Background: Electromyography (EMG) pattern recognition offers the potential for improved control of multifunction myoelectric prostheses. However, it is unclear whether this technology can be successfully used by congenital amputees. Objective: The purpose of this investigation was to assess the ability of congenital transradial amputees to control a virtual multifunction prosthesis using EMG pattern recognition and compare their performance to that of acquired amputees from a previous study. Study Design: Preliminary cross-sectional study. Methods: Four congenital transradial amputees trained and tested a linear discriminant analysis (LDA) classifier with four wrist movements, five hand movements, and a no-movement class. Subjects then tested the classifier in real time using a virtual arm. Results: Performance metrics for the residual limb were poorer than those with the intact limb (classification accuracy: 52.1%±15.0% vs. 93.2%±15.8%; motion-completion rate: 49.0%±23.0% vs. 84.0%±9.4%; motion-completion time: 2.05±0.75 s vs. 1.13±0.05 s, respectively). On average, performance with the residual limb by congenital amputees was reduced compared to that reported for acquired transradial amputees. However, one subject performed similarly to acquired amputees. Conclusions: Pattern recognition control may be a viable option for some congenital amputees. Further study is warranted to determine success factors.
Grasping Pattern Recognition and Grasping Force Estimation For Prosthetic Hands