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CER-S is a medical device stand-alone software intended for the analysis, editing, review and reporting of continuous ECG digital recordings, to support the clinician in the interpretation of the trace and the diagnosis of cardiac rhythm disorders in adult and pediatric patients.

CER-S is intended for use in clinical and hospital settings only by qualified medical personnel or adequately trained professional personnel working under the supervision and responsibility of a clinician. Users must undergo a thorough software training before using the medical device. This device does not provide an automated interpretation and is not intended for use as the only diagnostic tool.

CER-S analysis provides indications for evaluation of:

• Patients with rhythm disturbances (cardiac arrhythmias),
• Patients with transient myocardial ischemia,
• Patients with pacemaker (only if pacing detection is available from the input recording),
• Patients needing HRV evaluation.
• Newborn patients limited to QRS detection.

CER-S is a tool, designed to offer a framework for the interaction of different software-modules, providing advanced solutions for Continuous ECG Recording (CER).
Different modules provide:

• ECG Beat detection and classification,
• analysis of ECG rhythm, arrhythmia detection,
• interactive Viewer and set of tools to perform editing of ECG beats, Rhythm annotations and noise Windows,
• interactive Continuous ECG Viewer,
• interactive display/management of ECG Templates,
• holter-like report for analyzed Continuous ECG records,
• record exportation, in ISHNE format,
• generation of aECG FDA HL7 XML (v. 2).

Note: The automatic analysis is limited to data acquired from electrodes with conductive paste/gel (dry and dry/metal electrodes are not intended to be used) placed on standard location in compatible formats from any device used for the arrhythmia diagnostics such as Holter, event recorder, 12-lead ambulatory ECG devices when assessment of the rhythm is necessary.
Moreover, CER-S allows the automatic analysis for the following patch location:

• two-electrode patches positioned in the left upper chest area at a roughly inclined angle
• three-electrode triangular shape patches positioned on the patient's left upper chest area below the 1st rib, at an inclined angle
• three-electrode T-shaped patches positioned in the center-thoracic position between the upper part of the chest (manubrium) and the sternum
  In all cases, patch placement must strictly follow the indication provided by the manufacturer of the certified-patch device.

Here's a breakdown of the acceptance criteria and study information for the CER-S device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document (a 510(k) Premarket Notification) does not explicitly state acceptance criteria in terms of specific performance metrics with numerical thresholds (e.g., sensitivity > X%, specificity > Y%). Instead, it outlines the scope of performance testing and concludes that the device is "substantially equivalent" to its predicate and meets the relevant standards.

The document focuses on demonstrating that the device adheres to recognized industry standards and its performance is comparable to the predicate.

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

The document states: "No clinical tests were performed to demonstrate the substantial equivalence of CER-S." This implies that there isn't a "test set" in the traditional sense of a clinical dataset used to evaluate the device's diagnostic performance against a ground truth.

The performance evaluation relied on non-clinical tests against recognized standards rather than a clinical dataset with individual patient records. Therefore, information about sample size, country of origin, or retrospective/prospective nature of a clinical test set is not available in this document.

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

As there were no clinical tests performed with a ground truth established by experts, this information is not applicable/not available from the provided text.

4. Adjudication Method for the Test Set

Since no clinical test set was used with expert review, an adjudication method is not applicable/not available from the provided text.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of Human Improvement with AI vs. Without AI Assistance

The document explicitly states, "No clinical tests were performed to demonstrate the substantial equivalence of CER-S." Therefore, no MRMC comparative effectiveness study was conducted, and information about human reader improvement with AI assistance is not available. The CER-S is a standalone software, not an AI-assisted reading tool for human readers.

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

Yes, a standalone performance evaluation was done through non-clinical testing against recognized standards. The device itself is described as a "stand-alone software" intended to "support the clinician," not replace them, and explicitly states it "does not provide an automated interpretation and is not intended for use as the only diagnostic tool." The reported performance focused on compliance with ECG performance standards and software/risk management standards, indicating the algorithm's functionality and safety were evaluated.

7. The Type of Ground Truth Used

The "ground truth" for the non-clinical performance evaluation appears to be the requirements and specifications within the referenced industry standards (IEC 60601-2-47, IEC 60601-2-25 for ECG performance; IEC 62304 for software; IEC 62366-1 for usability; ISO 14971 for risk management). The device's algorithms and functions were tested to ensure they met the technical specifications and safety/performance criteria outlined by these standards, rather than a clinical ground truth like pathology or expert consensus on patient cases.

