Using mobile technology to construct a network medical health care system

Abstract

In this study, a multisensory physiological measurement system was built with wireless transmission technology, using a DSPIC30F4011 as the master control center and equipped with physiological signal acquisition modules such as an electrocardiogram module, blood pressure module, blood oxygen concentration module, and respiratory rate module. The physiological data were transmitted wirelessly to Android-based mobile applications via the TCP/IP or Bluetooth seri-al ports of Wi-Fi. The Android applications displayed the acquired physiological signals in real time and performed a preliminary abnormity diagnosis based on the measured physiological data and built-in index diagnostic data provided by doc-tors, such as blood oxygen concentration, systolic pressure, and diastolic pressure. In addition, in this study, the R waves, which are the highest peaks of the PQRST waves in electrocardiograms, were analyzed and detected using the heart rate variability (HRV) for time-frequency analysis and calculation of the RR interval time series. In this study, the heart rate data in the same age group were collected, and the optimal value of the standard deviation of normal to normal (SDNN) during the time domain of a normal heartbeat was found using the particle swarm optimization (PSO) algorithm and set as the risk level of the SDNN time domain analysis. A spectral analysis on the activity of the autonomic nervous system (ANS) was performed and the preliminary analysis results were displayed on the Android handheld devices for comprehensive physiological data analysis and HRV time-frequency analysis. Healthcare needs are distributed at all levels, therefore user-friendly software interfaces have been written to meet the health-care needs at all ages.