Pattern recognition controller (PRC) systems for upper-limb prostheses are a clinically established alternative to conventional direct control (DC) systems. For decades, two-site DC has been the primary method for controlling myoelectric upper-limb prosthetic devices. DC relies on surface electromyography (EMG) recordings from two control sites, typically an antagonistic muscle pair in the residual limb, and uses relative signal amplitude to generate movement commands for the prosthesis.
PRC is a more recent, clinically established control strategy developed to address several limitations associated with DC. Rather than depending on isolated activation of two muscle sites, PRC captures EMG signals from multiple sensors across the residual limb and uses pattern-classification algorithms to identify the user's intended movement. By incorporating information from multiple EMG channels, PRC may provide more intuitive and natural control, support a broader range of wrist and terminal device motions, and reduce reliance on non-intuitive switching strategies-particularly during tasks requiring rapid transitions between movements. PRC systems also enable on-demand recalibration, allowing users to adjust control performance in response to day-to-day changes in socket fit or electrode positioning.
Although both PRC and DC systems are clinically established and have been used in practice, this study provides an opportunity to directly compare two clinically established control strategies. This trial will evaluate the functional advantages and disadvantages of PRC relative to DC when used by adults with unilateral transradial limb loss.
