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Table 3 Summary of classification accuracies for each classifier across all participants

From: Applying LDA-based pattern recognition to predict isometric shoulder and elbow torque generation in individuals with chronic stroke with moderate to severe motor impairment

 

Dataset

Class

EMG-TD

Torque

Load cell

EMG + LC

EF

88

89

92

94

AB

76

85

87

90

ER

76

87

89

90

HAB

91

97

97

97

EE

89

97

98

97

AD

78

80

84

87

IR

76

76

83

87

HAD

90

96

96

98

Average

83

88

91

92

  1. EMG-TD refers to EMG time-domain features, Torque to the mean-absolute value (MAV) of torques generated at the shoulder and elbow only, load cell refers to MAV from the raw load cell data, and EMG + LC are the EMG time-domain features and the MAV from the raw load cell data combined together. Bold indicates ≥90% accuracy