||The promise of pattern recognition for improved control of upper-extremity powered
prostheses has existed for a long time. During the years of offline research and algorithm
development, very little experience has been gained with real-time use in clinical
settings. Our group, having the benefit of working with subjects who have undergone
muscle reinnervation (TMR) surgery, is at the forefront of real-world application
recognition for upper extremity amputees. Based on our experiences, we highlight a
of myoelectric control schemes from conventional control to enhanced pattern recognition
control, stressing the application of simple pattern recognition schemes to replace
conventional control. These clinically practical pattern recognition systems incorporate
realistic number of electrodes and the ability to control available prosthetic components.
experience suggests how the impending, and initial deployment of pattern recognition-controlled
prostheses for daily use can be more approachable than what is depicted in high-dimension
studies common in the literature today.