhythmias at the end of the monitoring period upon download of the ECG data. The Nuubo System is Rx use device.

The Nuubo System, developed by Smart Solutions Technologies (SST), is a wearable device designed for ambulatory recording electrocardiogram (ECG) up to 30 days. The system is composed of 3 main components:

• Nuubo30 – The Nuubo30 wearable is a single patient textile like a chest-belt that contains 4 textile electrodes in the inner side that are used for sensing patient 's ECG.
• NuuboREC - The Nuubo recorder is a small, lightweight device that records ECG continuously. The device records 2 Leads of ECG data up to 30 days. The device also records data from a 3-axis accelerometer located inside the device.
• Nuubo Leonardo - The Leonardo Software is installed on a computer where the patient´s ECG data stored in the recorder will be downloaded for subsequent analysis and report.

This document is a 510(k) summary for the Nuubo System, submitted to the FDA. It details the device's indications for use, technological characteristics, and performance data to demonstrate substantial equivalence to a predicate device.

Here's an analysis based on the provided information:

1. Table of Acceptance Criteria and Reported Device Performance

The document explicitly states that "The results obtained validate the Nuubo Arrhythmia Algorithms and prove equivalence to Monebo Automated ECG Analysis And Interpretation Software Library, version 3.0 [manufacturer Monebo Technologies, 510(k) number K062282]." It further mentions that "All results are comparable to the results claimed by Monebo."

While specific numerical acceptance criteria (e.g., minimum sensitivity/specificity for each arrhythmia) and the Nuubo System's reported performance for each criterion are not directly listed in the provided text, the document indicates that the device's arrhythmia detection performance was validated and found comparable to the Monebo device, which was referenced by the predicate ZioPatch. The table below lists the arrhythmia functionalities and their detection criteria, implying these are the targets for the algorithm:

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

The arrhythmia detection algorithms were tested using:

• Public Databases: MIT-BIH, AHA, and MITAF. These are well-known, established retrospective ECG databases. The country of origin for these databases is primarily the United States.
• Private Database: Comprised of 90 ECG registries from 58 patients. The provenance (country of origin) is not explicitly stated, but the context of the submission to the FDA suggests it aligns with U.S. medical practice. This data is described as "anonymized," potentially retrospective, selected to contain all arrhythmias detected by the algorithm.

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

For the private database (90 ECG registries from 58 patients), the ground truth was established by "experienced medical professionals." The specific number of experts is not provided, nor are their detailed qualifications (e.g., specific sub-specialty or years of experience). For the public databases (MIT-BIH, AHA, MITAF), ground truth is typically established by consensus of multiple cardiologists or electrophysiologists based on established annotation guidelines, though the document doesn't detail this for these specific databases.

4. Adjudication Method for the Test Set

The document states that the private database "was annotated using experienced medical professionals, using prospectively defined guidelines, consistent with US medical practice." This suggests an expert review process. However, the exact adjudication method (e.g., 2+1, 3+1, or simple consensus from a single annotator if a single expert annotated) is not specified. For the public databases, adjudication methods are usually defined by the database creators, often involving multiple experts to establish consensus.

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 MRMC comparative effectiveness study involving human readers' improvement with AI vs. without AI assistance is reported in this document. The study focuses on the standalone performance of the algorithm.

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

Yes, a standalone performance study of the algorithm was done. The document states: "The Nuubo Arrhythmia detection algorithm was tested per requirements of AAMI/IEC60601-2-47. To validate the arrhythmia detection algorithms were used three public databases and one private database." The results of this testing were compared to the performance claimed by the Monebo Automated ECG Analysis And Interpretation Software Library (K062282), indicating a standalone comparison. The caveat is that "The Nuubo Arrhythmia Detection Algorithm is not intended to replace the Clinician review of signals. The software menu prompts the Clinician or trained technician to review events prior to generating a report," which implies that the intended use is with a human-in-the-loop for final review, even if standalone performance was tested.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The type of ground truth used for the private database was expert annotation/consensus based on "experienced medical professionals, using prospectively defined guidelines." For the public databases (MIT-BIH, AHA, MITAF), the ground truth is also based on expert annotation (often expert consensus).

