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ES Complex Software is an optional software accessory for use with the following models with data management capabilities: a) Contec 08A, blood pressure device b) ESO, oximeter c) EIS-GS, galvanic skin response device and d) ES-BC. Analyzer body composition When use Contec 08A and ESO and/or EIS-GS and/or ES-BC, the ES Complex software uploads the data of the devices and displays the data into a computer for enhanced data management. The ES Complex software is intended for use in clinical settings as an aid for health care professionals to review, analyze and evaluate the historical tests results.

ES Complex Software is an optional software accessory for use with the following models with management capabilities: a) Contec 08A, blood pressure device b) ESO, oximeter c) EIS-GS, galvanic skin response device and d) ES-BC. Analyzer body composition When use combination Contec 08A and ESO, and/or EIS-GS and/or ES-BC, the ES Complex software uploads the data of the 4 devices and displays the data into a computer for enhanced data management.

This submission K113264 is for the Electro Sensors Complex Software (ES Complex Software). The documentation indicates that performance was evaluated through Software Verification & Validation and Risk Management, rather than a clinical study comparing device performance against specific acceptance criteria. This means the typical metrics for diagnostic accuracy (sensitivity, specificity, etc.) and associated study design elements (sample size, expert ground truth, etc.) are not applicable here.

The device's performance is described in terms of its functionality and its ability to manage data from connected medical devices. The "Table of comparison" highlights its equivalence to the predicate device in terms of data management, historical test results, operating system, and results screen.

Here's a breakdown of the requested information based on the provided text, with clarifications where direct answers are not available due to the nature of the submission:

1. Table of Acceptance Criteria and Reported Device Performance

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

• The submission does not mention a traditional "test set" or sample size in the context of diagnostic performance evaluation with patient data.
• The performance evaluation focused on Software Verification & Validation (D-11SRS/SDS/ D-12 STD/ STR D-33 and 34) and Risk Management (D-28). These types of tests typically involve controlled functional testing, integration testing, and simulated scenarios rather than a dataset of patient cases.
• Data Provenance: Not applicable as there wasn't a test set of patient data from a specific country or collected retrospectively/prospectively for diagnostic performance. The input data for the software is stated to come from other 510(k) cleared medical devices.

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

• Not applicable. There was no "test set" of patient cases requiring expert interpretation to establish ground truth. Software verification and validation utilize established software engineering practices and possibly simulated data or test cases based on expected device outputs.

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

• Not applicable. There was no test set of patient cases requiring adjudication of ground truth.

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 type of MRMC study was not performed or referenced. The device is a data management software, not an AI-assisted diagnostic tool that would typically involve human readers interpreting images or complex data with and without AI.

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

• The "standalone" performance, in this context, refers to the software's ability to fulfill its stated functions independently. The submission indicates that Software Verification & Validation was performed. This would confirm the algorithm's functional correctness in uploading, displaying, and managing data as intended, without human intervention in the data processing itself, but human professionals are the intended users for reviewing the managed data.

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

• Not applicable as there was no diagnostic "test set" requiring ground truth for clinical accuracy. For software verification, the "ground truth" would be the expected functional behavior and output of the software according to its design specifications (e.g., data is uploaded correctly, displayed accurately, historical tracking functions as intended).

8. The sample size for the training set:

• Not applicable. The Electro Sensors Complex Software is a data management software, not a machine learning or AI algorithm that requires a "training set" of data in the conventional sense. Its functionality is based on programmed logic and integration with other medical devices.

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

• Not applicable, as no training set was used for this software.

Summary of Device Performance Evaluation:

The K113264 submission demonstrates substantial equivalence for the Electro Sensors Complex Software primarily through comparison to a predicate device (Health care system software K110948) and by declaring adherence to an established software development lifecycle (Software Verification & Validation) and risk management processes. The focus is on the software's functional performance in data management from connected medical devices, rather than a diagnostic accuracy claim that would necessitate patient-level performance studies. The key performance evaluations cited are:

• Software Verification & Validation (D-11SRS/SDS/ D-12 STD/ STR D-33 and 34): This confirms that the software's components and system meet specified requirements and perform their intended functions correctly.
• Risk Management (D-28) according to ISO 14971: This ensures that potential risks associated with the software have been identified, evaluated, and mitigated.
• Adherence to ISO 62304: This standard governs medical device software life cycle processes, ensuring a structured approach to software development, maintenance, and risk management.

The comparison table highlights that the ES Complex Software shares the same core functions (data management, historical data tracking, operating system, PC display) as the predicate device, although it handles different types of physiological data and is indicated for clinical settings only (whereas the predicate included home use). The conclusion is that the device is "equivalent in performances, technology, safety and efficacy to the legally marketed predicate devices."

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