Skip to main content

Table 7 GROUP II: classification results and confusion matrices for TEST3

From: EMG-based pattern recognition approach in post stroke robot-aided rehabilitation: a feasibility study

Patient id and classification rate Actual classes Predicted classes
   North East South West
P1 North 66.7 20 25 14.3
53.3% East 16.7 40 41.7 0
South 0 20 33.3 0
West 16.7 20 0 85.7
P2 North 100 0 0 0
70% East 0 87.5 0 0
South 0 0 27.3 0
West 0 12.5 72.7 100
P3 North 66.7 25 0 0
36.7% East 16.7 75 75 50
South 0 0 0 0
West 16.7 0 25 50
P4 North 28.6 12.5 0 12.5
36.7% East 57.1 37.5 14.3 12.5
South 14.3 50 57.1 50
West 0 0 28.6 25
P5 North 25 14.3 0 33.3
43.3% East 37.5 57.1 16.7 0
South 12.5 28.6 83.3 44.4
West 25 0 0 22.2
P6 North 87.5 0 0 0
83.3% East 12.5 71.4 12.5 0
South 0 28.6 75 0
West 0 0 12.5 100
P7 North 100 0 0 14.3
70% East 0 50 55.6 14.3
South 0 50 44 0
  West 0 0 0 71.4
  1. Elements on the left-right diagonal indicate the percentage of correct classification, while elements on the off-diagonals denote percentage of misclassification. SVM was trained (70% of trials) and tested (30% of trials) individually on each patient with the muscle dataset recorded during the experimental session (see Methods); training and testing data were randomly selected and mutually exclusive; test was repeated 5 times for each patient and accuracy rates were averaged across iterations.