Human-Machine Interfacing via Epidermal Electronic Systems

Surface electromyography (EMG) is rapidly becoming a viable control source for interfacing with machines. By measuring the electric potential generated by the contractions of skeletal muscles, systems can be controlled with a mere flick of the wrist, allowing intuitive and versatile control to the wielder. As sensors and classification algorithms become more sophisticated, EMG control has increasing potential to revolutionize the way we interact with and utilize technology. Prosthetics in particular have benefited the most from these recent advances, with one research team successfully returning ambulation to a leg amputee last year. However, this technology is not yet suitable for practical use, as implementations often require bulky hardware and is limited by the complexities of the software. To amend these issues and facilitate further research in this field, we propose a consolidated solution that will handle the acquisition and classification of an EMG input while providing protocols to interface with an external system. Where most setups are cumbersome and impractical, usually requiring a piece of dedicated hardware for each step in the signal chain, we have made our system as small and cost-effective as possible. By consolidating our solution onto a single circuit board with bluetooth integration, we will maximize portability and afford researchers flexibility when working with our system. This portability will allow our device to be placed in close proximity to the EMG sensors to transmit the signal wirelessly to a central hub, which will process it further. Here the central hub will classify the waveform and map it to a definitive command that can be used to interface with an external system. This will abstract the classification aspect away from the developer, simplifying the process and allowing them to focus on what they are trying to accomplish. Our system will also allow for further extension by being robust enough to handle multiple EMG inputs and allowing researchers to easily configure the device for their purposes. To accommodate future advances in classification algorithms or future improvements to the system itself, we will also provide frameworks that will allow researchers and developers to program the device themselves. By giving researchers the tools to quickly implement this technology, we allow them to focus on other aspects of what they are trying to build instead of worrying about the technicalities that go into designing a system like this. Further development in this field will give us unprecedented ways to interact with the world around us and change how we utilize technology. Given this technology’s proclivity towards those who are disabled, our project has the potential to drastically improve the quality of life for the unfortunate as well.https://scholarscompass.vcu.edu/capstone/1040/thumbnail.jp