FusedNeXt-based anxiety detection from electroencephalography topographic maps: A comparative analysis of alpha, beta, and theta bands

Table 11 Comparison of FusedNeXt with baseline deep-learning architectures under participant-grouped five-fold cross-validation

Band	Model	Parameters (M)	GFLOPs	Window accuracy, %	Participant accuracy, %	Participant balanced accuracy, %	Participant macro F1, %	Participant AUC	95%CI for participant AUC
Alpha	Shallow CNN	1.42	0.31	72.48 ± 1.83	68.45 ± 2.64	68.37 ± 2.58	68.11 ± 2.71	0.7416 ± 0.0264	0.6468-0.8219
Alpha	ResNet-18	11.69	1.82	75.93 ± 1.47	72.31 ± 2.18	72.24 ± 2.09	71.98 ± 2.22	0.7857 ± 0.0219	0.6947-0.8586
Alpha	MobileNetV2	2.23	0.32	75.16 ± 1.61	71.80 ± 2.36	71.72 ± 2.28	71.46 ± 2.41	0.7789 ± 0.0237	0.6862-0.8537
Alpha	ConvNeXt-Tiny	27.82	4.47	76.84 ± 1.42	73.20 ± 2.04	73.13 ± 1.97	72.91 ± 2.10	0.7982 ± 0.0205	0.7086-0.8694
Alpha	FusedNeXt	7.17	1.95	78.21 ± 1.36	74.66 ± 1.92	74.58 ± 1.87	74.31 ± 1.98	0.8104 ± 0.0188	0.7237-0.8796
Beta	Shallow CNN	1.42	0.31	75.66 ± 1.72	71.20 ± 2.52	71.14 ± 2.47	70.88 ± 2.58	0.7794 ± 0.0247	0.6880-0.8532
Beta	ResNet-18	11.69	1.82	79.18 ± 1.39	75.42 ± 2.06	75.36 ± 2.01	75.11 ± 2.13	0.8281 ± 0.0198	0.7461-0.8901
Beta	MobileNetV2	2.23	0.32	78.64 ± 1.48	74.90 ± 2.21	74.83 ± 2.15	74.57 ± 2.26	0.8197 ± 0.0212	0.7356-0.8841
Beta	ConvNeXt-Tiny	27.82	4.47	80.03 ± 1.31	76.55 ± 1.93	76.50 ± 1.88	76.28 ± 1.97	0.8369 ± 0.0185	0.7568-0.8966
Beta	FusedNeXt	7.17	1.95	81.37 ± 1.24	77.84 ± 1.76	77.79 ± 1.72	77.62 ± 1.81	0.8448 ± 0.0173	0.7669-0.9028
Theta	Shallow CNN	1.42	0.31	76.42 ± 1.69	72.10 ± 2.47	72.02 ± 2.41	71.80 ± 2.52	0.7923 ± 0.0239	0.7022-0.8642
Theta	ResNet-18	11.69	1.82	80.36 ± 1.34	76.58 ± 1.98	76.51 ± 1.92	76.27 ± 2.03	0.8396 ± 0.0189	0.7600-0.8991
Theta	MobileNetV2	2.23	0.32	79.74 ± 1.43	75.62 ± 2.13	75.55 ± 2.07	75.30 ± 2.18	0.8318 ± 0.0201	0.7501-0.8934
Theta	ConvNeXt-Tiny	27.82	4.47	81.14 ± 1.26	77.90 ± 1.83	77.84 ± 1.78	77.67 ± 1.87	0.8472 ± 0.0177	0.7698-0.9049
Theta	FusedNeXt	7.17	1.95	82.48 ± 1.18	79.10 ± 1.69	79.05 ± 1.64	78.88 ± 1.73	0.8563 ± 0.0165	0.7817-0.9110

CI: Confidence interval; AUC: Area under the curve; CNN: Convolutional neural network.