M6 Comfort AFib

HEM-7380-E

5 years of warranty

Transform your home blood pressure check into a powerful defence against stroke with M6 Comfort AFib, powered by the clinically validated Intellisense AFib technology by OMRON.

With a touch of a button, automatically screen for AFib every time you measure your blood pressure. Maximize the benefits of regular monitoring, help prevent more serious complications and have a more comprehensive overview of your heart health, reducing the stress of uncertainty.

The OMRON M6 Comfort AFib comes with the Intelli Wrap Cuff - the easy way to get accurate results. It detects the possibility of Atrial fibrillation, enabling home monitoring of the condition and giving you peace of mind. It also takes 3 consecutive readings at 30 second intervals, then displays the average to give you a more accurate indication of your blood pressure.

Specifications

Weight of Device (kg)
0.44
Cuff Type
Intelli Wrap Cuff 22–42 cm
Cuff Wrap Guide
Yes
Memory
2 users x 100 readings plus guest mode
Irregular Heartbeat Detection
Yes
Body Movement Detection
Yes
Validation
Clinical Validation, Diabetic Validation, Pregnancy Validation
AFib detection
Yes
Easy High Blood Pressure Indicator
Yes
Advanced Positioning Sensor
Yes
Intellisense
Yes
Storage Case Included
Yes
Averaging Function
Yes
Connected
No
Item Dimensions (mm)
191 x 85 x 117

What's in the box?

1 x OMRON M6 Comfort AFib blood pressure monitor, 22-42 cm Intelli Wrap arm cuff, 4 x AA batteries, instruction manual, storage case.

External References:

Moody GB, Mark RG. The impact of the MIT-BIH Arrhythmia Database. IEEE Eng in Med and Biol 20(3):45-50 (May-June 2001). (PMID: 11446209) Contains information from “MIT-BIH Arrhythmia Database” which is made available under the ODC Attribution License. doi:10.13026/C2F305

Moody GB, Mark RG. A new method for detecting atrial fibrillation using R-R intervals. Computers in Cardiology. 10:227-230 (1983). Contains information from “MIT-BIH Atrial Fibrillation Database” which is made available under the ODC Attribution License. doi:10.13026/C2MW2D

Clifford GD, Liu C, Moody B, Li-wei HL, Silva I, Li Q, Johnson AE, Mark RG. AF classification from a short single lead ECG recording: The PhysioNet/computing in cardiology challenge 2017. In 2017 Computing in Cardiology (CinC) 2017 Sep 24 (pp. 1-4). IEEE. doi:10.22489/CinC.2017.065-469 Contains information from “AF Classification from a Short Single Lead ECG Recording: The PhysioNet/Computing in Cardiology Challenge 2017” which is made available under the ODC Attribution License. https://physionet.org/content/challenge-2017/1.0.0/training/#files-panel https://opendatacommons.org/licenses/by/1-0/

Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220.

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