BeatCare is a platform (both online and offline) for the analysis and interpretation of ECG signals.
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(Your files must be in `BeatCare ECG Data JSON Format` like here)
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- Heart rhythm
- Heart rate
- QRS segment duration
- QT segment duration
- ST segment duration
- PQ segment duration
- ST & isoelectric line
- Changes in ST segment morphology
- Respiratory rate
- Detection of sinus tachycardia
- Detection of bradycardia
- Detection of changes in the morphology of the ST-segment
- Detection of AV block
- Detection of second degree AV block
- Detection of different type of Arrhythmia
BeatCare provides a cutting edge algorithm for ECG analysis and interpretation. At the input the raw ECG signal is used. At least lead II is required to perform analysis. The algorithms allow to perform different checks: Rhythm, Heart rate, Arrhythmia, QRS segment length, QT segment duration, ST segment length, PQ segment, AV block, ST & isoelectric line. These checks provide an overview of health condition based on the ECG signal and can define certain health problems and alarm to perform deeper analysis in the hospital.
It is not always possible to use an online cloud service when it comes to health aware data. In this case you can use our technology embedded in your system or application. BeatCare technology is fast enough to perform real time analysis.
BeatCare technology is extremely fast. Analysis of up to 3 hours of high resolution ECG signal for signal lead will take less then 30 seconds to complete!
Health aware data is very sensitive and requires the highest protection level at every stage. In our service we work with fully anonymized data. ECG data does not contain any personal information about the patient whatsoever in BeatCare cloud.
In this paper a novel mobile ECG analysis system is discussed. Existing stationary systems allow recording high quality ECG signal, but they place patients in an unlikely environment. Known wearable systems do not provide enough freedom as their sensors are connected to a mobile computer by wires. We propose a wireless ECG system with wired sensors and a mobile computer able to perform real-time analysis. Recorded signal is also transmitted to a central server where it can be processed more accurately. Special algorithms, based on well known methods, are proposed for signal filtering, baseline drift removal and P, Q, R, S and T peaks detection
