(30 days)
The device is a digital monitor intended for use in measuring blood pressure and pulse rate in adult patient population with wrist circumference ranging from 7.1 inches to 8.5 inches (18.0cm to 21.5cm).
The device detects the appearance of irregular heartbeats during measurement and gives a warning signal with readings.
The Omron HEM-6410T-ZL Wrist Blood Pressure Monitor ("HEM-6410T-ZL") is a battery-powered, automatic, non-invasive blood pressure system intended for home use. HEM-6410T-ZL is intended for use in adult patient population with wrist circumference ranging from 7.1 inches to 8.5 inches (18.0cm to 21.50cm). The device is powered by a rechargeable lithium-polymer battery. An AC adapter is used for charging the device, but the device cannot be operated while charging. The device wrist cuff inflates using an integral pump and deflates via an electric valve. During inflation, the wrist 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 can measure pressure range from 0 to 299mmHg, and the pulse rate range from 40 to 180 beats/min.
The blood pressure reading is displayed in "red" color if the blood pressure recorded is equal to or greater than 130/80 based on the American Heart Association (AHA)/ American College of Cardiology (ACC) High Blood Pressure Clinical Practice Guideline criterion for Stage 1 Hypertension, published in 2017. The device displays the latest blood pressure reading, while up to 100 readings can be stored in memory. The device also detects the appearance of irregular heartbeats during the blood pressurement process. An irregular rhythm is defined as the appearance of two (2) or more heartbeat intervals which differ by greater than 25% from the average heartbeat rhythm. Detection of such irregular rhythms would result in an "irregular heartbeat symbol" displayed along with the blood pressure and pulse rate readings.
In addition, the device includes an Advanced Positioning Sensor (APS), known as the Heart Zone Indicator, which aids the user to determine if the wrist cuff is at the correct height in relation to the heart. This determination is based on the reading of an accelerometer (integral to the device) to measure the angle of the arm. The APS feature is identical to that of the predicate device. The operation of the device is intended for home use. Additional functions and other features that are controlled by the end user include applying the wrist cuff to the wrist, powering on/off the system, starting or stopping the blood pressure (BP) and pulse measurement cycle, and charging the battery as needed. As an optional feature, the user can also pair the HEM-6410T-ZL 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, HEM-6410T-ZL does not connect with other collateral devices.
The provided text describes the OMRON HEM-6410T-ZL Wrist Blood Pressure Monitor and its clearance through a 510(k) premarket notification (K190693). The document primarily focuses on demonstrating substantial equivalence to a predicate device, the OMRON HEM-6410T-ZM (K182481). While it mentions clinical testing, it does not provide detailed acceptance criteria or extensive specifics about the study that proves the device meets these criteria in the way typically expected for an AI/ML medical device.
Therefore, many of the requested details, particularly regarding AI/ML-specific validation (e.g., sample sizes for training/test sets, data provenance, expert ground truth, MRMC studies, standalone performance), are not present in this document because this is a traditional medical device, not an AI/ML device.
The device in question is a non-invasive blood pressure measurement system that uses the oscillometric method. Its "software" analyzes pulse waveform data to determine blood pressure and pulse rate, and it detects irregular heartbeats. While it contains software, it is not described as an AI/ML-powered device in the sense of needing large, annotated datasets for training and sophisticated validation of AI model performance.
Below is an attempt to address the request based only on the information provided, with an acknowledgment of what is missing due to the nature of the device:
Acceptance Criteria and Device Performance for OMRON HEM-6410T-ZL Wrist Blood Pressure Monitor (K190693)
Based on the provided 510(k) submission, the device's performance is primarily assessed against the accuracy standards for blood pressure monitors and compared to the predicate device.
1. Table of Acceptance Criteria and Reported Device Performance
| Criterion (Acceptance Standard) | Device Performance (Reported Value) |
|---|---|
| Accuracy of Pressure Indicator | Within ±3mmHg |
| Accuracy of Pulse Rate | Within ±5% of reading |
| Measurement Range - Pressure | 0 to 299mmHg |
| Measurement Range - Pulse Rate | 40 to 180 beats/min. |
| Conformance to Standard | Conformance with ANSI/AAMI/ISO 81060-2:2013 |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: The document states that "Clinical validation of the HEM-6410T-ZL was conducted," but it does not specify the sample size (number of patients/subjects) used for this clinical testing.
- Data Provenance: The document does not specify the country of origin of the data or whether the study was retrospective or prospective. It only mentions that the study was conducted in accordance with ANSI/AAMI/ISO 81060-2:2013. This standard typically requires prospective clinical studies.
3. Number of Experts Used to Establish Ground Truth and Qualifications
- The ground truth for blood pressure measurement was established by "trained medical staff" using an "auscultation method" with a "calibrated sphygmomanometer."
- The number of experts/medical staff is not specified, nor are their specific qualifications (e.g., "radiologist with 10 years of experience" is not applicable here as it's a blood pressure device, not an imaging device).
4. Adjudication Method for the Test Set
- The document implies a direct comparison of the device's readings against the auscultation method. It does not describe an adjudication method (like 2+1 or 3+1 consensus) for establishing ground truth, as is common in diagnostic AI/ML studies. The auscultation method itself serves as the reference standard.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done
- No, an MRMC comparative effectiveness study was not done in the context of human readers improving with AI assistance. This device is not described as an AI-assisted diagnostic tool where human readers interpret outputs. It is a standalone measurement device.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done
- The clinical validation directly assessed the device's performance (which includes its embedded algorithm) against the auscultation method. In essence, this is a form of "standalone" performance assessment of the device's measurement capabilities, as it's measuring blood pressure directly without human interpretive input beyond starting the measurement. However, it's not a standalone algorithm assessment in the way one would evaluate an AI model's output for an imaging device.
7. The Type of Ground Truth Used
- The ground truth used was auscultation method measurements taken by trained medical staff using a calibrated sphygmomanometer. This is a recognized clinical reference standard for blood pressure measurement.
8. The Sample Size for the Training Set
- This information is not applicable/not provided in the context of this device. The document describes "algorithm parameters" being changed and validated, implying a modification to a traditional blood pressure measurement algorithm rather than a machine learning model that requires a "training set."
9. How the Ground Truth for the Training Set was Established
- This information is not applicable/not provided as there is no mention of a "training set" in the context of machine learning model development. The "ground truth" for validation was established via auscultation method.
§ 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).