Neuromuscular-Activated Armband for Safety Operation of Small Unmanned Aircraft Systems

In recent years, wearable technology using gesture recognition has gained increasing attention in the field of human-machine interaction. One technology proposes the use of myoelectric controllers to collect electromyography (EMG) signals from user’s neuromuscular activation as inputs. Available commercial devices have accomplished gesture control by detecting motion and muscle activation in different groups of skeletal muscle. In addition to wearable technologies, the use of small unmanned aircraft systems (UAS) has seen an increase in popularity. The popularity and affordability of small UAS has also increased the number of new and inexperienced hobbyists and many are concerned that this will lead to the unsafe use of these vehicles. The Federal Aviation Administration (FAA) has proposed a new set of regulations for commercial small UAS. However, few manufacturers have implemented safety features to their UAS. Therefore, we propose to engage in a research project where wearable technology using neuromuscular activation and electrocardiograms signals can be implemented to successfully operate small UAS using safety parameters proposed by the FAA. Our hypothesis is that we can measure abnormal spikes in heart rate and then establish these spikes as a threshold for safety of the UAS user.  Then unexpected spikes in heart rate can be detected and transmitted to an armband.  Using these thresholds, we can change the trajectory of the UAS to avoid collisions with the user.