CTRL-Labs: Hand Activity Estimation and Real-time Control from Neuromuscular Signals

CTRL-Labs has developed algorithms for determination of hand movements and forces and real-time control from neuromuscular signals. This technology enables users to create their own control schemes at run-time -- dynamically mapping neuromuscular activity to continuous (real-valued) and discrete (categorical/integer-valued) machine-input signals. To demonstrate the potential of this approach to enable novel interactions, we have built three example applications. One displays an ongoing visualization of the current posture/rotation of the hand and each finger as determined from neuromuscular signals. The other two showcase dynamic mapping of neuromuscular signals to continuous and discrete input controls for a two-player competitive target acquisition game and a single-player space shooter game.