8. The Sample Size for the Training Set

The document does not provide information about the training set size for the CER-S algorithms. It mentions "Overall optimization of embedded algorithms for beat and noise detection, rhythm analysis and beat measurements," which implies an underlying development and training process, but no details are given.

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.

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CER-S is a stand-alone software medical device intended to analyze, edit, review and report digital continuous ECG recordings.

CER-S is intended for use in clinical and hospital settings only by qualified medical personnel or adequately trained professional personnel working under the supervision and responsibility of a clinician. Users must undergo a thorough software training before using the medical device.

The device provides the clinician an additional tool to aid in the interpretation of ECG data for diagnosis of heart rhythm disorders in adult and pediatric patients.

Note: This device does not provide an automated interpretation and is not intended for use as the only diagnostic tool.

CER-S analysis provides indications for evaluation of:

• Patients with rhythm disturbances (cardiac arrhythmias),
• Patients with transient myocardial ischemia,
• Patients with pacemaker (only if pacing detection is available from the input recording),
• Patients needing HRV evaluation,
• Newborn patients limited to QRS detection.

CER-S is a tool, designed to offer a framework for the interaction of different software-modules, providing advanced solutions for Continuous ECG Recording (CER). Different modules provide: ECG Beat detection and classification Analysis of ECG rhythm, arrhythmia detection interactive Viewer and set of tools to perform editing of ECG beats, Rhythm annotations and noise Windows interactive Continuous ECG Viewer interactive display/management of ECG Templates Holter-like report for analyzed Continuous ECG records, record exportation, in ISHNE format generation of aECG FDA HL7 XML (v. 2), for the submission of continuous ECG recording to the FDA ECG Warehouse. Note: The automatic analysis is limited to data acquired from electrodes with conductive paste/gel (dry and dry/metal electrodes are not intended to be used) placed on standard location in compatible formats from any device used for the arrhythmia diagnostics such as Holter, event recorder, 12-lead ambulatory ECG devices when assessment of the rhythm is necessary. Moreover, CER-S allows the automatic analysis for the following patch location: two-electrode patches positioned in the left upper chest area at a roughly inclined angle three-electrode triangular shape patches positioned on the patient's left upper chest area below the 1st rib, at an inclined angle three-electrode T-shaped patches positioned in the center-thoracic position between the upper part of the chest (manubrium) and the sternum In all cases, patch placement must strictly follow the indication provided by the manufacturer of the certified-patch device.

Here's a breakdown of the acceptance criteria and the study information for the CER-S device, based on the provided text:

Acceptance Criteria and Device Performance

The provided document does not explicitly present a table of acceptance criteria with corresponding device performance metrics in a quantitative format (e.g., sensitivity, specificity, accuracy thresholds). Instead, it states that "No clinical tests were performed to demonstrate the substantial equivalence of CER-S." The performance data section focuses on adherence to recognized standards and the demonstration of substantial equivalence to a predicate device.

However, the document lists improvements in performance over the predicate device, which can be interpreted as target performance goals for these specific aspects:

Study Details

The submission explicitly states: "No clinical tests were performed to demonstrate the substantial equivalence of CER-S." Therefore, the following sections will indicate "Not applicable" or detail the nature of the non-clinical tests conducted.

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

• Sample Size for Test Set: Not applicable (No clinical test set was used).
• Data Provenance: Not applicable (No clinical test set was used). Non-clinical tests were based on simulations and adherence to specified test standards.

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

• Not applicable (No clinical test set and thus no ground truth established by experts for performance evaluation).

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

• Not applicable (No clinical test set requiring adjudication).

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. A MRMC comparative effectiveness study was not performed. The device is described as a "stand-alone software medical device" that aids in interpretation and is "not intended for use as the only diagnostic tool."

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

• Yes. The improvements described, such as "beat detection in recordings with low amplitude and with noise" and "beat measures in recording with higher heart rate," relate to the standalone performance of the algorithm. These improvements were demonstrated through non-clinical tests by adhering to standards such as ANSI/AAMI EC57:1998/(R)2003 and IEC 60601-2-47:2012.

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

• For the non-clinical performance evaluation, the "ground truth" was established based on simulated data and standardized test methodologies defined by the referenced ECG performance testing standards (ANSI/AAMI EC57, IEC 60601-2-47, IEC 60601-2-25) to verify the algorithm's accuracy against known, controlled inputs.

8. The sample size for the training set:

• Not specified within the provided text. The document focuses on regulatory submission and does not detail the specifics of machine learning model training data.

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

• Not specified within the provided text.

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