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A Patient-centered medical environment with wearable sensors and cloud monitoring

In this paper, an integrated wearable application platform with physiological sensors are presented. We use the wearable devices to collect the electrocardiography (ECG) and respiration (RESP) signals. This wearable device is a prototype with analog front-end, a microcontroller, and a Bluetooth module. We attach the electrodes on the thorax to record single-lead ECG signal and thorax impedance variation of the users. The mobile phone is a platform for dealing with the digital signal processing. We design an Android app with convenient user interface for every application. With discrete wavelet transform (DWT), we can easily detect the important features such as P wave, QRS complex and T wave and reduce the interference of noise. We develop an application with the wearable device for the emotion recognition. The extracted-features of biomedical signals are implemented with methods by the cloud computing. We implement the cloud computing by Apache Storm, which can transmit the data by streaming via 3G/Wi-Fi. With the proposed stream processing framework for the relaxation state calculation with wearable ECG sensors, under 5 people monitoring simultaneously, the latency and response time can be reduced by 10 times.