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To power AEDs for which the OEM battery pack was intended. Only qualified service personnel should evaluate, test, or install AED battery packs.

To provide power for the specific Automated External Defibrillators (AEDs) for which the original battery packs were designed and manufactured, in back-up and portable use.

The Green4Life Batteries are non-rechargeable battery packs utilized as the primary power source or as a standby or backup power source for Automated External Defibrillators (AEDs). These devices provide a means of supplying electrical power through the chemical reaction of lithium cells. The energy provided depends upon the voltage and capacity rating of a particular pack and the amount of current required by the device into which they are installed. The performance and life span of these batteries depends on operating conditions of temperature, current drain, and discharge method. The goal of these battery packs is to provide a sufficient power source for AEDs for as long as possible under a specified range of environmental conditions.

The Green4Life Batteries are re-celled battery packs of those identified below in Predicate Devices.

Here's a breakdown of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Additional Acceptance Criteria:

• Ease of Installation: Battery pack must easily install into the AED and firmly lock into place as with the original battery pack.
• AED Self-Test Result: Upon installation, the AEDs undergo an operational self-test of the installed battery, and the final battery pack acceptance testing requires a reported "pass" by the corresponding AED.

Reported Device Performance: The document states, "The Green4Life Battery packs are re-celled packs manufactured as cleared devices... Performance testing within the specific AED was conducted to verify that the replacement battery pack tested within limits and that reset of battery pack information when operated within the designated AED, for those packs equipped with memory devices, was acceptable." It also states, "Final battery pack acceptance testing requires a reported 'pass' by the corresponding AED." This implies that all stated acceptance criteria were met.

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

• Sample Size: The document does not explicitly state a specific numerical sample size for the "Performance Testing" or "Manufacturing Tests," but it implies testing each battery pack. It mentions "typical sampling plans for similar devices" for incoming inspection of lithium cells, and "100% testing" for assembled packs. For the final acceptance test, "the battery packs will be installed into their corresponding AED for a final acceptance test." This suggests that a representative number of each re-celled battery model were tested.
• Data Provenance: The testing was conducted by AED Battery Exchange, LLC. The data provenance is internal to the manufacturer, intended to demonstrate equivalence to predicate devices. It is a form of prospective testing for the manufactured re-celled batteries. The company is based in Wauconda, IL, USA.

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

• This information is not applicable to this type of device and study. The "ground truth" for battery performance is objective and measurable (voltage, resistance, successful AED operation), not based on expert interpretation like in image analysis or clinical diagnosis.

4. Adjudication Method for the Test Set

• This information is not applicable. Adjudication methods like 2+1 or 3+1 are used for subjective interpretations (e.g., medical image reads) where disagreements between experts need resolution. For objective measurements like battery performance, the results are definitive.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No, an MRMC comparative effectiveness study was not done. This type of study is relevant for diagnostic devices where human readers interpret results, often with and without AI assistance. This submission pertains to a re-celled battery pack.

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

• Yes, in essence, standalone testing was done for the battery's performance. The core tests (open circuit voltage, loaded circuit voltage) are performed directly on the battery packs without human intervention beyond setting up the test equipment and recording results. The "final acceptance test" involves the AED's internal self-test, which is an automated algorithm checking the battery's functionality. This is the "algorithm only" aspect of performance evaluation for this type of device.

7. The Type of Ground Truth Used

• The ground truth is based on objective, measurable electrical parameters (voltage under open and loaded conditions) and functional validation (the AED's internal self-test reporting "pass"). This is a form of empirical validation against defined performance specifications.

8. The Sample Size for the Training Set

• This information is not applicable as this is not an AI/machine learning device that requires a "training set" in the conventional sense. The "training" for the manufacturing process is adherence to established specifications and procedures for re-celling and testing.

9. How the Ground Truth for the Training Set was Established

• This information is not applicable for the same reason as point 8. The "ground truth" for the manufacturing process is the successful replication of original battery performance, which is verified by the performance tests described in the acceptance criteria.

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The Powerheart® AED G3 Pro, model 9300P, is intended to be used by personnel who have been trained in its operation. The user should be qualified by training in basic life support or other physician-authorized emergency medical response.

The device is indicated for emergency treatment of victims exhibiting symptoms of sudden cardiac arrest who are unresponsive and not breathing. Post-resuscitation, if the victim is breathing, the AED should be left attached to allow for acquisition and detection of the ECG rhythm. If a shockable ventricular tachyarrhythmia recurs, the device will charge automatically and advise the operator to deliver therapy.

