AED: adaptive energy-efficient data transmission scheme for heart disease detection
The system consists of Android based smartwatch, smartphone, and server as shown below:
The smart watch equipped with a sensor senses the user’s heart rate. Different sensors in smartwatch extract different features such as an accelerometer, gyroscope which are helpful
in gesture recognition to know the user activities.
The user data is stored in the cloud based clinical server, for future medical diagnosis. This huge amount of user’s data will be useful in prediction and analysis based on user’s heart rate and activities. This kind of integration will make the system to reduce power consumption and accountable of user’s critical events.
Role: Researcher, System Architect, Technical Writer
Next generation health and fitness wearable devices offer the opportunities for improving personalized healthcare. To detect and predict health problems, wearable devices with limited power resource need to transmit sensing data uninterruptedly that could be a huge challenge. Many exist researches use various ways to reduce the energy consumption but, to the best of our knowledge, no one employs physical activities integrated with data transmission technique to save the power. In this paper, we have developed an Adaptive Energy-efficient Data transmission (AED) scheme, which can detect critical events such as myocardial infarction and, at the same time, minimizes data transmission from the devices. Simulation results show that AED reduces the number of transmission by 71.35% for continuous data transmission and 30.33% for batch data transmission.