Development of Mobile Apps for Wireless Sensor Data Acquisition and Visualization of Biopotentials

Abstract

Pervasive health biomedical devices are presently trending towards supplementary usage with smart phones, tablets and wearable gadgets to complement their ubiquitous roles in monitoring and diagnostic applications. In this paper, detailed design and development of a user-friendly mobile app using MIT App Inventor 2 software is explained, where emphasis is placed on building a graphical user interface (GUI) to provide the stage for real-time data acquisition and quality visualization (plotting) of photoplethysmography (PPG) data and their spectra on a smart device. Brief review of wireless networking and serial communications is also presented. PPG is modeled in a laboratory environment, where blood volume measurement is obtained via light absorption and reflectance through arterial pulse in the finger by an infrared LED source and optical sensor. A low-power microcontroller is implemented to control and digitize the analog PPG signal, characterized by a pulse oximeter waveform. Investigation of how this valuable biopotential data can be wirelessly transferred from the PPG device via a Bluetooth or WiFi module to a beaconing smart device is pursued. Following a research-driven approach and systematic process, the PPG raw data is amplified and filtered, transmitted and collected wirelessly, then further analyzed to derive the Heart Rate Variability (HRV) signal. Utilizing an advanced tool for studying the variability of heart beat intervals, namely Kubios software, the HRV data was validated for its accuracy in its computation and generation of quantitative markers indicative of the autonomic nervous system's (ANS) influence on the cardiovascular system, particularly the stress response.