(248 days)
The Apps-Health01 is intended for use in home settings as an aid for people to review, analyze, and evaluate test results which are measured from a blood pressure monitor or scale.
Apps-Health01 iHealth App is an iOS software for using with health devices, such as Blood Pressure Monitor and Scale. When used with the health devices, iHealth App could transfer data from the device's memory and count, manage, share the data.
The provided text describes the 510(k) summary for the Apps-Health01 device. However, it does not contain the detailed information necessary to fully answer all aspects of your request regarding acceptance criteria and a specific study proving the device meets those criteria. The document primarily focuses on software validation and comparison to a predicate device.
Here's an analysis based only on the provided text, highlighting what is present and what is missing:
1. Table of Acceptance Criteria and Reported Device Performance:
The document broadly mentions "Software validation" as the performance test. It does not provide specific quantitative acceptance criteria or corresponding reported device performance metrics in a table format.
| Acceptance Criterion | Reported Device Performance |
|---|---|
| Not specified | Software validation, system test, unit test, Wireless coexistence test, IEC 60601-1 and 60601-1-2, FCC test. |
2. Sample Size Used for the Test Set and Data Provenance:
The document does not specify any sample size for a test set (e.g., number of users, number of data points) or the data provenance (country of origin, retrospective/prospective). The "Software validation" mentioned is a general statement and doesn't detail the specifics of testing data.
3. Number of Experts Used to Establish Ground Truth and Qualifications:
The document does not mention the use of experts to establish ground truth for any test set. The device is a "Data management software" and its primary function is to transfer, count, manage, and share data from health devices, as well as to allow users to review, analyze, and evaluate their own test results. There's no indication of clinical interpretation or diagnostic capabilities requiring expert ground truth in the context of this 510(k) submission.
4. Adjudication Method for the Test Set:
Since there is no mention of a test set requiring expert ground truth or interpretation, there is no adjudication method described.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
No MRMC study is mentioned. The device is a data management software, not an AI-assisted diagnostic tool for human readers.
6. Standalone (Algorithm Only Without Human-in-the-Loop) Performance:
The document states "Apps-Health01 is only a software, it doesn't include meter." Its function is described as enabling users to "review, analyze, and evaluate test results." This implies human interaction as integral to its intended use for data interpretation. The "software validation" performed would be analogous to a standalone performance test for the software's functionality (e.g., data transfer, display, calculations), but it's not a clinical performance study in the typical sense of an algorithm making a diagnosis or prediction.
The performance tests cited are:
- Software validation (system test and unit test)
- Wireless coexistence test
- Tests according to IEC 60601-1 and 60601-1-2
- FCC test
These are primarily engineering and regulatory compliance tests for the software and its interaction with hardware, not clinical performance studies.
7. Type of Ground Truth Used:
Given the nature of the device as data management software, the concept of "ground truth" in a medical context (like pathology or outcomes data) is not applicable here. The "ground truth" for the software validation would likely be the correct functioning of the software according to its specifications (e.g., data accurately transferred, calculations performed correctly, data displayed as expected).
8. Sample Size for the Training Set:
The document does not mention any training set. As this is a data management software, it's not described as an AI/ML model that would require a distinct training set for learning.
9. How the Ground Truth for the Training Set Was Established:
Since no training set is mentioned, this information is not provided.
§ 870.1130 Noninvasive blood pressure measurement system.
(a)
Identification. A noninvasive blood pressure measurement system is a device that provides a signal from which systolic, diastolic, mean, or any combination of the three pressures can be derived through the use of tranducers placed on the surface of the body.(b)
Classification. Class II (performance standards).