(114 days)
Intended Use:
The intended use of the CAIg-STR exercise ECG analysis algorithm is to analyze multi-channel ECG waveforms acquired from a patient and produce measurements such as heart rate, detect ventricular arrhythmias, form representative beats, and calculate ST segment deviation (elevation or depression) and ST slope for review by a trained physician or clinician in determining a diagnosis. The measurements should not be used as a sole means for determining a patient's diagnosis.
Indications for Use:
The analysis algorithm is indicated for use in exercise ECG testing where the clinician decides to evaluate the electrocardiogram of patients at 10 years or older, as part of decisions regarding possible diagnosis, potential treatment, effectiveness of treatment or to rule out causes for symptoms. The analysis algorithm is not intended to be used as a physiological monitor.
The CAlg-STR Exercise ECG Analysis Algorithm is a software module which may be integrated into a stress exercise system. It is used to analyze ECG waveforms to find and classify heart beats to calculate heart rate, detect arrhythmias and calculate ST deviation and ST slope when an adult or pediatric patient is undergoing cardiac stress testing.
The exercise ECG Analysis Algorithm takes up to 16 ECG leads as input and provides analysis and measurements. The Exercise ECG Analysis Algorithm analyzes up to 3 leads of ECG waveforms to find and classify the heart beats and calculate heart rate. The beat classifications are then used to calculate arrhythmias. The beats with similar morphology are averaged to from representative beats for up to 16 leads. The representative beats are used to measure ST deviation and slope for up to 16 leads. Those measurements are used for display and report in the host device. The algorithm does not supply an interpretation of the data.
Here's a summary of the acceptance criteria and the study that proves the device meets them, based on the provided text:
CAlg-STR Exercise ECG Analysis Algorithm Performance Data
This device is a software module designed to analyze multi-channel ECG waveforms during cardiac stress testing to calculate heart rate, detect ventricular arrhythmias, form representative beats, and measure ST segment deviation and slope.
1. Table of Acceptance Criteria and Reported Device Performance
| Metric/Performance Standard | Acceptance Criteria (Set by ANSI/AAMI/ISO EC57:1988/(R)2008) | Reported Device Performance (CAlg-STR) |
|---|---|---|
| Overall Performance | Meet the requirements of ANSI/AAMI/ISO EC57:1988/(R)2008 | Performed consistently and meets the requirements of ANSI/AAMI/ISO EC57:1988/(R)2008 for testing and reporting performance results of cardiac rhythm and ST-segment measurement algorithms. |
| Cardiac Rhythm Measurement | Defined by ANSI/AAMI/ISO EC57:1988/(R)2008 | Met the requirements of the standard, demonstrating consistent performance. |
| ST-Segment Measurement (Deviation/Slope) | Defined by ANSI/AAMI/ISO EC57:1988/(R)2008 | Met the requirements of the standard, demonstrating consistent performance. |
Study Details:
The performance data demonstrated that the CAlg-STR Exercise ECG Analysis Algorithm met its design specifications by being tested against the ANSI/AAMI/ISO EC57:1988/(R)2008: Testing and reporting performance results of cardiac rhythm and ST-segment measurement algorithms standard.
2. Sample Size Used for the Test Set and Data Provenance
The provided text does not explicitly state the sample size used for the test set or the country of origin of the data. It indicates that the testing was conducted to prove adherence to a recognized international standard (ANSI/AAMI/ISO EC57:1988/(R)2008), which typically specifies the types and quantities of data required for such validation. The data provenance (retrospective or prospective) is also not mentioned.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications
The provided text does not specify the number or qualifications of experts used to establish the ground truth for the test set.
4. Adjudication Method for the Test Set
The provided text does not describe any adjudication method used for the test set.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
The provided text does not indicate that a multi-reader multi-case (MRMC) comparative effectiveness study was done, nor does it discuss the effect size of human readers improving with or without AI assistance. The device is described as an "analysis algorithm" that "produces measurements... for review by a trained physician or clinician," suggesting a standalone analysis component rather than an AI-assisted interpretation tool for human readers in a comparative study.
6. Standalone (Algorithm Only) Performance
Yes, a standalone performance evaluation was explicitly conducted. The text states: "The performance data demonstrated that the CAIg-STR Exercise ECG Analysis Algorithm meet with the design specifications of the algorithm." This implies the algorithm was tested on its own to determine if its outputs (heart rate, arrhythmia detection, ST deviation/slope) conformed to the established standard.
7. Type of Ground Truth Used
The ground truth was based on the requirements and specifications outlined in the ANSI/AAMI/ISO EC57:1988/(R)2008: Testing and reporting performance results of cardiac rhythm and ST-segment measurement algorithms standard. This standard typically defines methods for generating or validating reference measurements for ECG analysis. While not explicitly stated, it can be inferred that the ground truth for rhythm and ST-segment measurements would align with the established and accepted methodologies within this standard.
8. Sample Size for the Training Set
The provided text does not mention the sample size for any training set. As this is an older submission (2012), it's possible the algorithm was developed using more traditional signal processing techniques rather than contemporary machine learning that explicitly defines "training sets" in the same way.
9. How the Ground Truth for the Training Set Was Established
The provided text does not describe how the ground truth for any training set was established, as a training set is not explicitly mentioned. If the algorithm relies on specific parameters or rules, these would have likely been derived from expert knowledge, physiological models, and existing ECG data, rather than a labeled training set in the modern sense.
§ 870.2340 Electrocardiograph.
(a)
Identification. An electrocardiograph is a device used to process the electrical signal transmitted through two or more electrocardiograph electrodes and to produce a visual display of the electrical signal produced by the heart.(b)
Classification. Class II (performance standards).