Abstract
In this thesis, a healthcare platform is designed to establish a mobile telecare environment with the digital signal processing (DSP) ability. Although mobile health (mHealth) is not an innovative research topic, the improvements of wearable sensing technologies and today’s mobile devices can make such systems more consummate and powerful than before. In our platform, an electrocardiography (ECG)/respiration (RESP) prototype is developed to record single-lead ECG signal and thorax impedance variation caused by respiration of the users. The prototype weights about 8 g, and the size of prototype, which is 25 × 35 × 6 mm^3, is smaller than electrode. With easy-to-use user interface (UI), it could be applied in many kinds of platform such as mobile phone and tablet as a monitoring device. The recorded data can be uploaded to Dropbox automatically. The other thing that’s worth mentioning is the ability to process digital data. With discrete wavelet transform (DWT) we can not only preprocess the biomedical signals for noise reduction but also detect P wave, QRS complex and T wave in real-time. By verifying with MIT-BIH QT database, the results show that the sensitivity of R peak achieves to 99.5%, P wave 97.87% and T wave 92.91%. Ignoring the data recorded from sudden death, the sensitivity of T wave can be up to 98.38% In addition to many functions and services for users, our system also has lower power consumption. The power consumption of the system is 169mW, which can continuously monitor over 6 hours at least with a 280mAh patch-sized battery. Equipped with the developed DSP algorithms, the system can provide noise cancellation and motion artifact removal when moving, stretching and sleeping in user’s daily life. According to the experiment results, the sensitivity of R wave still performs well even running on treadmill at speed of 15km/h. Therefore, our design can be applied in various fields such as art, sport and medical care.