When a patient is a child or infant up to 8 years of age, or up to 55 Ibs (25kg), the Powerheart AED G3 Pro should be used with the Model 9730 Pediatric Attenuated Defibrillation Electrodes. The therapy should not be delayed to determine the patient's exact age or weight.

At the discretion of emergency care personnel, the G3Pro with ECG display enabled can also be used with the Model 5111 ECG Patient Cable to display the rhythm of a responsive or breathing patient, regardless of age. The G3Pro and ECG Patient Cable system provides a non-diagnostic display for attended patient monitoring. While connected the G3Pro ECG Patient Cable, the G3Pro evaluates the patient's ECG and disables its shock capability.

The Powerheart® AED G3Pro is a portable, battery-operated, semi-automatic, low power DC defibrillator. The device is designed to diagnose and monitor the patient's cardiac rhythm and deliver the shock energy as required. The Powerheart@ AED G3Pro also has an ECG display and manual override for advanced users. The device in this submission is equivalent to the current Powerheart® ABD and accessories in commercial distribution that was cleared under premarket 510(k) notifications K022929, K011901, K982710 and K031987. The reason for this premarket notification is to introduce the semi-sutomatic

The provided text is a 510(k) summary for the Cardiac Science Powerheart® AED G3 Pro. This document establishes substantial equivalence to predicate devices rather than providing a detailed study proving the device meets specific acceptance criteria in the way a new, de novo device might. Therefore, many of the requested elements about acceptance criteria, detailed study design, and performance metrics are not explicitly available or are presented indirectly through the claim of substantial equivalence.

Based on the provided text, here's what can be extracted and inferred:

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

The document does not specify quantitative "acceptance criteria" for performance metrics like sensitivity, specificity, or positive predictive value. Instead, it asserts that the device modifications (ECG display and manual override) had "no affect on the safety or effectiveness of the device" and that the "device was found to perform as intended." This is based on comparative testing against predicate devices.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

The document mentions "performance software and hardware evaluations" and "testing" but does not specify:

• The sample size for any test set (e.g., number of patients, number of ECG events).
• The data provenance (country of origin, retrospective or prospective nature of data collection).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

The document does not provide details about how ground truth was established for any performance testing, nor does it mention the number or qualifications of experts involved in such a process.

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

The document does not describe any adjudication method used for a test set.

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

The document does not describe an MRMC comparative effectiveness study involving human readers or AI assistance. The device is an AED, and the modifications discussed relate to an ECG display and manual override, not an AI-assisted diagnostic tool for interpretation by human readers.

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

The document states that the Powerheart® AED G3Pro is a "semi-automatic" device, meaning it diagnoses and may advise shock delivery but requires operator action (human-in-the-loop) for therapy. While it performs internal diagnostic algorithms ("software algorithm"), the summary does not detail a standalone algorithm performance study independent of the complete device operation. The focus is on the device as a whole and its equivalence to predicates.

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

The document does not specify the type of ground truth used for any testing. For an AED, ground truth would typically relate to the presence or absence of a shockable rhythm verified by expert cardiologists or electrophysiologists based on ECG analysis or patient outcomes.

8. The sample size for the training set

The document does not refer to a "training set" or provide any sample size for training data. As this is a 510(k) for a device claiming substantial equivalence, the focus is on comparative testing rather than a de novo algorithm development and training process.

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

Since no training set is mentioned, there is no information on how its ground truth might have been established.

Summary of the Study:

The "study" described in this 510(k) notification is primarily a comparative equivalency assessment against previously cleared predicate devices. The modifications introduced in the Powerheart® AED G3 Pro (ECG display and manual override) were evaluated through "performance software and hardware evaluations" and "testing." The reported conclusion is that these modifications did not affect the safety or effectiveness of the device, and it performs as intended, being substantially equivalent to the Powerheart® AED G3 (K031987) and the Philips Medical Systems Heartstream FR2 (K014157, K013425). Specific quantitative performance metrics, detailed study designs, sample sizes, and ground truth methodologies are not provided in this summary, as is typical for 510(k) submissions focusing on substantial equivalence.

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The Powerheart® AED G3A is intended to be used by personnel who have been trained in its operation. The user should be qualified by training in basic life support or other physician-authorized emergency medical response.

The device is indicated for emergency treatment of victims exhibiting symptoms of sudden cardiac arrest who are unresponsive and not breathing. Post-resuscitation, if the victim is breathing, the AED should be left attached to allow for acquisition and detection of the ECG rhythm. If a shockable ventricular tachyarrhythmia recurs, the device will charge automatically and advise the operator to deliver therapy.

