(20 days)
ECScope 100 hand held, battery operated 12 channel electrocardiograph is intended to be used for the diagnosis of cardiovascular system complications. ECScope 100 will acquire and record 12 ECG leads simultaneously.
ECScope 100 is intended to be used by a licensed health care practitioner or under the direct supervision of a licensed health care practitioner in a hospital or health care environment. These measurements are not intended for a specific clinical diagnosis.
The clinical significance of the ECG tracings must be determined by the physician in conjunction with clinician's knowledge of patient, the results of physical examination and other clinical findings.
ECScone 100 is designed to acquire, display and record ECG signals from surface electrodes. The device consists of two basic components: the processing unit and the patient acquisition module.
ECScope 100 is a multi channel electrocardiograph for the simultaneous acquisition of the 12 ECG leads i.e L1, L2, L3, aVR, aVL, aVf, V1, V2, V3, V4, V5 & V6, featuring Display Unit, alphanumeric keyboard and an option to print the ECG data by transferring the image file to computer through USB key or USB Cable on A4 Sheet Paper or Direct Printing through connected printer.
ECScope 100 can record and store in its Database up to 30 ECG tests. Each ECG test can include patient data, doctor's information and ECG measurements. Stored ECG tests can be printed on the external printer by directly connecting the printer or by transferring data through USB cable/Key using a PC.
The provided 510(k) summary for the DyAnsys ECScope 100 ECG Monitor does not describe a study that establishes performance against acceptance criteria in the manner typically expected for AI/ML-driven medical devices.
Instead, this submission is for a traditional electrocardiograph device, and the "study" mentioned refers to performance testing against a regulatory standard. Therefore, many of the requested fields cannot be directly answered in the context of an "acceptance criteria and study" as applied to AI/ML device performance.
Here's the information that can be extracted and clarified:
1. Table of Acceptance Criteria and Reported Device Performance
The submission states: "Final testing for the product included various performance tests as per ANSI/AAMI EC11: 1991 Guidance Document." This implies that the acceptance criteria are adherence to the specifications outlined in this standard. It does not provide specific performance metrics like sensitivity, specificity, accuracy, or F1-score which are common for AI/ML devices.
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Adherence to ANSI/AAMI EC11: 1991 Guidance Document for Electrocardiographs | The device was subjected to safety and performance tests against regulatory standards and final testing included various performance tests as per ANSI/AAMI EC11: 1991 Guidance Document. (This statement implies successful adherence, as the device received 510(k) clearance). |
2. Sample Size Used for the Test Set and Data Provenance
Not applicable in the context of an AI/ML performance study. The testing refers to hardware and software functionality against a technical standard, not a dataset of patient cases.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of those Experts
Not applicable. Ground truth as typically defined for AI/ML models (e.g., expert consensus on clinical findings) is not mentioned or relevant to the performance testing described.
4. Adjudication Method for the Test Set
Not applicable. No adjudication method is mentioned for clinical interpretations, as the device is a data acquisition and display tool, not an interpretive AI.
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. This device is an electrocardiograph that acquires and displays ECG signals. It does not include AI for interpretation or assist human readers in a diagnostic capacity beyond presenting the raw ECG data. Therefore, an MRMC study related to AI assistance is not relevant to this submission.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
No, an algorithm-only standalone performance study is not mentioned. The device's primary function is to acquire and display ECG signals, with the interpretation left to a licensed healthcare practitioner.
7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, Etc.)
Not applicable in the context of an AI/ML performance study. The "ground truth" for this device's testing would be the physical and electrical specifications defined in the ANSI/AAMI EC11: 1991 standard.
8. The Sample Size for the Training Set
Not applicable. This submission is for a traditional medical device (ECG monitor) and does not involve AI/ML models that require a training set.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as no training set for an AI/ML model is mentioned.
§ 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).