Article: Determining Optimal Feature-Combination for LDA Classification of Functional Near-Infrared Spectroscopy Signals in Brain-Computer Interface Application.
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Naseer N; Noori FM; Qureshi NK; Hong KS
Front Hum Neurosci, 2016
The classification accuracies of all 2-feature combinations obtained from HbO signals for all subjects.
Feature combination |
S1 |
S2 |
S3 |
S4 |
S5 |
S6 |
S7 |
Mean and Slope |
53.82 |
50.81 |
50.69 |
59.22 |
59.84 |
55.21 |
59.84 |
Mean and Peak |
94.61 |
96.48 |
90.71 |
91.96 |
90.96 |
91.96 |
94.85 |
Mean and Variance |
86.57 |
87.21 |
81.93 |
82.93 |
82.81 |
75.53 |
83.43 |
Slope and Peak |
87.07 |
83.31 |
80.92 |
85.44 |
83.81 |
83.56 |
81.18 |
Slope and Variance |
86.95 |
88.71 |
83.43 |
82.81 |
81.81 |
76.78 |
80.55 |
Peak and Variance |
89.71 |
89.96 |
83.56 |
87.71 |
87.21 |
83.68 |
81.31 |
Peak and Skewness |
89.08 |
83.44 |
80.55 |
86.71 |
81.81 |
83.06 |
81.05 |
Mean and Skewness |
48.11 |
49.56 |
49.81 |
53.07 |
52.94 |
51.94 |
50.31 |
Slope and Skewness |
47.43 |
50.31 |
47.81 |
53.58 |
52.57 |
54.21 |
50.06 |
Kurtosis and Skewness |
46.17 |
48.55 |
51.56 |
54.21 |
48.93 |
53.58 |
50.56 |
Variance and Skewness |
87.82 |
88.58 |
82.31 |
83.18 |
81.55 |
78.29 |
84.19 |
Peak and Kurtosis |
86.82 |
82.43 |
80.93 |
85.57 |
83.93 |
82.06 |
81.05 |
Mean and Kurtosis |
46.92 |
46.67 |
51.44 |
53.71 |
49.05 |
52.07 |
48.43 |
Slope and Kurtosis |
47.55 |
45.29 |
53.45 |
54.07 |
52.19 |
49.18 |
48.18 |
Variance and Kurtosis |
87.45 |
88.33 |
82.18 |
83.31 |
82.31 |
82.18 |
85.95 |
Inferred neuron-electrophysiology data values
Neuron Type |
Neuron Description |
Ephys Prop |
Extracted Value |
Standardized Value |
Content Source |