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The CardioTag device is a tool that can be used to record, display and transfer vibrational waveforms produced by the heart contractions and transmitted to the chest as well as single-channel electrocardiogram (ECG) rhythms and heart rate. It also measures pulse waveform and pulse rate by photoplethysmograph (PPG). The CardioTag may be used as a tool to measure the timing of the aortic valve opening and closing in the cardiac cycle. The CardioTag is intended for spot-checking of adult patients in clinics or at home under the care of a physician. The data from the CardioTag is intended for use by healthcare professionals as an aid to diagnosis and treatment.

The CardioTag device consists of a rechargeable wearable that is responsible for collecting raw cardiac signals from a single patient, and produces a spot-check report of a patient's electrocardiogram (ECG), photoplethysmogram (PPG), and seismocardiogram (SCG) signals and heart rate. To generate the report, the user places the wearable on the sternum and starts a 2 minute recording session for waveform output and heart rate /pulse rate calculation. The wearable contains electrodes to measure single-lead ECG, light sources and optical sensor arrays to measure PPG, and an accelerometer to measure vibrational waveforms from the heart's contractions transferred to the chest wall (SCG). Sensor data is then transferred for storage and processing to a cloud-based backend). The backend uses the recording to calculate heart rate and pulse rate and then visualizes the waveforms and heart rate in the format of a downloadable PDF report for the clinician. The SCG signal is intended to be used for manual interpretation by the clinician in conjunction with other information from the device. The device may be used as a tool to measure the timing of the aortic valve opening and closing in the cardiac cycle.

The provided FDA 510(k) clearance letter and supporting documentation for the CardioTag device does not contain enough information to fully answer all aspects of the acceptance criteria and study design, specifically regarding the detailed performance metrics, sample sizes for test and training sets, expert adjudication details, and the specific ground truth establishment methods.

However, I can extract and infer information from the available text to address as many points as possible.

Here's a breakdown of the acceptance criteria and study details based on the provided document:

Acceptance Criteria and Device Performance

The document states that "The primary endpoints for the CardioTag study were all met. The study results demonstrated that the CardioTag performs at an acceptable level when compared to commercially available devices with high accuracy." While this confirms the device met its performance criteria, the specific metrics and numerical targets are not explicitly stated in the provided text.

Based on the device's functions, the implied acceptance criteria would relate to the accuracy of:

• ECG waveform recording and display
• Heart rate calculation (from ECG)
• PPG waveform recording and display
• Pulse rate calculation (from PPG)
• SCG waveform recording and display
• Measurement of aortic valve opening and closing timing (from SCG)

Since the document states "The primary endpoints for the CardioTag study were all met," we can infer that the reported device performance met or exceeded the (unspecified) acceptance thresholds for these functions, demonstrating high accuracy when compared to commercially available devices.

Table of Acceptance Criteria and Reported Device Performance (Inferred/General)

Study Proving Device Meets Acceptance Criteria

The document describes a clinical study that was conducted to validate the CardioTag device.

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

   • Test Set Sample Size: The exact numerical sample size for the clinical study is not specified in the provided document. It only states, "The CardioTag device has been clinically tested and validated in the US."
   • Data Provenance: The data was collected from subjects recruited in the US. The study was prospective as it involved recruiting subjects for clinical testing. It also states, "subjects were recruited based on US demographics to present proper race and ethnicity to ensure diverse representation."

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

   • The document does not specify the number of experts or their qualifications used to establish ground truth for the clinical study. It only mentions that the data is "intended for use by healthcare professionals as an aid to diagnosis and treatment" and the SCG signal is for "manual interpretation by the clinician." This implies that expert interpretation would be crucial for ground truth, but the details are missing.

