ECG machines and devices used commonly in hospitals and scan centers are stand alone devices. They have their own set of prediction algorithms based on the manufacturer and also the prediction given by the device is not accurate up to the point, due to a fact that the database containing the pre recorded values are not updated. The database used in those stand-alone devices are basically the system memory. The proposed idea is to develop an ECG acquisition and Abnormality prediction system, which compares data in real-time with the data in the cloud, which acts as a database and also a prediction platform to predict the abnormality by comparing data in real-time scenario with pre-recorded real-time data of patients from all over the globe. The outcome product will analyse the ECG signal of the patient, the morphological attributes of the ECG signal will be extracted and will send the recorded and processed data to the cloud storage so that the medical practitioner can view the ECG waveform , the essential parameters , and the predicted abnormality which will be a suggestion to the cardiologist. The product when compared to the existing ECG machines in India is faster, accurate, can be connected to the cloud storage, can predict the abnormalities by use of the pre-recorded values and mainly small in size, less weight, low cost and portable.
Vital Signal Analyser - A system to acquire and predict abnormalities in ECG signal .
ECG machines and devices used commonly in hospitals and scan centers are stand alone devices. They have their own set of prediction algorithms based on the manufacturer and also the prediction given by the device is not accurate up to the point, due to a fact that the database containing the pre recorded values are not updated. The database used in those stand-alone devices are basically the system memory. The proposed idea is to develop an ECG acquisition and Abnormality prediction system, which compares data in real-time with the data in the cloud, which acts as a database and also a prediction platform to predict the abnormality by comparing data in real-time scenario with pre-recorded real-time data of patients from all over the globe. The outcome product will analyse the ECG signal of the patient, the morphological attributes of the ECG signal will be extracted and will send the recorded and processed data to the cloud storage so that the medical practitioner can view the ECG waveform , the essential parameters , and the predicted abnormality which will be a suggestion to the cardiologist. The product when compared to the existing ECG machines in India is faster, accurate, can be connected to the cloud storage, can predict the abnormalities by use of the pre-recorded values and mainly small in size, less weight, low cost and portable.
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