When the patient is a child or infant up to 8 years of age, or up to 55 lbs (25kg), the Powerheart® AED G3A should be used with the Model 9730 Pediatric Attenuated Defibrillation Electrodes. The therapy should not be delayed to determine the patient's exact age or weight.

The Powerheart® AED G3A is a portable, battery-operated, fully-automatic, low power DC defibrillator. The device is designed to diagnose and monitor the patient's cardiac rhythm and deliver the shock energy as required. The Powerheart® AED device in this submission is equivalent to the current Powerheart® AED and accessories in commercial distribution that was cleared under premarket 510(k) notifications K022929, K011901, K 982710 and K031987. The reason for this premarket notification is to introduce a fully -automation version of the device.

This product is an Automated External Defibrillator. The provided 510(k) summary (K040438) primarily focuses on establishing substantial equivalence to previously cleared AEDs, rather than presenting detailed new clinical study data with specific acceptance criteria and detailed performance metrics of the device as an AI-powered diagnostic tool. This is a common approach for device modifications or new versions of established devices when the underlying technology (e.g., software algorithm) remains the same or only minimally altered without impacting safety or effectiveness.

Here's an analysis based on the provided text, addressing your points where possible:

1. Table of acceptance criteria and the reported device performance

Based on the provided K040438 summary:

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

The document does not explicitly state a sample size for a "test set" in the context of diagnostic accuracy, nor does it detail data provenance. The testing mentioned refers to "performance software evaluations." This suggests testing of the software's functionality and adherence to specifications, rather than a clinical trial with a patient test set.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

Not applicable. The submission does not describe a study involving expert-established ground truth for a test set of patient data. The evaluation appears to be internal software testing and comparison to predicate devices, not a diagnostic accuracy study using a panel of experts.

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

Not applicable. The document does not describe a test set requiring adjudication by experts.

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. The K040438 summary does not mention a multi-reader multi-case (MRMC) comparative effectiveness study. AEDs like the Powerheart AED G3A are designed to automatically detect and advise on shockable rhythms, and in this fully-automatic version, they also deliver the therapy automatically. The role of "human readers" in the context of an MRMC study for an AED's primary function is not typically applicable in the same way as for image-based diagnostic AI.

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

Yes, in essence, the "performance software evaluations" and the device's inherent design as a "fully-automatic" AED (meaning it diagnoses and delivers shock energy autonomously) can be considered a standalone performance assessment. The device's primary function is to operate independently of real-time human diagnostic input.

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

The ground truth for the software evaluations would have been based on established engineering and cardiac rhythm analysis standards, likely involving:

• Simulated ECG waveforms: Known waveforms (shockable vs. non-shockable) would have been input to verify correct classification and action.
• Performance standards: Adherence to established standards for defibrillator performance (e.g., energy delivery, charge time, shock advisory accuracy).
• Predicate device's algorithm performance: The software algorithm is stated to be "identical... as the current commercially distributed Powerheart® AED," implying that the ground truth for its core functionality would have been established during the clearance of prior versions.

8. The sample size for the training set

The document does not specify a training set sample size. Given that the software algorithm is "identical... as the current commercially distributed Powerheart® AED," it implies the training (if any Machine Learning was involved, which is less common for traditional AED algorithms relying on rule-based detection) would have occurred for previous versions, and this submission is primarily about hardware/operational modifications (fully-automatic functionality) and demonstrating the continued validated performance of the existing algorithm.

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

Not explicitly stated for this particular submission, as it focuses on equivalence. For the original development of an AED's rhythm analysis algorithm, the ground truth for a training set (if applicable) would typically be established by:

• Expert cardiologists/electrophysiologists: Annotation of ECG recordings to identify shockable rhythms (e.g., ventricular fibrillation, pulseless ventricular tachycardia) and non-shockable rhythms.
• Clinical outcomes data: Correlation of algorithm's outputs with actual patient outcomes (e.g., successful defibrillation, survival).
• Standardized databases: Use of well-characterized ECG databases (e.g., AHA/MIT-BIH) with expert-verified annotations.

In summary, this 510(k) submission for the Powerheart® AED G3A is primarily a declaration of substantial equivalence to previously cleared AEDs, particularly a fully-automatic version from another manufacturer, and a semi-automatic version of their own device. The performance testing described focuses on software functionality and ensuring that the conversion to fully-automatic operation did not negatively impact safety or effectiveness, rather than a de novo clinical study establishing diagnostic accuracy with a new AI algorithm.

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