Conventional analog methods cannot track changes in individual ECG data, and it is also difficult to compare and analyze current and past data.
-> In traditional ways, it is often too late to visit a hospital because the patient feels abnormal, failing to diagnose whether a healthy person is approaching heart disease.
Assumes a system combined with mobile devices and cloud services
If you can observe and analyze changes in ECG data regularly (or intermittently) over a relatively long period of time, it is more likely to prevent worsening of heart disease.
-> It is also possible to develop new diagnostic methods through the use of big data.
To realize this, it is necessary to build an ECG monitoring system composed of ECG measuring devices, mobile devices, and cloud services.
- ECG Monitoring System Concept
-> ECG data sent to the cloud continuously or intermittently for a long time performs statistical processing such as P wave time, PR, QRS, QT, QTc interval, and a warning is sent to the specialist to be diagnosed if meaningful changes are detected.
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Select Lead I as the measurement location for ECG
ECG measuring devices for monitoring should be simple and easy to use. It should also be provided at an affordable price and need to minimize the measurement position.
-> Without sufficient user convenience, it is difficult to achieve the task of observing and analyzing changes in ECG data regularly (or intermittently) over a long period of time.
-> Lead II is the most representative of 12 ECG channel, but it is inconvenient to measure it with a portable ECG device. It is important to ensure convenience.
From this point of view, select Lead I as the measurement location for ECG Monitoring.
- Lead I : RA(Right Arm) and LA(Left Arm)
Effectiveness Issues of Lead I Data
The specialist performs ECG diagnosis using 12 Lead Data. Questions may arise about whether analysis using only Lead I data is sufficient.
-> As long as monitoring is concerned, we have verified that Lead 1 is of sufficient utility.
- Verification work is completed on the data obtained at https://physionet.org/physiobank/database/