Development of a wireless system for the remote monitoring of muscular activity

INTRODUCTION The study and the analysis of the human movements require the acquisition of kinematic, dynamics and electrophysiological variables. Among them, the electromyographic signal (EMG) plays a fundamental role to monitor the muscular activity. In the last years, EMG devices composed by a set of wireless modules allowing the detection and transmission of one or more EMG signals to a mobile device, such a tablet or smartphone, have been developed and are now commercially available. The aim of this works is the development of a telemetry wireless system for the detection and real-time monitoring of EMG signals using a wireless body area network (WBAN). METHODS The system architecture (Figure 1) consists of one or more modules, each one detecting two bipolar EMG signals sampled at 2.048kHz with 16 bit resolution. The sampled signals are sent to a mobile device acting as a receiver through a Bluetooth 4.0 link. A web client mobile application, written using the C++ programming language, acquires the data, calculates the EMG envelope and send it to a remote web server using a TCP-IP socket. The web server, written in Python using the Heroku PaaS (Platform as a Service) service, has a permanently opened TCP-IP socket in order to maximize the Internet data throughput. The signals received on the web server, can be displayed in real-time on a website (http://lisinsite.herokuapp.com/) designed using the HTML language and the Highcharts javascript library. RESULTS The system has been successfully tested on two subjects during a marathon organized for the “Just the Woman I Am” event held in Turin on March 2017. The Figure 1.b shows the EMG envelope detected on the medial gastrocnemius muscle of two subjects participating to the marathon. The signals are plotted in a web browser. The mean data throughput observed during the event was 100 kbps. DISCUSSION The main innovation introduced by this system is the ability to real-time monitoring the muscular activity of subjects without constraints on the maximum transmission distance of the detection system worn by the subject. The modular architecture of the system permits the simultaneous use of many detection probes on different subjects. Finally, the system is easy to use and requires only a smartphone and a web browser.