Study of stability of time-domain features for electromyographic pattern recognition

INIS

• classification 100%
• signals 80%
• disturbances 80%
• pattern recognition 80%
• stability 60%
• variations 60%
• muscles 60%
• electrodes 60%
• performance 40%
• fatigue 40%
• accuracy 40%
• man-machine systems 40%
• levels 20%
• patients 20%
• applications 20%
• solutions 20%
• motors 20%
• contraction 20%

Computer Science

• Pattern Recognition 80%
• Classification Accuracy 40%
• Human Machine Interface 40%
• Classification Performance 40%
• Domain Feature 40%
• Location Shift 40%
• Pattern Classification 20%
• Real World 20%
• Classification (Machine Learning) 20%
• Clinical Application 20%
• Feature Individual 20%
• Stability Index 20%
• Domains 20%

Neuroscience

• Pattern Recognition 80%