Key result
A scalable cloud-based telemonitoring model was developed to generate realistic synthetic ECG signals and evaluate biomedical signal processing methods for remote patient surveillance.
A cloud-based telemonitoring model can generate realistic synthetic ECG signals to evaluate biomedical signal processing methods.
Telemonitoring model is health observations model that going to surveillance patients remotely. Telemonitoring model is suitable for patients to avoid high operating expense to get Emergency treatment. Telemonitoring gives the path for monitoring the medical device that generates a complete profile of patient's health through assembling essential signs as well as additional health information. Telemonitoring model is relying on four differential modules which is capable to generate realistic synthetic electrocardiogram (ECG) signals. Telemonitoring model shows four categories of chronic disease: pulmonary state, diabetes, hypertension, as well as cardiovascular diseases. On the other hand, the results of this application model recommend facilitating despite of their nationality, socioeconomic grade, or age, patients observe amid tele-monitoring programs as well as the utilization of technologies. Patient's multiple health status is shown in the result such as beat-to-beat variation in morphology and timing of the human ECG, including QT dispersion and R-peak amplitude modulation. This model will be utilized to evaluate biomedical signal processing methods that are utilized to calculate clinical information from the ECG.
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Sawant et al. (2017) studied Chronic diseases (pulmonary, diabetes, hypertension, cardiovascular). Cloud-based telemonitoring model was evaluated on Generation of realistic synthetic electrocardiogram (ECG) signals. A scalable cloud-based telemonitoring model was developed to generate realistic synthetic ECG signals and evaluate biomedical signal processing methods for remote patient surveillance.
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