8. The Sample Size for the Training Set

The document does not explicitly state the sample size used for the training set for the Nuubo arrhythmia detection algorithm. It only mentions the databases used for validation/testing.

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

Since the training set size and specific databases are not mentioned, how the ground truth for any training set was established is also not described in this document. The description of ground truth establishment is specifically for the test/validation data.

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The Zargis Acoustic Cardioscan, (ZAC) is an electronic auscultatory device, intended to provide support to the physician in the evaluation of heart sounds in patients.

The product will acquire and record the acoustic signals of the heart and analyze these signals. The analysis procedure will identify specific heart sounds. that may be present. Identified sounds include S1, S2, and suspected murmurs.

The device is indicated for use in a clinical setting, by a physician or by trained personnel who are acting on the orders of a licensed physician. It is not intended as a sole means of diagnosis.

The interpretations of heart sounds offered by the Zargis Acoustic Cardioscan are only significant when used in conjunction with physician over-read as well as consideration of all other relevant patient data.

The ZAC is an electronic auscultatory device intended to acquire, record, and analyze heart sounds.

The complete system is a CD comprising software and instructions for use with an included USB transceiver for connection with a PC and capable of wireless communication with a Bluetooth-enabled electronic stethoscope.

Here's an analysis of the acceptance criteria and study information for the Zargis Acoustic Cardioscan (ZAC), based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The provided document (K083309) is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed acceptance criteria and performance metrics for a novel technology. Therefore, specific quantitative acceptance criteria (e.g., sensitivity, specificity thresholds) and corresponding numerical performance results are not explicitly stated in this document.

The document broadly states: "non-clinical performance testing has been conducted to demonstrate the performance of the modified ZAC device and that it meets its intended use." and "A clinical software validation was performed to insure the performance of the enhanced software algorithm."

Based on the limited information, we can infer the implied performance goal is to "identify specific heart sounds that may be present. Identified sounds include S1, S2, and suspected murmurs." However, no specific metrics for the accuracy of this identification are provided.

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

• Sample Size for Test Set: Not explicitly stated. The document mentions "A clinical software validation was performed," but does not provide the number of cases or patients included in this validation.
• Data Provenance: Not explicitly stated. The document does not mention the country of origin of the data or whether it was retrospective or prospective.

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

• Number of Experts: Not explicitly stated.
• Qualifications of Experts: Not explicitly stated. The device's intended use emphasizes "physician over-read" and "consideration of all other relevant patient data," implying medical professionals are involved in the overall diagnostic process, but their role in establishing ground truth for the validation study is not detailed.

4. Adjudication Method for the Test Set:

• Adjudication Method: Not explicitly stated. The document does not describe how discrepancies in ground truth or interpretation were resolved, if multiple experts were involved.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance:

• MRMC Study: The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study.
• Effect Size: Therefore, no effect size of human readers improving with AI assistance is provided. The device is intended to "provide support to the physician" and is "not intended as a sole means of diagnosis," requiring "physician over-read." This implies human-in-the-loop, but a comparative study assessing its impact is not described.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

• Standalone Performance Study: The document does not explicitly present standalone (algorithm-only) performance metrics such as sensitivity or specificity. While "analysis procedure will identify specific heart sounds," the performance of this identification in isolation is not separately quantified. The emphasis is on its use "in conjunction with physician over-read."

7. The Type of Ground Truth Used:

• Type of Ground Truth: Not explicitly stated. Given the nature of heart sound analysis, it's highly probable that the ground truth would have been established by expert clinical assessment (e.g., cardiologists interpreting auscultation, possibly combined with other diagnostic tests like echocardiography), but this is an inference, not a direct statement from the document.

8. The Sample Size for the Training Set:

• Sample Size for Training Set: Not mentioned or provided in the document.

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

• Ground Truth for Training Set Establishment: Not mentioned or provided in the document.

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