3. Adjudication Method for the Test Set:

   • The document does not specify any adjudication method (e.g., 2+1, 3+1, none) used for the test set.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • The document does not mention a specific MRMC comparative effectiveness study. The study "compared [CardioTag] to commercially available devices" to demonstrate accuracy, which suggests a comparative element, but not necessarily an MRMC study assessing human reader performance with and without AI assistance.
   • Therefore, no effect size for human reader improvement with AI vs. without AI assistance is reported in this document.

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

   • The document does not explicitly describe a standalone algorithm-only performance study. The description of the device heavily emphasizes the output for "manual interpretation by the clinician" and "aid to diagnosis and treatment by healthcare professionals," suggesting a human-in-the-loop workflow.
   • However, the validation of "ECG Validation," "PPG Validation," and "SCG Validation" in the performance testing section, which were "Bench-testing (non-clinical)," might imply a component of standalone algorithm evaluation of signal quality and derived parameters. The clinical study, by nature of validating against commercially available devices, would involve the device's outputs without necessarily detailing a separate "algorithm only" performance metric without human review.

6. Type of Ground Truth Used:

   • The document implies that ground truth was established by comparison to "commercially available devices" which served as the reference standard. This suggests a clinical comparator ground truth rather than pathology or long-term outcomes data. For parameters like heart rate and pulse rate, the ground truth would likely come from validated measurements by the comparator devices. For waveform interpretation (ECG, SCG), expert consensus or comparison to gold-standard clinical systems would be the likely ground truth, though not explicitly stated.

7. Sample Size for the Training Set:

   • The document does not specify the sample size used for the training set.

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

   • The document does not specify how ground truth for the training set was established. Given the nature of a 510(k) submission, this information might be in a more detailed study report not included in this summary.

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CorSens Device records vibrational waveforms produced by the heart contractions and transmitted to the chest wall. CorSens Device may be used as a tool to measure the timing of part of the cardiac cycle for adult population.

CorSens Device senses and analyzes the mechanical movement of the heart. This is accomplished by 3 standard ECG electrodes for the ECG signal and with a suitable miniature electronic accelerometer for the mechanical motions.

The CorSens Device, a Ballistocardiograph, records vibrational waveforms produced by heart contractions to measure the timing of part of the cardiac cycle in adults.

Here's an analysis of its acceptance criteria and the supporting study:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria in a table format. However, it indicates a high-level performance expectation and makes a direct comparison to an established clinical method.

2. Sample Size and Data Provenance for Test Set

The provided document does not explicitly detail a specific 'test set' with a defined sample size for a clinical study comparing the CorSens Device to an echocardiogram. It refers to a "comparison test" with echocardiogram, stating: "In addition to the verification and validation testing, a comparison test with the current common clinical practice to measure the timing of the events in the cardiac cycle, an Echocardiogram, was conducted."

Without further information, the specific sample size, country of origin, or whether the data was retrospective or prospective cannot be determined from this document.

3. Number and Qualifications of Experts for Ground Truth

The document does not specify the number or qualifications of experts used to establish ground truth for any test set. The ground truth (echocardiogram measurements) would typically be established by trained sonographers and/or cardiologists.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method for the comparison test with echocardiogram.

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

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study. Therefore, information on the effect size of human readers improving with or without AI assistance is not applicable or provided.

6. Standalone (Algorithm Only) Performance Study

The document indicates that "the proposed CorSens Device safety and the efficacy of the system were established by performance lab tests and Software V&V." While this suggests evaluation of the device's technical performance in isolation, it does not specifically describe a 'standalone (algorithm only without human-in-the-loop performance)' study in the way it might be discussed for an AI-driven diagnostic algorithm. The device is a measurement tool, and its 'performance' inherently involves its ability to capture and process data to produce timing measurements.

7. Type of Ground Truth Used

For the comparison test, the ground truth used was echocardiogram. The text explicitly states: "a comparison test with the current common clinical practice to measure the timing of the events in the cardiac cycle, an Echocardiogram, was conducted."

