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510(k) Data Aggregation
(92 days)
The CPRmeter™ 2 CPR Feedback Device is used as a guide in administering cardiopulmonary resuscitation (CPR) to a suspected sudden cardiac arrest (SCA) victim at least 8 years old.
The CPRmeter™ 2 is used as a guide in administering CPR to a suspected sudden cardiac arrest (SCA) victim at least 8 years old. The housing material of the CPRmeter™ 2 is composed of polycarbonate. It is small, lightweight and powered by a replaceable battery. The device is approximately 153 mm × 64 mm × 25 mm (6"× 2 ½"× 1") and weighs approximately 163 g (5.7 oz), excluding batteries. The device is approximately the size and weight of a cell phone. It is intended to be placed between the responder's hands and the patient's chest during CPR by means of a self-adhesive foam pad. The CPRmeter™ 2 is intended to be used by responders who have been trained in CPR and use of the CPRmeter™ 2. If the responder is in doubt about its appropriateness for use or the ability to use it. CPR is to be performed without using the CPRmeter™ 2 device.
When placed on the bare chest of a suspected SCA victim, the CPRmeter™ 2 provides real-time feedback on CPR compressions in accordance with current CPR guidelines. It displays CPR feedback indicators for depth, rate, and release of chest compressions. It also counts the number of compressions in a series and provides notification of lack of expected CPR activity. The CPRmeter™ 2 may be reused, provided proper cleaning procedures are performed after each patient use.
The CPRmeter™ 2 CPR Feedback Device's acceptance criteria and the study that proves it meets these criteria are detailed below. It is important to note that this device is not an AI-powered diagnostic tool, but rather a feedback device for CPR. Therefore, some of the requested information regarding AI-specific studies (e.g., MRMC studies, training set details, expert ground truth for training) are not applicable.
1. Table of Acceptance Criteria and Reported Device Performance
The acceptance criteria for the CPRmeter™ 2 are primarily based on its functionality in providing real-time feedback for CPR compressions according to current guidelines. The reported device performance is demonstrated through various verification and validation tests.
| Feature | Acceptance Criteria (Target) | Reported Device Performance (Demonstrated) |
|---|---|---|
| Depth Feedback | > 50 mm and < 60 mm | Demonstrated acceptable performance under simulated use conditions. |
| Rate Feedback | 100-120 per minute | Demonstrated acceptable performance under simulated use conditions. |
| Release Feedback | Residual force < 2.5 kg | Demonstrated acceptable performance under simulated use conditions. |
| Biocompatibility | Conformance to ISO 10993-1 | Demonstrated appropriate biocompatibility profile for patient-contacting parts. |
| Electrical Safety & EMC | Conformance to AAMI/ANSI ES 60601-1 and AAMI/ANSI/IEC 60601-1-2 | Demonstrated appropriate electrical safety and electromagnetic compatibility. |
| Environmental Stability | Withstand changes in ambient pressure, temperature, humidity | Demonstrated adequate ability to withstand these changes. |
| Shelf Life | Maintain acceptable performance at end of shelf life | Demonstrated acceptable performance at the end of its labeled shelf life. |
| Human Factors | Effective use by intended user | Validated that device design and labeling are sufficient for effective use. |
2. Sample size used for the test set and the data provenance
The provided document does not specify a distinct "test set" in the context of an AI/algorithm where a dataset is used to evaluate performance against ground truth. Instead, performance was evaluated through various engineering and simulated use tests. Therefore, details like sample size for a test set, country of origin, or retrospective/prospective nature of a dataset are not applicable as it's not a data-driven diagnostic AI. The "test sets" here refer to test scenarios and conditions under which the device's physical and functional properties were assessed.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. This device is not an AI/algorithm that makes diagnostic predictions or classifications requiring expert-established ground truth on a dataset. Its performance is based on its ability to accurately measure and provide feedback on physical parameters (compression depth, rate, release) which are objectively defined by CPR guidelines.
4. Adjudication method for the test set
Not applicable. As described above, there is no "test set" requiring adjudication by experts in the context of an AI/algorithm evaluation.
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
Not applicable. This device is a feedback tool for CPR, not an AI-powered diagnostic system that assists human readers in interpreting medical images or data. Therefore, an MRMC comparative effectiveness study is not relevant.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Yes, in a sense. The "standalone" performance of the CPRmeter™ 2 itself, independent of a human's CPR performance, was evaluated through nonclinical performance testing under simulated use conditions. This involved assessing its accuracy in measuring and reporting CPR parameters (depth, rate, release) mechanically or in controlled environments, demonstrating its ability to meet the specified targets. However, this is not an "algorithm-only" standalone performance in the context of a diagnostic AI, but rather the performance of the device's embedded measurement and feedback algorithms.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The "ground truth" for the CPRmeter™ 2's performance is based on objectively defined CPR guidelines for compression depth, rate, and release (e.g., depth > 50 mm and < 60 mm, rate 100-120 per minute, residual force < 2.5 kg). These are universally accepted standards for effective CPR. The device's accuracy in measuring these parameters under simulated conditions constitutes its performance against this "ground truth."
8. The sample size for the training set
Not applicable. The CPRmeter™ 2 is a hardware device with embedded firmware/algorithms based on physical principles (accelerometer and force sensor) and established CPR guidelines, not a machine learning model that requires a "training set" in the conventional AI sense.
9. How the ground truth for the training set was established
Not applicable, as there is no "training set" for this device in the context of AI/machine learning.
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