MyoHMI: A low-cost and flexible platform for developing real-time human machine interface for myoelectric controlled applications

EMG pattern recognition has been studied for control of prostheses and rehabilitation systems for decades. Existing research platforms for developing EMG pattern recognition algorithms are typically based on MATLAB and the collection of EMG signals is often done by expensive, non-portable data acquisition systems. The requirement of these resources usually limits the use of these platforms in the lab environments and prohibits their widespread to other fields and applications. To address this limitation, this paper presents a low-cost, easy to use, and flexible platform called MyoHMI for developing real-time human machine interfaces for myoelectric controlled applications. MyoHMI facilitates the interface with a commercial EMG-based armband Myo, which costs less than $200 and can be easily worn by the user without the need of special preparation. MyoHMI also provides a highly modular and customizable C/C++ based software engine which seamlessly integrates a variety of interfacing and signal processing modules, from data acquisition through signal processing and pattern recognition, to real-time evaluation and control. The experimental results on able-bodied human subjects for controlling two evaluation platforms in real time verified the merit of the MyoHMI platform and demonstrated the feasibility of a low-cost solution for the development of myoelectric controlled applications.