Monebo FAQ
Monebo FAQ
Frequently asked questions is a page where we answer the most popular questions that our Monebo company receives from our customers. On this page, we have collected frequently asked questions about our services and products. We tried to answer the questions as detailed and useful as possible to help you find the answer to your question.
If you have any questions that are not covered on this page, please contact us using the form below and we will be happy to help you. We strive to provide quality and accessible information so that you can get answers to your questions quickly and easily.
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What devices can your software be installed on?
We customize our software for each client individually, so it can be installed on any device that supports Windows, Linux and Android or IOS systems.
Where can I use your algorithm?
Wherever ECG analysis is needed, Monebo has a solution. The Kinetic™ Family of ECG Algorithms is scalable for use in devices utilizing small microcontrollers or DSP’s, all the way up to computor or server-based platforms.
You can use our software as an embedded application:
- ambulatory cardiac event recorders
- ambulatory long-term monitoring devices
- vital signs monitoring devices
- personal cardiac safety devices
- health and wellness devices
- bedside monitors
- exercise machines and any a device that uses any ECG waveform
as well as an application for computors or servers:
- cardiology call centers that receive data from the event recorder
- automated analysis of ECG files from a specific device
- equipment suppliers that need post-processing of ECG records
Please contact us to find out if our technology can help you and your customers improve accuracy, add functionality, make your workflow more efficient, or speed up your product development.
What is an ECG Analyzer?
ECG processing or monitoring system is a software program that receives a cardiological signal at the input and, through a complex mathematical analysis of the data array, produces a result in the usual form for a doctor in the form of a set of indicators that characterize the work of the heart. The basis of such software are digital signal processing (DSP) algorithms, applied statistical analysis algorithms, multi-dimensional classification algorithms. ECG algorithms must meet certain requirements in order to be safe for patients and useful for physicians. Such algorithms must provide the required performance (accuracy) and are subject to mandatory regulatory processes.. These algorithms must be sufficiently robust with respect to the quality of the input signal, since the ECG signal is characterized by a significant noise level in a wide frequency range. This problem is usually solved with complex digital filtering systems. As a result, an ECG algorithm typically produces annotation of heart beats (including the positions of PQRST waves and their amplitudes, types of heart beats), heart rate, interval measurements, and rhythm events interpretation.
What makes an ECG signal impossible to process?
Processing of the ECG signal can be complicated by various factors, such as:
- Noises
The ECG signal can be contaminated by various noises, such as: power line noise, electromagnetic interference, patient movements, and other artifacts. Noise can make it difficult to accurately determine the shape and characteristics of the ECG signal.
- Artifacts
Artifacts such as muscle movements, respiratory muscle spasms, patient body movements and other similar factors can also complicate the processing of the ECG signal.
- Individual differences
the ECG signal may vary depending on individual differences in the shape of the heart, its location in the chest, and other factors.
- Poor ECG recording quality
Poor ECG recording quality, which can be caused by incorrect electrode placement, poor electrode quality, insufficient contact between the electrodes and the skin, can also complicate the processing of the ECG signal.
In general, accurate processing of an ECG signal can be a challenge due to a variety of factors, but with the use of appropriate signal processing and analysis techniques, many of these problems can be solved.