Prenatal Abdominal Electrocardiogram Monitoring System using IoT in Cloud Environment: A MIMO approach
The application of Internet of Things (IoT) for acquiring, analyzing and transmission of medical data is increasing in recent years. Especially in abdominal ECG processing the need is more. Since the fetal movements are random in the abdomen, a single electrode can’t be able to acquire the fetal ECG. So multi-electrodes are used to record the same. At the same time all electrodes will not provide continuous ECG signal due to the fetal movements. The temperature, pressure and heart rate of the mother also monitored for effective diagnosis. This options makes the design a multi-input structure. In existing methods, Multi-input multi-output options are not available. In addition to that the complexity increases if number of input increases. In conventional methods, the complete machine is available in the patient room. But here in this work the product is divided into three units, bedside unit, doctors unit and main server. The bedside unit is an ECG acquisition device developed using a multi-lead heart rate monitor, sensors and microcontroller. Zigbee is used to transmit the information from the patient bedside to doctors unit which makes it wireless. During the movement of the patient also the data can be viewed. The Multi-output data corresponds to fetal ECG, maternal ECG, heart rate, temperature, pressure. The IoT using raspberry pi module connects the doctors unit with the main server. The machine learning algorithms analyze the ECG data of all electrodes and sensor outputs. The multi-outputs are viewed in a Graphical User Interface (GUI). The integration of the system is conducted to construct a complete IoT-based ECG monitoring system and diagnosis in Cloud environment.