8. Sample Size for the Training Set

The document does not mention any specific training set or its sample size. This implies that the device's core functionality does not rely on a machine learning model that requires a discrete training phase with labeled data in the way many contemporary AI devices do. The device's operation is based on established biophysical principles of measuring vibrational waveforms.

9. How Ground Truth for the Training Set Was Established

Since no training set is mentioned as part of the device's development or validation process in this document, the method for establishing its ground truth is not applicable or provided. The device likely operates on fixed algorithms rather than a trained machine learning model.

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The dBG 300 records vibrational waveforms produced by the hearts contractions and transmitted to the chest wall. The dBG 300 may be used as a tool to measure the timing of the events in the cardiac cycle.

The Heart Force Ballistocardiograph senses and analyzes the mechanical movement of the heart. This is accomplished with 2 or 3 standard ECG electrodes for the ECG signal and with a suitable miniature electronic accelerometer for the mechanical motion.

The provided text describes the 510(k) summary for the dBG 300 Digital Ballistocardiograph, but it does not contain acceptance criteria or detailed study results that prove the device meets specific performance metrics.

The document discusses substantial equivalence to a predicate device (Seismed SCG-2000 Seismocardiograph) and mentions clinical data collected to compare cardiac event timings with an echocardiograph. However, it does not provide the specifics of this clinical data in a way that allows for a comprehensive description of acceptance criteria and a study proving their fulfillment.

Therefore, I cannot fulfill all parts of your request with the information provided. I can, however, extract what is available regarding clinical data and ground truth establishment:

Missing Information

The provided text does not contain the following information:

• A table of acceptance criteria or specific reported device performance metrics (e.g., accuracy, precision, sensitivity, specificity, agreement thresholds).
• Sample size used for the test set.
• Number of experts used to establish ground truth for the test set or their qualifications.
• Adjudication method for the test set.
• Whether a multi-reader multi-case (MRMC) comparative effectiveness study was done, or any effect size for human readers with/without AI assistance.
• If a standalone (algorithm only) performance study was done with specific results.
• Sample size for the training set.
• How the ground truth for the training set was established.

Available Information Related to Studies and Ground Truth

While specific acceptance criteria and detailed study results are absent, the document does mention a clinical study and the type of ground truth used:

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

   • Information not available: Specific acceptance criteria (e.g., "timing measurements must be within X ms of echocardiograph measurements") and quantitative reported device performance against such criteria are not provided.
   • The document implies that "equivalent intended use, manufacturing materials, operating principles, physical and operational specifications" to the predicate device (Seismed SCG-2000) serve as a basis for substantial equivalence, rather than direct performance metrics against specific criteria.

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

   • Information not available: The exact sample size for the clinical data is not specified.
   • Data provenance: "clinical data collected to compare the subjects device's finding of the times of occurrence of cardiac events such as aortic valve opening or closing with that of an echocardiograph." This implies prospective data collection for comparison. The country of origin is not explicitly stated for the clinical data itself, though the submitter is from Canada and the regulatory correspondent from the US.

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

   • Information not available: This detail is not provided.

4. Adjudication method for the test set:

   • Information not available: This detail is not provided.

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: The device is described as a tool to measure timing events; there is no mention of an "AI" component or human-in-the-loop performance improvement study in the context of MRMC. The document predates widespread AI in medical devices (2009).

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

   • Implied: The comparison to echocardiograph measurements suggests a standalone performance evaluation of the device's ability to measure cardiac event timings. However, specific performance metrics or detailed study design for this "standalone" evaluation are not provided.

7. The type of ground truth used:

   • Ground truth type: The clinical data compares the dBG 300's findings with "that of an echocardiograph." Therefore, echocardiography serves as the ground truth for measuring the timing of cardiac events (e.g., aortic valve opening or closing).

8. The sample size for the training set:

   • Information not available: No explicit mention of a separate "training set" or its size is made, suggesting a traditional device validation approach rather than an AI/machine learning model.

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

   • Information not available: Given the lack of an explicit training set, this information is not provided.

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