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 HbR signals for all subjects.
Feature combination |
S1 |
S2 |
S3 |
S4 |
S5 |
S6 |
S7 |
Mean and Slope |
56.83 |
54.45 |
61.61 |
59.59 |
55.33 |
56.71 |
62.86 |
Mean and Peak |
92.34 |
92.59 |
90.84 |
91.84 |
88.71 |
86.07 |
87.07 |
Mean and Variance |
82.43 |
86.82 |
82.93 |
85.94 |
82.55 |
79.92 |
79.54 |
Slope and Peak |
86.07 |
86.32 |
79.67 |
85.44 |
85.19 |
83.06 |
84.69 |
Slope and Variance |
79.79 |
87.32 |
82.31 |
85.82 |
80.55 |
76.41 |
77.91 |
Peak and Variance |
85.44 |
86.07 |
82.93 |
87.21 |
86.32 |
76.91 |
84.31 |
Peak and Skewness |
88.33 |
87.21 |
84.44 |
85.94 |
84.94 |
80.81 |
85.44 |
Mean and Skewness |
51.69 |
51.31 |
53.32 |
52.82 |
47.05 |
54.71 |
59.47 |
Slope and Skewness |
52.44 |
52.07 |
57.34 |
51.31 |
51.94 |
47.55 |
54.83 |
Kurtosis and Skewness |
52.94 |
48.81 |
55.21 |
49.43 |
45.42 |
56.46 |
52.69 |
Variance and Skewness |
82.55 |
81.93 |
83.81 |
86.71 |
80.92 |
77.03 |
78.16 |
Peak and Kurtosis |
86.95 |
83.81 |
81.43 |
86.07 |
85.69 |
78.67 |
86.44 |
Mean and Kurtosis |
50.06 |
54.57 |
55.33 |
45.42 |
48.55 |
60.47 |
57.59 |
Slope and Kurtosis |
51.81 |
49.43 |
54.21 |
48.55 |
49.31 |
56.21 |
59.09 |
Variance and Kurtosis |
86.32 |
85.94 |
85.44 |
86.71 |
82.05 |
78.16 |
78.41 |
Inferred neuron-electrophysiology data values
Neuron Type |
Neuron Description |
Ephys Prop |
Extracted Value |
Standardized Value |
Content Source |