(117 days)
The device is a digital monitor intended for use in measuring blood pressure and pulse rate in adult patient population with arm circumference ranging from 9 inches (22cm to 42cm). The device detects the appearance of irregular heartbeats during measurement and gives a warning signal with readings.
The Evolv Model BP7000 Upper Arm Blood Pressure Monitor ("BP7000") is a battery powered automatic non-invasive blood pressure system intended for home use. The device inflates a cuff with an integral controllable pump, then deflates the cuff via an electric valve. During inflation the cuff pressure is monitored and pulse waveform data is extracted. The extracted pulse waveform data is then analyzed by software which determines pulse rate, as well as systolic and diastolic blood pressure. The systolic and diastolic blood pressures are measured using the oscillometric method. The cuff pressure range is 0 to 299mmHg and the pulse rate range is 40 to 180 beats/min. BP7000 is intended to be used for arms ranging from 22 to 42cm in circumference. The cuff is not replaceable. The device also detects the appearance of irregular heartbeats during measurement. The device displays the latest blood pressure reading, while up to 100 readings can be stored in memory. The operation of the device is intended for home use. Functions and other features that are controlled by the end user include applying the arm cuff to the upper arm, powering on/off the system, starting or stopping the BP and pulse measurement cycle, and installing and changing the batteries as needed. As an optional feature, the user can also pair the BP7000 to a smartphone when employing the "Omron connect" app. This app is an optional feature and is only intended to display trend graphs of measured systolic and diastolic blood pressure, and pulse rate. This app does not provide any diagnostic or measurement functions, and does not interpret or analyze the data for medical decision making. Unlimited readings can be stored in the app for archiving and review by the user. Aside from this optional app for smartphones, BP7000 does not connect with other collateral devices.
The provided text describes the 510(k) submission for the Omron Evolv Model BP7000 Upper Arm Blood Pressure Monitor. This device is a non-invasive blood pressure measurement system, and the submission focuses on demonstrating its substantial equivalence to a predicate device (Omron HEM-7320) rather than proving performance against specific acceptance criteria for an AI/ML powered device.
Therefore, many of the requested details regarding AI/ML study methodologies (e.g., sample size for training set, number of experts for ground truth, MRMC study, standalone performance) are not applicable to this traditional medical device submission.
However, I can extract the relevant information regarding the device's performance and the clinical testing that was conducted.
Here's a breakdown of the requested information based on the provided document:
Acceptance Criteria and Study for Omron Evolv Model BP7000 Upper Arm Blood Pressure Monitor
This submission demonstrates substantial equivalence of a traditional blood pressure monitor to a predicate device, not the performance of an AI/ML algorithm. As such, many of the requested AI/ML specific criteria are not applicable.
1. Table of Acceptance Criteria and Reported Device Performance
For this device, the "acceptance criteria" are primarily based on demonstrating equivalence to the predicate device and meeting established industry standards for blood pressure monitors. The document mentions an accuracy claim for both the proposed and predicate devices.
| Feature/Metric | Acceptance Criteria (Implied/Stated) | Reported Device Performance (BP7000) |
|---|---|---|
| Blood Pressure Accuracy | ±3mmHg (Same as predicate device) | Confirmed (Comparison testing demonstrated equivalence to predicate; Clinical investigation found it performed equivalently to auscultation) |
| Pulse Rate Accuracy | ±5% (Same as predicate device) | Confirmed (Comparison testing demonstrated equivalence to predicate) |
| Cuff Pressure Range | 0 to 299mmHg (Same as predicate device) | 0 to 299mmHg |
| Pulse Rate Range | 40 to 180 beats/min (Same as predicate device) | 40 to 180 beats/min |
| Arm Circumference Range | 22cm to 42cm (Same as predicate device) | 22cm to 42cm |
| Irregular Heartbeat Detection | Detects and gives warning signal (Same as predicate device) | Detects and gives warning signal |
| Equivalence to Predicate | Substantially equivalent in safety and effectiveness | Determined to be substantially equivalent (Based on nonclinical and clinical tests) |
| Cleaning Performance | Retains performance when cuff is exposed to surfactants | Confirmed by cleaning verification testing |
| Usability | Acceptable performance in simulated home use environment | Confirmed by usability testing |
| Biocompatibility | Compliant with ISO 10993-1 requirements | Confirmed by biocompatibility testing |
| Electrical Safety, EMC, ESD | Complies with relevant requirements | Confirmed by testing |
| Software Verification/Validation | Complies with relevant requirements | Confirmed by testing |
2. Sample Size Used for the Test Set and Data Provenance
- Test Set Sample Size: The document does not explicitly state the exact sample size for the clinical investigation. It mentions "a clinical investigation" to validate accuracy. For non-clinical bench testing, it refers to "comparative blood pressure and pulse rate testing to the predicate device" and "performance verification testing," but no specific sample numbers are provided.
- Data Provenance: Not explicitly stated regarding country of origin. The clinical investigation was for "validating the accuracy... as compared to an auscultation method." It does not specify if it was retrospective or prospective, but clinical investigations for device validation are typically prospective studies.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of those Experts
- Number of Experts: Not explicitly stated. The clinical investigation compared the device's accuracy "to an auscultation method using a calibrated sphygmomanometer by trained medical staff."
- Qualifications of Experts: "Trained medical staff." No further details on their specific qualifications or experience level (e.g., radiologist with X years of experience) are provided as this is not an imaging device.
4. Adjudication Method for the Test Set
- Adjudication Method: Not applicable/not stated. The comparison was to an auscultation method performed by medical staff, implying a direct comparison rather than an expert consensus adjudication process typically seen in image interpretation studies.
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
- MRMC Study: Not applicable. This is a blood pressure monitor, not an AI-powered diagnostic tool requiring human reader studies.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Standalone Performance: The device itself performs the measurement and provides readings. The "clinical investigation" effectively evaluates its "standalone" performance against a reference standard (auscultation). The direct comparison was of the device's measured blood pressure values against the auscultation readings.
7. The Type of Ground Truth Used
- Ground Truth: For the clinical investigation, the ground truth was based on the auscultation method using a calibrated sphygmomanometer performed by trained medical staff. This serves as the clinical reference standard.
8. The Sample Size for the Training Set
- Training Set Sample Size: Not applicable. This device is a traditional blood pressure monitor, not an AI/ML algorithm that undergoes a distinct "training" phase with a specified dataset. Its internal algorithm for oscillometric measurement is pre-defined.
9. How the Ground Truth for the Training Set was Established
- Ground Truth Establishment for Training Set: Not applicable. As stated above, this is not an AI/ML device in the context of "training data." The device's underlying algorithm for converting oscillometric data to blood pressure readings is based on established physiological principles and engineering design, not on a machine learning training process with a labeled dataset.
§ 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).